kshana-mcp

New in 0.35

What it does, and why

Ledger status

Read

Maritime trust score

kshana receiver-trust scores a vessel's fix from the NMEA 0183 it already has: a 0-100 score, three bands and the reasons, per epoch, in batch, live or as a gate

arithmetic of the monitors VALIDATED (pynmea2, GeographicLib); the score's aggregation MODELLED

Maritime trust

NMEA training streams

kshana nmea-scenario writes synthetic bridge NMEA with scripted jamming, drag-off, time-spoof and replay events and an instructor log, for crew training; text only

stream conformance and decoded values VALIDATED (pynmea2); the receiver, sky and event models MODELLED

NMEA training

Interference map and route exposure

kshana interference-map and route-exposure turn openly licensed ADS-B and AIS reports into a GeoJSON map per day and the share of a route through degraded cells

how the codes are read and the geometry VALIDATED (pyModeS, pyais, shapely, GeographicLib, pyproj); that a cell is interference is not checked

Interference map

Trust telemetry

kshana trust-telemetry exports the trust stream as Prometheus text, OpenTelemetry (OTLP/HTTP) and CEF or LEEF syslog events, so a security operations centre sees a navigation fault

Prometheus, OTLP and CEF VALIDATED against independent parsers; LEEF MODELLED

Trust telemetry

Signed evidence packs

kshana receiver-trust evidence bundles an event window into a hash-chained, Ed25519-signed pack that verifies offline: a technical record, not a legal opinion

integrity, signature and verification VALIDATED (RFC 8032 vectors, FIPS 180-4, a clean-room verifier)

Evidence packs

Test-bench export

kshana bench-export writes a scenario's vehicle motion and events as a CSV trajectory and NMEA for a laboratory GNSS simulator; no signal is written

conversions and encodings VALIDATED (PROJ, GeographicLib, pynmea2, SciPy)

Test bench

Compliance mapping

kshana compliance-report maps run results to clauses of public frameworks, by number only, and says "supports evidence for", never that a framework is met

MODELLED: its references are checked to exist, not that each mapping is right

Compliance mapping

Signal K, OpenCPN and a reference build

the score and its reasons on a boat's Signal K server and in an OpenCPN panel, and a pinned image that rebuilds the engine

MODELLED (an integration run, not an oracle)

Marine integrations

Galileo OSNMA verification

kshana osnma verify checks which satellites' navigation data a receiver can authenticate, from the Galileo signal-in-space specification

VALIDATED against the official test vectors; scope stated in the ledger row

OSNMA

MCP install channels and self-hosting

every channel for kshana-mcp in one place: prebuilt binaries, the Claude Desktop extension, Cursor and VS Code buttons, npx, uvx, Homebrew, Scoop, winget, the registries, and an HTTP mode you host

distribution, not a ledger capability

Install, MCP install, HTTP self-host

Capability

What it answers

Spectrum

how a jammer takes the GNSS L band, band by band, second by second

Clocks and timing

how long each clock holds time after GNSS is lost

Constellations around any body

coverage, dilution of precision and availability around the Earth, the Moon or Mars

Solar system

where every planet is, and the light time of any link

Low-Earth-orbit navigation

a pass, a link, a navigation message and a fused fix, stage by stage

Campaigns

a chained mission, a sweep or a Monte Carlo ensemble in one scenario

Animation

a run's time series as an animated drawing, a player or frames

Reports

every figure with its unit and its label, in HTML (HyperText Markup Language) and JSON (JavaScript Object Notation)

Interoperability exports

orbits and geometry for other tools: SP3, CCSDS OMM and OEM, CZML, KML, GeoJSON, STK and SigMF

Maritime trust

can the bridge trust this fix: a 0-100 score and reasons for a vessel's NMEA, live or from a log (advisory, not type-approved navigation equipment)

NMEA training streams

synthetic bridge NMEA with scripted jamming and spoofing and an instructor log, for crew training (text only; never for a vessel's live navigation systems; advisory, not type-approved navigation equipment)

Interference map

where aircraft and ships reported degraded navigation data, and how much of a route it touches

Evidence packs

a signed, offline-verifiable technical record of a vessel's log window and what the engine computed from it, for an incident report (advisory, not type-approved navigation equipment)

Trust telemetry

the trust stream as Prometheus metrics, SIEM events and optional OpenTelemetry, with a sample Grafana dashboard (deploy/grafana/kshana-gnss-trust.json)

Signal K and OpenCPN

the trust score on a boat's Signal K server and in OpenCPN, with a reference build for a small computer next to the receiver (advisory, not type-approved navigation equipment)

Test-bench export

kshana bench-export: a scenario's vehicle motion and events for a laboratory GNSS simulator (no signal is written), and how to score the receiver's log afterwards

Compliance mapping and report

kshana compliance-report: which rows of public resilience frameworks a set of runs supports evidence for, and the gap that is left

Notebooks

runnable tutorials: vessel trust and training streams, an interference-map route exposure, compliance mapping and the test bench, quantum against classical GDOP

Galileo OSNMA verifier

which satellites' navigation data a receiver can cryptographically authenticate, and why a check fails; Kshana grants no rights under the EU's OSNMA ICD IPRs (see the NOTICE in the page)

Domain

Capability

Orbit & geometry

SGP4/SDP4 propagation (validated to 4.12 mm against all 666 AIAA 2006-6753 vectors); real two-line elements (a committed, date-stamped Celestrak gps-ops snapshot) or synthetic Walker-delta constellations whose mean elements realise the i:T/P/F formula to under 1 km over a 24 h propagation; multi-constellation visibility, dilution of precision — geometric, position, horizontal, vertical and time (GDOP/PDOP/HDOP/VDOP/TDOP), validated to 1e-6 against gnss_lib_py 1.0.4, Stanford NAV Lab (Navigation and Autonomous Vehicles Laboratory), and GNSS availability; a gradient-free constellation-design optimiser, streets-of-coverage minimum-satellite sizing, a multi-constellation comparison tool, and a Walker design sweep that tabulates coverage / PDOP / revisit-time over a planes × satellites grid and reports the Pareto-optimal designs.

Numerical propagator

A Cowell numerical propagator (src/propagator.rs) complementing the analytic SGP4/SDP4 path, with a hierarchical seven-perturbation force model (src/forces.rs): two-body + the full J2–J6 zonal field (the Earth-oblateness zonal harmonic coefficients J2 to J6; the exact analytic gradient of its disturbing potential), an optional EGM2008 tesseral spherical-harmonic geopotential to degree/order 70 (Earth Gravitational Model 2008; src/gravity_sh.rs; real NGA — US (United States) National Geospatial-Intelligence Agency — coefficients, Holmes–Featherstone normalized-Legendre recurrence, cross-checked against the closed-form Legendre functions and the analytic ∇V identity), epoch-driven Sun and Moon third-body gravity (a built-in low-precision ephemeris, no DE/SPK — Development Ephemeris / SPICE Spacecraft and Planet Kernel — kernel), solar-radiation pressure (cannonball model with a conical umbra+penumbra shadow), atmospheric drag (Vallado piecewise-exponential density, co-rotating atmosphere), the post-Newtonian Schwarzschild relativistic correction, and the Lense–Thirring frame-dragging term (IERS — International Earth Rotation and Reference Systems Service — Conventions 2010 §10, linear in Earth's angular momentum, ~1–2 orders below Schwarzschild) — driven by a choice of two adaptive integrators (RK4 — fourth-order Runge–Kutta — step-doubling or the Dormand–Prince RK5(4) embedded pair). Validated against Orekit 12.2 (CS GROUP, Apache-2.0) NumericalPropagator/DormandPrince853 — 275 epochs across LEO (low Earth orbit) + GTO (geostationary transfer orbit), the conservative-force tiers agreeing to a worst-case |Δr| 0.08 m over 24 h (tests/numerical_cowell_propagator_reference.rs); the atmospheric-drag tier is characterised separately (≈ 333 m / 24 h) and the absolute Sun/Moon-ephemeris and density inputs stay honestly Modelled. Additional internal evidence (not external validation): the unperturbed orbit is checked against the exact universal-variable Kepler solution to sub-metre over 24 h, energy/angular-momentum conserve to ~1e-9, and each perturbation matches a hand-derived closed-form signature.

Maneuvers & trajectory design

Impulsive ΔV nodes with 6×6 covariance propagation (ECI — Earth-centred inertial — / LVLH — local vertical, local horizontal — execution-error frames), finite-burn integration checked against the closed-form Tsiolkovsky rocket equation to < 0.01 %, an Izzo-2015 single-revolution Lambert solver, an exact universal-variable Kepler propagator, and a porkchop (launch × arrival) C3 (launch energy) / arrival-V∞ sweep emitted as a JSON contour grid — the performance-simulation layer above GMAT/Orekit, with every Lambert output round-tripped against two-body truth and the porkchop minimum checked against the analytic Hohmann floor.

Time systems & reference frames

IERS leap-second UTC / TAI / TT / UT1 scales (Coordinated Universal Time, International Atomic Time, Terrestrial Time, and the Earth-rotation time Universal Time 1), a Julian-date API (application programming interface), the IAU-2000 (International Astronomical Union) Earth Rotation Angle (ERA), GMST-based (Greenwich Mean Sidereal Time) TEME ↔ ECEF (true equator, mean equinox ↔ Earth-centred, Earth-fixed) with WGS-84 (World Geodetic System 1984) geodetic frames, IAU 2006 precession (Fukushima–Williams), full IAU 2000A/2000B nutation, IERS polar motion, and the equinox-free CIO-based IAU 2006/2000A GCRS↔ITRS reduction (CIO = Celestial Intermediate Origin) — all validated bit-for-bit against the SOFA/ERFA vectors, and independently cross-checked against ANISE (the pure-Rust NAIF/SPICE reimplementation; NAIF = the Navigation and Ancillary Information Facility of NASA, the US National Aeronautics and Space Administration): kshana's GCRS→ITRS vs ANISE's ITRF93 (International Terrestrial Reference Frame 1993) from JPL's earth_latest_high_prec.bpc, the same IERS Earth-orientation parameters fed to both, agree to ≤ 0.86 m on the ground / ≤ 3.6 m at GNSS orbit (max 0.028″) across eight epochs 2020–2023.

Inertial

Three-axis strapdown INS — quaternion attitude, WGS-84 NED (north-east-down) mechanization, coning/sculling compensation, and a deterministic IMU error model (scale-factor, misalignment, g-sensitivity, quantization, drift); a first-principles cold-atom-interferometer accelerometer (Mach–Zehnder phase, quantum projection noise, contrast decay, vibration coupling) that derives the velocity-random-walk coefficient; and a sequential-importance-resampling particle filter for map-aided (terrain-/gravity-referenced) GPS-denied navigation.

Alt-PNT (GPS-denied)

A cold-atom gravimeter measurement model whose white-noise floor (σ = ASD/√τ, ASD = amplitude spectral density) is derived from the CAI accelerometer physics; a low-degree, fully-normalised spherical-harmonic gravity-anomaly field (checked against the closed-form Legendre functions and a hand-derived single-term anomaly) plus synthetic mascons; the gravity-functional synthesis kernel (gravity_sh::gravity_magnitude / gravity_disturbance_mgal) — the "map reader" a gravity-aided navigator matches against — is validated against the GRS80 normal-gravity standard (Geodetic Reference System 1980), reproducing the closed-form Somigliana normal gravity and the published γ_e / γ_p to 3.5e-12 and producing a physically-bounded disturbance map from the real ICGEM (International Centre for Global Earth Models) EGM2008 field (RMS — root mean square — ≈ 26 mGal, max ≈ 89 mGal at d/o 70; tests/icgem_gravity_reference.rs); and a gravity-map-matching particle filter that recovers a GPS-denied track from the anomaly sequence it flies through. It extends to terrain-referenced navigation (TERCOM/SITAN — terrain contour matching / Sandia Inertial Terrain-Aided Navigation — against an SRTM (Shuttle Radar Topography Mission) .hgt DEM (digital elevation model), src/altpnt/terrain.rs), an IGRF-14 geomagnetic main field (14th-generation International Geomagnetic Reference Field) to degree/order 13 (src/igrf.rs, checked against the tilted-dipole closed form and ∇V finite differences), and a combined gravity + magnetic + terrain navigator that fuses all three scalar channels through one particle filter (information is additive — no channel makes the fix worse). A 60-minute GPS-denied benchmark (a ~700 km / one-hour outage where the inertial solution drifts to ~70 km) is recovered to ~145 m (< 500 m) by a hierarchical coarse-to-fine matcher — the ESA NAVISP (Navigation Innovation and Support Programme) Quantum Wayfarer target.

Fusion

Loosely-coupled 15-state GNSS/INS error-state EKF (extended Kalman filter) with closed-loop feedback (the gnss-ins pack); a tightly-coupled pseudorange update that keeps correcting with fewer than four satellites; a coupled clock + position filter; a general unscented (sigma-point) Kalman estimator for strongly nonlinear measurements; a tightly-coupled GNSS/INS UKF navigator (pseudorange + Doppler) whose force-model orbital coast is self-consistency-checked to 0.77 m RMS over a 30-minute curving LEO pass that includes a 120-second GNSS outage (a filter-consistency figure, not an external-oracle validation — this navigator stays MODELLED); and a full 17-state tightly-coupled GNSS/INS UKF (position, velocity, attitude error, accelerometer and gyro biases, clock bias and drift) whose quantum-CAI dead-reckoning coasts a 120-second outage on the cold-atom accelerometer's derived velocity-random-walk.

Orbit determination

Recovery of an orbital state [r, v] from ground-station range tracking, composing the two-body + J2 force model and RK4 integrator with a Gauss–Newton batch corrector (determine_orbit_batch, sub-metre / mm·s⁻¹ from noiseless ranges, ~2 m at a 5 m noise floor) and a sequential unscented-filter variant (determine_orbit_sequential).

Observability & estimation theory

A general, reusable Fisher-information / Cramér–Rao layer (src/fim.rs): the information matrix M = HᵀWH, the Cramér–Rao lower bound, observability rank and datum-defect null space (Moore–Penrose pseudo-inverse), and D/A/E/T-optimal experiment-design scalars from a symmetric Jacobi eigensolver. Validated — eigenvalues vs numpy.linalg.eigh, the CRLB covariance vs σ²(XᵀX)⁻¹ via numpy.linalg.inv, and GNSS DOP from the information matrix, all matched to 1e-9 (tests/fim_observability_reference.rs), and additionally cross-checked against the Kay (1993) closed-form bounds with Monte-Carlo CRLB attainment. It underpins the DOP engine, the passive-geolocation CRLB, and the lunar absolute-station observability theorem (below).

Lunar & cislunar

An Earth–Moon circular restricted three-body (CR3BP) propagator in the rotating frame — conserved Jacobi constant and all five Lagrange points (src/cr3bp.rs) — now with a 6×6 state-transition matrix (STM) and a single-shooting differential corrector (cr3bp_jacobian, propagate_state_stm, differential_correct_halo) that produces genuinely periodic halo / NRHO (near-rectilinear halo orbit) orbits: the STM is validated against finite differences, corrected orbits close to machine precision, and seeding the published apolune state reproduces the L2 southern 9:2 NRHO (L2 = the second Earth–Moon Lagrange point; the Gateway orbit) at period ≈ 6.57 d / perilune ≈ 3,250 km, consistent with the published ≈ 6.56 d / ≈ 3,370 km (a CR3BP — circular, Sun-free — solution, not validated against a real LANS (Lunar Augmented Navigation Service)/Gateway ephemeris; the selenocentric MCI/MCMF (Moon-centred inertial / Moon-centred, Moon-fixed) transform of the corrected orbit is a follow-on); plus LunaNet / LNIS (LunaNet Interoperability Specification) cislunar PNT geometry (MCI↔MCMF reduction, selenographic coordinates) with a lunar south-pole ARAIM pass that honestly surfaces the integrity gap: a ~30 m σ_URE (user range error) drives the protection level well above a 50 m alert limit (src/lunar.rs, scenarios/lunanet-araim.toml); and a surface-beacon DOP augmentation (src/lunar_beacon.rs) showing how a few surveyed surface ranging beacons supply the low-elevation, wide-azimuth line-of-sight rows an all-overhead orbit-only set lacks — collapsing the ill-conditioned south-polar GDOP and, via a root-sum-square error budget, the realized position accuracy in metres (reusing the gnss_lib_py-validated DOP kernel and the airless-horizon visibility closed form; the dilution-of-precision analysis is written up in arXiv:2607.06212).

Lunar PNT suite

A modelled lunar/cislunar navigation suite layered on the CR3BP core, each a runnable kind: Lunar Coordinate Time (lunar-time-offset, src/lunar_time.rs — the secular LTC/TCL − TT rate (LTC = Lunar Coordinate Time; TCL = its French form, Temps-Coordonnée Lunaire) from the self-potential difference + kinetic term, reported with the published 56–59 µs/day band); a geodetic lunar VLBI (very-long-baseline interferometry) delay observable (lunar-vlbi, src/lunar_vlbi.rs — an Earth-baseline near-field two-range-difference delay + rate, cross-checked against the same-codebase plane-wave Δ-DOR (delta differential one-way ranging) in the far-field limit, partials finite-difference-verified); a joint multi-technique OD + clock batch estimator (lunar-joint-od-clock, src/lunar_combination.rs — a Gauss–Newton fit fusing VLBI + lunar-local ranges + inter-satellite ranges) carrying a Fisher-information observability result: internal ranging alone leaves a six-degree-of-freedom rigid-body datum defect, so a surface station's absolute position is unobservable until an Earth-frame tie is added — an Earth-baseline VLBI delay restores observability for a sparse constellation and sharpens the Cramér–Rao bound for a rich one, the absolute datum closing at three non-collinear Earth stations (the observability result written up in arXiv:2607.02566); reference-frame realisation (lunar-frame-realisation, src/lunar_frame_realise.rs — a 7-parameter Helmert datum fit + IAU 2015 WGCCRE orientation tie — WGCCRE = the IAU Working Group on Cartographic Coordinates and Rotational Elements); a Moonlight/LCNS-class service-volume analysis (LCNS = Lunar Communications and Navigation Services; moonlight-service-volume, src/lunar_service.rs — DOP / coverage / availability + a generalised lunar ARAIM HPL/VPL (horizontal/vertical protection level) envelope, reusing the gnss_lib_py-validated DOP kernel and the LunaNet σ_URE≈30 m machinery); lunar differential PNT (lunar-differential-pnt, src/lunar_dpnt.rs — a lunar differential-GNSS / satellite-based-augmentation-system (SBAS) analogue: exact common-mode clock cancellation + first-order spatial decorrelation vs baseline, reusing the DO-229E SBAS protection level — DO-229E being the RTCA (formerly the Radio Technical Commission for Aeronautics) minimum operational performance standard for SBAS receivers); and a LunaNet/IOAG-aligned interoperability export (IOAG = Interagency Operations Advisory Group; lunar-interop-export, src/lunar_interop.rs — CCSDS-OEM (Orbit Ephemeris Message) + lunar-time-scale round-trip in the IAU 2015 lunar body frame, wrapped in the KIF envelope). All MODELLED against internal consistency / reference implementations from illustrative public-source parameters — not validated against real VLBI/Gateway tracking, not affiliated with or endorsed by any agency, no TRL (technology readiness level) / heritage claim.

Deep-space & Mars PNT

An open radiometric navigation engine: iterative light-time + Shapiro relativistic delay, two-/one-/three-way Doppler & range (Moyer two-leg), coherent transponder turnaround ratios, regenerative/PN (pseudo-noise) ranging (CCSDS 414, the pseudo-noise ranging standard), and Δ-DOR plane-of-sky (CCSDS 506, the Delta-DOR standard), with solar-plasma/tropo/iono media; CCSDS-TDM (503) tracking-data-message parse + emit; a reduced-dynamic Square-Root Information Filter (RTN — radial, transverse, normal — empirical accelerations + a 3-state onboard clock + Mars atmospheric drag) that does Mars-LMO orbit determination to ≈ 0.2 m in a synthetic closed loop; a joint one-way + two-way fusion estimator; a multi-body dynamics core (Body{μ, re, zonals, gravity, IAU-pole}, Mars GMM-3 (Goddard Mars Model 3) gravity, an IAU body-fixed Mars frame, a pluggable EphemerisProvider seam, two-part Julian dates + TT↔TDB (Barycentric Dynamical Time)); and the mars-pnt relay-PNT scenario (a MARCONI areostationary relay constellation) with an end-to-end GSE performance simulator (GSE = ground-support equipment) (geometry → link budget → observables → SRIF → covariance). Simulation-validated (covariance / closed-loop figures of merit); the Sun-central Mars dynamics are cross-checked against JPL DE440 (137 m @ 1-day arc, xval/anise-mars-od). Real DSN/ESTRACK tracking-data validation is on the roadmap.

Solar system & any-body PNT

A kernel-free whole-solar-system ephemeris (src/ephem.rs, src/ephem_provider.rs): every planet from the JPL Standish Keplerian elements (Table 1, 1800–2050 AD; Tables 2a/2b, 3000 BC–3000 AD) with each planet's published nominal error, the Earth and Moon split by the lunar series, and Phobos, Deimos, Io, Europa, Ganymede, Callisto and Titan from JPL mean elements and the IAU (International Astronomical Union) rotation model; any body relative to any other in the ICRF (International Celestial Reference Frame). Body now carries GM (gravitational parameter), radii, J2 (the second zonal harmonic) where published and the IAU pole and prime meridian for eighteen bodies. The solar-system kind reports positions, velocities, constants, light time and one-/two-way range between any two bodies (the existing radiometric light-time solver, with the solar Shapiro delay) and an orbit track per body — enough to draw an interactive solar system; the body-pnt kind positions an orbiter or a lander around any body (scenarios/mars-orbit-pnt.toml, scenarios/europa-surface-pnt.toml) with a local Walker constellation, the dilution-of-precision and Gauss–Newton machinery, and a deep-space range from Earth. Validated against JPL Horizons (DE441, JPL Development Ephemeris 441): Mercury–Saturn and the Earth from Table 1 within twice the nominal error (worst 1.87×), all eight planets from Tables 2a/2b (worst 1.71×), and the Earth–Mars/Jupiter light time. Modelled: Uranus and Neptune from Table 1 (2.0× and 5.2× the stated error against DE441), Pluto, the moons, and the body-pnt navigation results.

Fused MEO + LEO PNT

src/leo_fusion/: system-agnostic LEO positioning, navigation and timing over any constellation (Walker shells, element sets, GNSS presets) and any signal (carrier, chip rate, C/N0 envelope, signal-in-space range error), with optional one-file presets carrying their sources (Xona Pulsar X1/X5, Iridium STL, Starlink signals of opportunity, CentiSpace, a representative C-band system, the ATOMIC zero-clock ephemeris model). leo-pvt: batch Doppler positioning from range rate (single- and multi-satellite, clock-drift and velocity states, single-pass along/cross-track geometry and the mirror solution), joint GNSS + LEO weighted least squares with per-system inter-system biases and caller-supplied per-signal sigmas, the DOP against the number of LEO satellites, polar and Arctic coverage, and LEO time transfer to UTC against C/N0 and the oscillator. leo-ppp: a float PPP (precise point positioning) EKF (extended Kalman filter) with GNSS only and with LEO, its convergence time and a chi-square NEES consistency test. ntn-positioning: 5G non-terrestrial-network positioning from the Cramér-Rao bound of the bandwidth. Validated: the LEO Doppler envelope against the published Iridium and Xona figures. Modelled: the rest, with the PPP trend compared against Li et al. (2019) — see docs/LEO-PNT-FUSION.md.

Integrity

Snapshot and solution-separation (ARAIM-style) RAIM — receiver autonomous integrity monitoring — with horizontal/vertical protection levels (HPL/VPL), fault detection & exclusion, and Stanford integrity diagrams; an explicit integrity-risk-budget multiple-hypothesis solution separation (MHSS) protection level, including the dual-/multi-constellation constellation-wide fault mode (EU (European Union) ARAIM / DO-316, the RTCA performance standard for GPS airborne equipment with aircraft-based augmentation), exercised on a real GPS + Galileo snapshot (scenarios/araim-gps-galileo.toml). The protection level applies the one-sided nominal-bias projection `b_k = Σ_i

Augmentation (SBAS)

SBAS / WAAS protection levels (WAAS = the Wide Area Augmentation System) in the DO-229E weighted-least-squares form (precision-approach and en-route K-factors) and the L1/L5 dual-frequency ionosphere-free combination (L1 and L5 being two GPS civil signal bands; IS-GPS-705, the GPS interface specification for the L5 signal, γ₁₅ ≈ 1.793) that underpins DO-316 — src/sbas.rs. The protection-level algorithm is externally validated against the RTKLIB SBAS-PL fork (RTKLIB = the open real-time-kinematic positioning library; PL = protection level) (zsiki/rtklib_ws waasprotlevels(), Siki & Takács 2017, DO-229D — the previous revision of DO-229 — App. J) run on real EGNOS data (European Geostationary Navigation Overlay Service), reproducing its HPL to < 2e-3 m (tests/sbas_reference.rs); gLAB (the GNSS Laboratory tool suite) v6.0.0 confirmed the identical convention.

Clock & timing

Two-state Kalman holdover (Joseph-form covariance, NIS/NEES — normalised innovation squared / normalised estimation error squared — consistency health); Allan-family stability (ADEV / MDEV / TDEV / HDEV / MTIE — Allan, modified Allan, time and Hadamard deviation, and maximum time interval error) with noise-type-specific confidence intervals and a full IEEE-1139 five-coefficient power-law fit (IEEE Std 1139, the Institute of Electrical and Electronics Engineers frequency-and-time metrology definitions) — the estimators are validated on real hardware against Stable32: a real 5071A caesium primary standard vs a hydrogen maser (556,990 phase samples, 16 averaging factors, OADEV/OHDEV — overlapping Allan/Hadamard deviation — to 1e-3; tests/cs5071a_reference.rs) and the canonical Stable32 PHASE.DAT regression series (139 averaging factors, OADEV/MDEV/TDEV to 1e-3; tests/phasedat_reference.rs); the ADEV/MDEV/TDEV estimators and the telecom MTIE wander metric are additionally cross-checked against the independent allantools 2024.06 library to < 1e-9 on the NIST SP 1065 series (tests/mtie_reference.rs, tests/mdev_tdev_reference.rs); geometric corrections (Sagnac, GNSS common-view); and the operational transfer methods — TWSTFT (two-way satellite time and frequency transfer) with the BIPM (International Bureau of Weights and Measures) Sagnac closed form, GNSS common-view, PPP (precise point positioning) ionosphere-free time transfer, a free-space optical link with turbulence scintillation, and an inverse-variance clock-ensemble (paper) timescale below the best contributing clock. A GNSS-denied clock-holdover calculator (src/holdover.rs) exposes the closed-form van-Loan coast-error growth as a holdover-to-threshold inversion — how long a clock free-runs before its timing error exceeds budget — across representative classical and quantum-clock classes; modelled (cross-checked against the multi-step clock_state covariance recursion), and honest that for a very stable clock the holdover to a tight threshold is set by the assumed long-tau noise floor, not the cited ADEV. A conditional Timing Protection Level (src/tpl.rs) extends holdover to spoofing: a bound on the undetected time error, given an independent cross-check, that composes a k-sigma monitor floor, the van-Loan coast variance over the detection latency, and a CUSUM (cumulative-sum) time-to-alarm. Calibrated on a real recorded spoof (JammerTest 2024) and reproducible via cargo run --example tpl_jammertest; MODELLED composition (no integrity-risk-per-hour budget), conditional on detection — there is no finite unconditional bound.

GNSS measurement domain

Forward pseudorange / Doppler synthesis with Klobuchar (broadcast) and IONEX / TEC-grid (IONosphere map EXchange format / total electron content; measured) ionosphere — including an IONEX file parser, time interpolation between maps, and the thin-shell slant-obliquity mapping — Saastamoinen + Niell troposphere, and snapshot RAIM (HPL/VPL).

Resilience

Link-budget jamming (J/S → effective C/N₀ → loss of lock — jammer-to-signal ratio, carrier-to-noise-density ratio — with the anti-jam spectral-separation factor Q now derived from the actual signal and jammer power spectra via src/navsignal.rs — Q = 1/(R_c·κ), cross-checked in CI against the previous representative constant); a stochastic time-spoof detector (Neyman–Pearson / χ²₁ energy test with closed-form and Monte-Carlo P_fa/P_md and a Security figure of merit (FoM) of 1 − P_md); and a multi-layer spoof detector fusing a RAIM-consistency parity test (with the common-mode blind spot modelled honestly), an RF AGC-power (automatic gain control) monitor, and a signal-quality (SQM — signal-quality monitoring, early-minus-late) monitor; and a quantum-inertial dead-reckoning error budget (QuantumNavBudget, src/inertial/quantum_imu.rs) composing the cold-atom-interferometer white-noise velocity-random-walk with residual bias (cross-checked against the independent AccelModel integrator) and scale-factor error into a position-drift-over-holdover figure — the inertial twin of the clock holdover. A framework-aligned resilience-scoring engine (src/resilience/) maps an architecture's simulated behaviour to per-dimension sub-scores across Kshana's own seven resilience categories (not DHS terms), aligned to the US Department of Homeland Security Resilient PNT Conformance Framework, then studies the decision-stability of any single composite score or maturity Level under a Dirichlet weighting simplex and a five-threat ensemble — Kendall-τ rank instability, top-1 winner flip rate, and common-mode diversity collapse (Hill-N2), with an integrity-hashed assurance report (35 hand-derived oracle tests). Reproducible via cargo run --example resilience_report; MODELLED synthetic architectures, a self-assessment aligned to RPCF v2.0, not a certification. See docs/RESILIENCE-CROSSWALK.md.

Passive RF geolocation

TDOA/FDOA emitter geolocation (time-/frequency-difference of arrival; src/geolocation.rs) — locate a jammer or spoofer (or an opportunistic source for reverse-PNT) from time-difference-of-arrival hyperboloids across a receiver network, solved by Gauss–Newton least squares; adding frequency-difference-of-arrival with moving receivers jointly recovers the emitter's position and velocity, with the Cramér–Rao bound on the position covariance derived from the network geometry. MODELLED (internal-consistency oracles: forward→inverse round-trips, the J·CRLB = I identity, GDOP monotonicity, and the estimator attaining its own CRLB under Monte-Carlo) — a point-source line-of-sight model, no multipath / NLOS (non-line-of-sight), receiver-clock-bias, or refraction terms.

Nav-signal & code tracking

The signal level between the link budget and the measurement domain (src/navsignal.rs): unit-area power spectral densities (PSDs) for BPSK-R(n) (binary phase-shift keying with rectangular chips) and sine-BOC(m,n) (binary offset carrier); the spectral-separation coefficient (SSC) κ = ∫ G_s·G_i df, which derives the anti-jam Q the jamming model uses (Q = 1/(R_c·κ)) from the actual signal/jammer spectra instead of a representative constant; the RMS (Gabor) bandwidth (BOC > BPSK — the ranging-information / Cramér–Rao measure); the coherent early–late DLL code-tracking thermal-noise jitter (DLL = delay-lock loop; Kaplan & Hegarty; ~sub-metre for C/A — the GPS coarse/acquisition code — at 45 dB-Hz); and the multipath error envelope (coherent EML, early-minus-late — narrow-correlator suppression). Validated against closed-form anchors (BPSK self-SSC = 2/(3·R_c), unit-area PSDs, sub-metre C/A jitter). This is signal-performance analysis, not antenna / RF-payload hardware design (a payload partner's role).

Interoperability

RINEX-3 multi-GNSS broadcast-ephemeris ingestion (GPS, Galileo, QZSS — Japan's Quasi-Zenith Satellite System —, BeiDou MEO/IGSO — medium Earth orbit / inclined geosynchronous orbit — via IS-GPS-200, the GPS interface specification; GLONASS, Russia's Global Navigation Satellite System, via PZ-90 — the Russian Parametry Zemli 1990 datum — state-vector RK4) usable as a constellation source (RINEX in, PNT geometry out); a RINEX-3 observation parser (pseudorange, carrier phase, Doppler, signal strength; the 4.00 observation layout is expected to parse but is untested, and RINEX 4 navigation files are refused by name rather than mis-decoded) that now feeds a single-point-positioning (SPP) solver (pvt) — real code observations in, a real receiver position out, validated on IGS data; an SP3-c/d precise-ephemeris reader/writer with 9th-order Lagrange interpolation; and CCSDS OEM 2.0 + OMM (Orbit Mean-elements Message) export for flight-dynamics tools (GMAT, Orekit, STK — Systems Tool Kit); and CCSDS-TDM (503) tracking-data-message parse + emit for deep-space radiometric tracking.

Mission analysis (systems engineering)

First-order mission-design budgets, each a runnable kind: two-body launch & ascent geometry (launch-window — launch azimuth sin Az = cos i/cos lat, minimum inclination, Earth-rotation bonus, dogleg plane-change Δv, daily opportunities; src/launch.rs); an Allen–Eggers ballistic re-entry corridor (reentry — peak deceleration, peak-g velocity/altitude, peak-heating velocity; src/reentry.rs); Earth-observation coverage geometry (eo-coverage — swath / nadir GSD (ground sample distance) / off-nadir access / revisit via the SMAD (Space Mission Analysis and Design) space triangle; src/eo_payload.rs); a 3-DOF attitude & pointing error budget (three-degree-of-freedom; attitude-budget — worst-case gravity-gradient torque + RSS (root-sum-square) pointing budget; src/attitude_budget.rs); ground-station pass prediction (passes — AOS/TCA/LOS, acquisition of signal / time of closest approach / loss of signal, max elevation, access time; src/passes.rs); and a one-way link budget over the CCSDS 401 / DSN 810-005 link equation (the CCSDS radio-frequency and modulation standard / the Deep Space Network link design handbook; link-budget — FSPL (free-space path loss), C/N₀, Eb/N₀ (energy-per-bit to noise-density ratio), margin, closure; src/linkbudget.rs). MODELLED first-order analytic budgets — the pre-hardware layer below STK/GMAT/Basilisk, not a 6-DoF or radiometric replacement.

Decision analysis & trade-off (MCDA)

A full multi-criteria decision-analysis (MCDA) suite (src/mcda/) spanning all four method families — value aggregation (WSM, WPM, WASPAS — weighted sum model, weighted product model, weighted aggregated sum product assessment), distance-to-ideal (TOPSIS, Technique for Order of Preference by Similarity to Ideal Solution), compromise programming (VIKOR, from the Serbian for multi-criteria optimisation and compromise solution), and outranking (PROMETHEE II, Preference Ranking Organization Method for Enrichment of Evaluations; ELECTRE I, from the French for elimination and choice expressing reality), plus ratio-system MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) and proportional COPRAS (Complex Proportional Assessment) — with AHP (Analytic Hierarchy Process) pairwise-comparison priority weighting (Consistency Ratio), a Pareto non-dominated front, weight-sensitivity analysis, and multi-attribute utility scoring. The nine aggregators reproduce the independent third-party libraries pymcdm (WSM / WPM / WASPAS / MOORA / TOPSIS / VIKOR / PROMETHEE II) and pyDecision (ELECTRE I, COPRAS) to < 1e-9, and the AHP priority vector + Consistency Ratio match Saaty's Random-Index table and the SciPy/LAPACK principal eigensolver to < 1e-9 (tests/mcda_*_reference.rs). VALIDATED — the decision layer under the trade-study engine.

Space environment

A space-weather environment model (space-weather, src/space_weather.rs): solar (F10.7 / centred-81-day F10.7a — the 10.7 cm solar radio flux) and geomagnetic (Kp, the planetary K-index, with the definitional Kp↔ap table — ap being its linear planetary amplitude) activity indices, the Jacchia-1971 exospheric temperature they drive (validated vs published solar min/mean/max), and the activity-corrected vs static thermospheric neutral density at altitude — the solar-cycle density dependence the static USSA76 (US Standard Atmosphere 1976) atmosphere omits. MODELLED: a calibrated first-order scale-height coupling, not a data-validated (NRLMSISE — the US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Exosphere model) atmosphere.

AI/ML evaluation & trade

An RF-impairment detection evaluation testbed (impairment-eval, src/impairment_eval.rs): a labelled, parameter-grounded synthetic corpus (nominal / jamming / spoof-time / spoof-position / multipath), a detector-agnostic ROC/AUC (receiver operating characteristic / area under the curve) harness scoring any detector (energy | agc | sqm | parity | fused) with per-class Pd (probability of detection) at a target Pfa (probability of false alarm), and the in- vs out-of-distribution optimism gap (distribution-shift mode). Plus a quantum-vs-classical PNT trade (quantum-trade, src/quantum_trade.rs) quantifying a candidate clock's timing/inertial holdover benefit from a measured-ADEV curve vs a classical baseline, with the long-τ floor caveat carried on the artifact and a GNSS-denied resilience-vs-time envelope. The evaluation metrics (AUC / confusion / Pd-Pmd, Pmd being the probability of missed detection) are validated to an exact match against scikit-learn 1.9.0 — including on real ESA OPS-SAT telemetry (the OPSSAT-AD anomaly-detection dataset, Ruszczak et al. 2025, CC BY 4.0 — Creative Commons Attribution 4.0), where Kshana's Mann–Whitney ROC AUC reproduces scikit-learn's roc_auc_score to < 1e-9 on the held-out test split and a transparent peak-count detector separates the labelled anomalies at AUC ≈ 0.85 (tests/opssat_ad_reference.rs) — and the trade engine's numerical kernels (ADEV NNLS — non-negative least squares — fit, χ² consistency bands, van-Loan clock Q) against scipy 1.17.1; the device-benefit numbers built on top stay MODELLED operating characteristics — never field/IQ (in-phase/quadrature sample) data, no good/bad verdict. Building on the testbed, a deeper optimism-gap study (src/impairment_study.rs, impairment_ml.rs, eval_stats.rs) scores a 13-detector panel (energy/AGC/SQM/parity plus seeded logistic-regression and one-hidden-layer-MLP — multi-layer perceptron — detectors), fits in- vs out-of-distribution scaling laws with a permutation null, and learns a leave-one-out predictor of out-of-distribution degradation from in-distribution statistics (cargo run --example optimism_study). A software-defined-receiver front end (src/sdr.rs — raw IQ/IF (intermediate-frequency) → correlator early/prompt/late taps → SQM) and real-data ingest adapters (src/realdata/ — RINEX, u-blox UBX (the u-blox binary protocol), GnssLogger, JammerTest, Yunnan, SatGrid) let the same detectors run over recordings supplied locally (no datasets are committed). The quantum-vs-classical resilience crossover map under parameter uncertainty (src/crossover.rs; cargo run --bin crossover_study) regenerates the inertial and clock crossover studies behind the Results figures.

Quantum-Enabled PNT demonstrator

Three runnable, MODELLED application areas behind the open engine, each emitting honest TradeEvidence + a representativeness / gaps-to-flight record (src/representativeness.rs): trusted quantum time transfer (quantum-time-transfer, src/timetransfer_chain.rs — an end-to-end optical-lattice-clock + photonic-link vs CSAC (chip-scale atomic clock) + RF two-way budget, with a reused timing protection level, a delay/replay-attack security FoM (1 − P_md), and clock-anomaly detection + CUSUM latency); GNSS-free quantum navigation (quantum-gnss-free-nav, src/quantum_nav_od.rs — a cold-atom-interferometer inertial coast vs a navigation-grade INS over a GNSS outage, honest that with no external fix the accelerometer bias is unobservable so the error still grows); and quantum-system fault/anomaly detection (quantum-anomaly-detect, src/quantum_faults.rs — a labelled fault catalogue with a bootstrap-CI (confidence-interval) ROC AUC from the externally-validated eval_stats and a minimum-detectable-fault at a fixed false-alarm rate). A shared quantum device error-model library (src/quantum_devices.rs) and a unified quantum-vs-classical trade harness (src/qtrade.rs) underpin them. The validated kernels they ride (eval-metrics vs scikit-learn, trade kernels vs scipy) are reused; the device-benefit numbers built on top stay MODELLED — illustrative public-source device/link parameters, models the class, no TRL / flight heritage / certification, no agency endorsement.

Frugal engineering & integrity impact

A cost-per-coverage ROI (return on investment) lens (src/frugal.rs) — cost per unit of delivered coverage for an architecture trade — and a detection-miss → integrity-impact mapping (src/integrity_impact.rs) that turns a monitor's missed-detection rate into its integrity-risk contribution. MODELLED decision-support budgets, additive.

Artifact interchange

The Kshana Interchange Format (KIF) (src/interchange.rs) — a versioned, self-describing envelope wrapping a scenario result with its kind, schema version, and MODELLED/VALIDATED labels, so a stored artifact stays self-documenting and older envelopes remain forward-compatibly readable.

Pack

Scenario

Quantum

Classical

1 — Clock holdover

clock-holdover.toml (20 ns spec)

optical clock holds the full outage

CSAC breaches the spec mid-outage

2 — Inertial dead-reckoning

imu-deadreckoning.toml (100 m spec)

cold-atom: ~41 m, holds full outage

nav-grade: breaches in ~350 s → tens of km

3 — Time transfer (optical inter-satellite link)

timetransfer.toml

optical: ~0.3 mm ranging

RF (TWSTFT): ~150 mm ranging

4 — Hybrid fusion (capstone)

hybrid-pnt.toml

full position+timing for the whole outage

position-limited at ~350 s

Sector

Start with

Defence and security

campaign-jam-spoof-holdover-integrity, spoof-meaconing

Space, Earth orbit

orbit-gnss-challenged, leo-pnt-end-to-end

Moon, Mars and deep space

lunar-relay-constellation, mars-orbit-pnt

Aviation and drones

small-uas-jammed-nav, araim-gps-galileo

Maritime

maritime-strait-jamming, maritime-port-approach-coast

Road

automotive-urban-canyon

Rail

rail-tunnel-coast

Critical infrastructure and timing

clock-holdover, clock-ensemble

Telecom and 5G (the fifth generation of mobile networks)

telecom-prtc-holdover-24h, leo-vertical-5g-network-timing

Science and research

sweep-clock-stability, quantum-pnt-demonstrator.suite

Sector

The question it asks

Start with

Defence and security

How long do our navigation and timing stay trustworthy under jamming and spoofing, and which layers keep us in spec?

campaign-jam-spoof-holdover-integrity, spoof-meaconing

Space: Earth orbit

Does my spacecraft see enough navigation satellites, how long does its clock hold time between fixes, and what would a low-orbit navigation layer add?

orbit-gnss-challenged, leo-pnt-end-to-end

Lunar and deep space

Will a lander, rover or orbiter at the Moon, at Mars or further out get a trustworthy position and time?

lunar-relay-constellation, mars-orbit-pnt

Aviation and drones

After a jammer takes GNSS away, how long does my uncrewed aircraft system (UAS) stay inside its position budget, and is integrity available on my route?

small-uas-jammed-nav, araim-gps-galileo

Maritime

How far across the water does a jammer reach, would a position push be caught, and how long can a ship coast into port?

maritime-strait-jamming, maritime-spoof-position-push, maritime-port-approach-coast

Road and automotive

How far does a car drift under an overpass or past a roadside jammer?

automotive-urban-canyon

Rail

How many seconds into a tunnel can a train still tell which track it is on?

rail-tunnel-coast

Critical infrastructure and timing

If GNSS time is lost or spoofed, how long do a power grid, a trading venue or a data centre keep traceable time?

clock-holdover, clock-ensemble

Telecom and 5G

If the GNSS time reference is lost, does my network clock stay inside the ITU-T masks, and for how long?

telecom-prtc-holdover-24h, leo-vertical-5g-network-timing

Science and research

Can I reproduce, extend and cite a PNT result, down to the seed?

sweep-clock-stability, quantum-pnt-demonstrator.suite

Label

Rows

Meaning

VALIDATED

132

an independent external oracle agrees: real data, an independent implementation or published reference vectors

MODELLED

127

checked against analytic truth or simulation self-consistency, and said out loud

PARTNER

4

owned by a hardware partner; Kshana holds no oracle for it

Status

Capability

Agreement

Reference / oracle

VALIDATED

SGP4/SDP4 propagation

666/666 vectors, worst 4.12 mm

AIAA 2006-6753 (Vallado tcppver.out) + head-to-head vs the independent sgp4 crate

VALIDATED

Reference frames — IAU 2000A/B nutation, IAU 2006/2000A CIO chain, ERA

bit-for-bit (X,Y to 1e-14, s to 1e-18, ERA to 1e-12)

ERFA/SOFA eraXys06a · eraC2ixys · eraEra00 · eraNut00a/b

VALIDATED

GCRS→ITRS vs an independent SPICE engine

max 0.028″ → ≤ 0.86 m ground, ≤ 3.6 m GNSS orbit

ANISE (pure-Rust NAIF/SPICE), same IERS finals2000A EOP, 8 epochs 2020–2023

MODELLED

EGM2008 geopotential (degree/order 70)

acceleration = ∇V to < 1e-6; zonal collapse to validated J2

NGA EGM2008 coefficients + analytic ∇V identity

VALIDATED

Gravity-functional synthesis (gravity-aided / GNSS-free nav map)

GRS80 Somigliana + γ_e/γ_p to 3.5e-12; real EGM2008 disturbance map physical (RMS ≈ 26 mGal, d/o 70)

GRS80 (Moritz 1980, IAG — International Association of Geodesy) Somigliana normal gravity + real ICGEM EGM2008 (tests/icgem_gravity_reference.rs)

VALIDATED

Allan estimators (ADEV/MDEV/TDEV/HDEV) + confidence bands

reproduce reference deviations; χ² bands match

NIST SP 1065 (Riley), 1000-point Table 31/32

VALIDATED

Allan estimators on a real measured caesium clock

OADEV/OHDEV to 1e-3 (observed ≤ 3e-5), 16 averaging factors

Stable32 on a real 5071A Cs vs H-maser, 556,990 pts (tests/cs5071a_reference.rs, data-gated)

VALIDATED

Allan estimators on the canonical Stable32 PHASE.DAT

OADEV/MDEV/TDEV to 1e-3 (observed ≤ 5e-5), 139 averaging factors

Stable32 reference deviations for PHASE.DAT (tests/phasedat_reference.rs, data-gated)

MODELLED

IMU error model — ARW / VRW / bias-instability

recovered to < 5 % (bias-instability < 15 %)

Analog Devices ADIS16465 datasheet; NaveGo reference profile

VALIDATED

Numerical Cowell propagator + force model (conservative tiers)

worst position error 0.08 m over 24 h, 275 epochs (LEO + GTO)

Orekit 12.2 NumericalPropagator/DormandPrince853 (CS GROUP), tests/numerical_cowell_propagator_reference.rs

MODELLED

Cowell drag tier + absolute Sun/Moon-ephemeris & density inputs

drag tier characterised ≈ 333 m / 24 h; unperturbed matches universal-variable Kepler sub-m, energy/momentum ~1e-9

built-in low-precision ephemeris + analytic Kepler

MODELLED

Lambert · Tsiolkovsky · porkchop

round-trip to two-body truth; ΔV < 0.01 %

Izzo 2015 · rocket equation · analytic Hohmann floor

MODELLED

Orbit determination (Gauss–Newton batch)

sub-m / mm·s⁻¹ noiseless; ~2 m at a 5 m noise floor

two-body + J2 over an RK4 arc

VALIDATED

Force-model fit vs Galileo precise ephemeris (full-arc)

0.61 m 3-D RMS, 24 h, d/o-70, force-only

ESA/ESOC ESA0MGNFIN final orbit (E11), real finals2000A EOP

VALIDATED

Force-model fit vs Swarm-A precise ephemeris (reduced-dynamic)

0.10 m 3-D RMS (empirical-tier bound, not a measure)

ESA SW_OPER_SP3ACOM_2_ precise orbit

VALIDATED

Force-model fit vs LRO lunar (honest miss)

6.6 m reduced-dynamic, above the 5 m target

JPL Horizons LRO (NAIF −85) + GRAIL (Gravity Recovery and Interior Laboratory) GRGM660PRIM

MODELLED

Deep-space Mars OD (reduced-dynamic SRIF)

≈ 0.2 m Mars-LMO (simulation FoM, not real-mission)

synthetic closed-loop OD — estimator-machinery validation

VALIDATED

Sun-central Mars dynamics vs JPL DE440

137 m @ 1-day arc (grows with arc = unmodelled n-body)

JPL DE440 via ANISE (xval/anise-mars-od, kernel-gated)

VALIDATED

Single-point positioning vs a surveyed IGS coordinate (real observations)

5.7 m 3-D RMS / 1.1 m horizontal, dual-frequency iono-free code SPP

IGS station ABMF survey + GPS broadcast ephemeris, 2018-05-13 (tests/pvt_abmf.rs)

MODELLED

Tightly-coupled GNSS/INS UKF

0.77 m RMS over a 30-min LEO pass incl. a 120 s outage

force-model coast, hand-derived

MODELLED

GPS-denied gravity-map navigation

~70 km INS drift → ~145 m recovered

ESA NAVISP Quantum Wayfarer target

MODELLED

Terrain-referenced navigation (TERCOM/SITAN)

70 km drift → < 500 m (grid-resolution floor ~140 m)

SRTM .hgt DEM; hand-injected drift (non-circular check)

MODELLED

IGRF-14 main field (degree/order 13)

pole ~80.7°N, dipole ~29.7 µT, physical 22–67 µT band

IAGA (International Association of Geomagnetism and Aeronomy) igrf14coeffs.txt (Schmidt semi-normalised)

MODELLED

Nav-signal modulation & code tracking

BPSK self-SSC = 2/(3·R_c); unit-area PSDs; sub-metre C/A DLL jitter @ 45 dB-Hz

Closed-form SSC/PSD anchors + Kaplan & Hegarty DLL thermal-noise formula

MODELLED

CR3BP halo/NRHO differential corrector

STM = finite differences; orbit closes to machine precision; L2 9:2 NRHO ≈ 6.57 d / perilune ≈ 3,250 km

finite-difference STM check + published L2 southern 9:2 NRHO (≈ 6.56 d / ≈ 3,370 km) — CR3BP, not a real Gateway ephemeris

VALIDATED

ARAIM dual-constellation integrity

constellation-wide fault mode on real GPS + Galileo

EU ARAIM TR (technical report) / DO-316; Celestrak gps-ops 2021-07-28

VALIDATED

GNSS geometry / DOP (GDOP/PDOP/HDOP/VDOP/TDOP)

match to 1e-6 relative across 8 geometries (well-conditioned → near-singular)

gnss_lib_py 1.0.4 (Stanford NAV Lab) — independent library (tests/dop_reference.rs)

VALIDATED

ML detector-evaluation metrics (AUC/ROC/confusion/Pd-Pmd/precision/F1)

exact counts + < 1e-9 over 5 datasets × 24 thresholds

scikit-learn 1.9.0 (Pedregosa et al., JMLR — Journal of Machine Learning Research — 2011) — independent library (tests/eval_metrics_reference.rs)

VALIDATED

Anomaly-detection ROC AUC on real ESA OPS-SAT telemetry

AUC reproduces scikit-learn to < 1e-9; peak-count detector AUC ≈ 0.85 on the labelled test split

scikit-learn roc_auc_score on the OPSSAT-AD test split (Ruszczak et al. 2025, CC BY 4.0) — real OPS-SAT telemetry (tests/opssat_ad_reference.rs)

VALIDATED

Quantum-trade numerical kernels (ADEV NNLS fit · χ² consistency bands · van-Loan clock Q)

NNLS + Q exact; χ² < 5e-4 at operating dof ≥ 48

scipy 1.17.1 — optimize.nnls / stats.chi2.ppf / linalg.expm (tests/scipy_reference.rs)

VALIDATED

MTIE / MDEV / TDEV telecom wander metrics (ITU-T G.810/G.823/G.8261/G.811 — the International Telecommunication Union's Telecommunication Standardization Sector recommendations)

MTIE (9 averaging factors, bit-exact) and MDEV + TDEV (8 factors, < 1e-9 relative) on the NIST SP 1065 LCG (linear congruential generator) series

allantools 2024.06 mtie / mdev / tdev — independent library (tests/mtie_reference.rs, tests/mdev_tdev_reference.rs)

VALIDATED

MCDA trade-study methods — all four decision families, nine externally-validated aggregators (WSM · WPM · WASPAS · MOORA · COPRAS · TOPSIS · VIKOR · PROMETHEE II · ELECTRE I) plus AHP pairwise-comparison priority weighting

scores / rankings / concordance matrices reproduced to < 1e-9

pymcdm + pyDecision (independent third-party MCDA libraries) + Saaty RI (Random Index) / SciPy-LAPACK eig (tests/mcda_*_reference.rs)

VALIDATED

LEO Doppler envelope from the orbit and carrier

Iridium maximum within 5 % of the published ±36 kHz; Xona Pulsar X1 inside the published 32–34 kHz

RNTF LEO PNT test results; Leclère, Marathe & Reid, arXiv:2509.19551 (tests/leo_doppler_reference.rs)

MODELLED

PPP convergence with LEO augmentation

7.4 → 4.8 / 3.2 / 2.7 / 2.3 min with 60 / 96 / 192 / 288 LEO satellites, monotone; filter NEES inside the χ² band

trend compared with Li et al., J. Geod. 93:749 (2019) (9.6 → 7.0 / 3.2 / 2.1 / 1.3 min); constellations and noise not reproduced

MODELLED

Conditional Timing Protection Level (holdover-limited undetected time error under spoofing)

composition reproduces the multi-step clock_state covariance recursion; calibrated on a real recorded spoof

JammerTest 2024 (Zenodo 15911589) scalars + van-Loan / CUSUM closed forms (examples/tpl_jammertest)

MODELLED

PNT-resilience scoring + decision-instability

35 hand-derived oracle tests; byte-deterministic study artifact (fixed seed)

DHS RPCF v2.0 mapping + Dirichlet / Kendall-τ / Hill-N2 closed forms — synthetic architectures, not a certification

MODELLED

RF-impairment optimism-gap study (scaling laws + leave-one-out predictor)

permutation-null significance; byte-deterministic artifact (5 seeds)

synthetic parameter-grounded corpus — the eval metrics are VALIDATED vs scikit-learn (above); the study is MODELLED

CI

Cross-platform reproducibility

bit-identical input + shape goldens on 3 OSes (operating systems)

Linux / macOS / Windows CI matrix, SHA-256 goldens

CI

Test coverage

~95 % line on src/ excluding src/*_data.rs and src/main.rs, gated ≥ 85 %

cargo-tarpaulin (LLVM engine)

Channel

Install

Guide

Try in the browser

open https://kshana.dev

Studio guide

Command line (Rust)

cargo install kshana

Command-line usage

Rust library

cargo add kshana

API reference on docs.rs

Python

pip install kshana

Python API guide

JavaScript and WebAssembly

npm install kshana

npm and WebAssembly guide

AI assistant (MCP server, cargo)

cargo install kshana-mcp

MCP server guide

Docker image

docker run --rm -i ghcr.io/ashfordeou/kshana-mcp

MCP server guide: Docker

Claude Desktop extension

double-click the .mcpb for your system: macOS (Apple silicon) · macOS (Intel) · Windows · Linux (x86-64) · Linux (Arm)

Every MCP install snippet

Cursor (one click)

Add to Cursor (npx) · Add to Cursor (Docker) · npx -y kshana-mcp@0.35.0

Every MCP install snippet

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Install in VS Code (npx) · Install in VS Code (Docker) · npx -y kshana-mcp@0.35.0

Every MCP install snippet

Claude Code

claude mcp add kshana -- npx -y kshana-mcp@0.35.0

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npx -y kshana-mcp@0.35.0

Every MCP install snippet

uvx / pipx

uvx kshana-mcp==0.35.0

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Homebrew

brew install ashfordeOU/tap/kshana-mcp

Every MCP install snippet

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scoop bucket add ashforde https://github.com/ashfordeOU/scoop-bucket && scoop install kshana-mcp

Every MCP install snippet

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winget install AshfordeOU.KshanaMcp

Every MCP install snippet

Prebuilt binary

download kshana-mcp- from the release and check it against SHA256SUMS

Every MCP install snippet

Official MCP registry

search io.github.ashfordeOU/kshana-mcp

Every MCP install snippet

Remote (streamable HTTP), self-hosted

kshana-mcp --http 127.0.0.1:8080

Self-hosting guide

Claude Code plugin marketplace

/plugin marketplace add ashfordeOU/kshana

Using Kshana from an agent

JetBrains IDE plugin

Settings → Plugins → Marketplace → search "Kshana" (plugin ID dev.kshana.ide)

Plugin guide

Signal K plugin

npm install signalk-kshana-trust

Signal K plugin guide

OpenCPN plugin

download the plugin tarball from the release

OpenCPN catalogue submission

Grafana dashboard

import kshana-grafana-*.json from the release

Dashboard source

Reference-build image

docker pull ghcr.io/ashfordeou/kshana-reference-build

Marine integrations

Channel

Command or button

Requires

Pinned form

Claude Desktop extension

double-click the .mcpb for your system: macOS (Apple silicon) · macOS (Intel) · Windows

none

kshana-mcp-<target>.mcpb of v0.35.0

Cursor (one click)

npx (Node) · Docker

Node, or Docker

kshana-mcp@0.35.0 / ghcr.io/ashfordeou/kshana-mcp:0.35.0

VS Code (one click)

npx (Node) · Docker · Insiders (npx)

Node, or Docker

kshana-mcp@0.35.0 / ghcr.io/ashfordeou/kshana-mcp:0.35.0

Claude Code

claude mcp add kshana -- npx -y kshana-mcp@0.35.0 · plugin: /plugin marketplace add ashfordeOU/kshana then /plugin install kshana@ashforde

Node (or Docker)

kshana-mcp@0.35.0

npx

npx -y kshana-mcp@0.35.0

Node 18+

kshana-mcp@0.35.0

uvx / pipx

uvx kshana-mcp==0.35.0 · pipx run kshana-mcp==0.35.0

Python 3.9+ with uv or pipx

kshana-mcp==0.35.0

Docker

docker run -i --rm ghcr.io/ashfordeou/kshana-mcp:0.35.0

Docker

ghcr.io/ashfordeou/kshana-mcp:0.35.0

Homebrew

brew install ashfordeOU/tap/kshana-mcp

brew

formula for v0.35.0

Scoop

scoop bucket add ashforde https://github.com/ashfordeOU/scoop-bucket then scoop install kshana-mcp

Scoop (Windows)

manifest for v0.35.0

winget

winget install AshfordeOU.KshanaMcp

winget (Windows)

--version 0.35.0

cargo

cargo install kshana-mcp --version 0.35.0

Rust 1.88+

kshana-mcp 0.35.0

Prebuilt binary

the release page: kshana-mcp (Linux x86-64), kshana-mcp-<target>[.exe], checked by SHA256SUMS and gh attestation verify

none

v0.35.0

MCP registry

io.github.ashfordeOU/kshana-mcp (found by registry-aware clients)

a registry-aware client

0.35.0

Remote (streamable HTTP)

kshana-mcp --http 127.0.0.1:8080, self-hosted: see docs/deploy/mcp-http.md

your own host

v0.35.0

Tool

What it does

run_scenario

Run a scenario from a TOML (Tom's Obvious, Minimal Language) definition

list_scenario_kinds

The 75 built-in scenario kinds with descriptions + required/optional fields — so the agent can construct a valid scenario

validate_scenario

Pre-flight check: parse the TOML and detect its kind, without running

list_example_scenarios

The bundled reference scenarios as JSON

get_example_scenario

The TOML text of one bundled reference scenario, byte for byte the file under scenarios/

report_scenario

Run a scenario and return its report

animate_scenario

Run a scenario and return its time series as an animation

Tool

What it does

list_export_formats

Which interoperability formats apply to a scenario (czml, kml, geojson, stk, sigmf), the reason when one does not, and the specification each writer follows

export_interop

Export a scenario as CZML (Cesium Language), KML (Keyhole Markup Language), GeoJSON, STK (Systems Tool Kit) ephemeris .e, or SigMF (Signal Metadata

import_route

Write a GeoJSON LineString route into a scenario that flies a waypoint track (terrain-nav, terrain-slam, gravity-map, combined-altpnt) and return the new TOML

export_sp3

Export an orbit scenario's constellation as SP3-c (Standard Product 3, revision c) precise ephemeris

export_omm

Export an orbit scenario's elements as a CCSDS (Consultative Committee for Space Data Systems) 502.0-B-2 OMM (Orbit Mean-elements Message) catalogue

export_oem

Export an orbit scenario's state series as CCSDS OEM (Orbit Ephemeris Message) 2.0 ephemeris — the TEME (true equator, mean equinox) position and

export_table_csv

Run a scenario and return its reproducibility table as CSV (comma-separated values) — the byte-stable table the CLI (command-line interface) writes as <scenario>.table.csv

export_test_bench

A scenario's vehicle motion and events for a laboratory GNSS simulator (kshana bench-export)

Tool

What it does

assess_receiver_log

Assess a real GNSS (global navigation satellite system) receiver log for trust

assess_vessel_stream

Score a bounded NMEA 0183 excerpt (at most 2 MiB and 20,000 epochs

assess_vessel_log

A vessel's NMEA 0183 log (at most 4 MiB) as a batch run, with the session TOML stating the vessel's limits

create_evidence_pack

A signed evidence pack for a window of a vessel's log (kshana receiver-trust evidence)

attach_evidence_timestamp

Bind an RFC 3161 timestamp token (base64 of the .tsr bytes) to a pack, in memory (kshana evidence attach-timestamp)

verify_evidence_pack

Verify a pack (kshana evidence verify)

generate_training_nmea

Synthetic bridge NMEA 0183 for crew training from a nmea-scenario TOML (jamming, position drag-off, time spoof, replay delay) with the instructor log (kshana-nmea-training/1)

build_interference_map

A GNSS interference map from ADS-B or AIS position reports as CSV text (at most 4 MiB)

route_exposure

The share of a route's length in degraded, not-degraded, unassessed and not-observed cells of one or more interference maps, optionally within a date range

trust_telemetry

A trust stream (JSON lines) or receiver-trust result rendered as Prometheus text, CEF or LEEF syslog lines or an OTLP JSON payload, with the kshana trust-telemetry encoders

Tool

What it does

iq_signals

The GNSS IQ layer's set-up

iq_info

Describe one IQ (in-phase and quadrature) recording in the work directory without processing it

iq_scene

Generate a multi-satellite GNSS IQ scene into the work directory (kshana iq scene)

iq_acquire

FFT (fast Fourier transform) acquisition of one or more PRNs (pseudo-random noise codes) over a recording (kshana iq acquire), optionally behind front-end stages

iq_track

Acquire, then track with the DLL/PLL/FLL (delay-, phase- and frequency-locked loop) bank (kshana iq track), with the loops from a `kshana.loop-desig

iq_frontend

Apply receiver front-end and interference-mitigation DSP (digital signal processing

iq_sweep

Replay one IQ recording in the work directory across several tracking-loop designs (kshana iq sweep)

iq_monitor

Run the interference and spoofing detection monitors over an IQ recording in the work directory (kshana iq monitor)

iq_labfit

Fit the tracking-loop loss-of-lock model to lab runs (kshana iq labfit) from an iq-labfit scenario whose logs are inline (text or base64

iq_test_conditions

Validate a kshana.test-conditions/1 file given as text and return the resolved conditions with their hash

iq_campaign

Run a lab-replay campaign (kshana iq campaign)

iq_campaign_status

A campaign output folder's progress

Tool

What it does

compliance_report

The public-framework mapping filled from result documents given as text (kshana compliance-report)

compliance_mapping

The static mapping tables (or, with sources, the source documents they cite with versions and URLs) as Markdown, led by the same statement

Free

Kshana Pro

Custom study

What it is

the whole open engine, all 75 scenario kinds, no feature gate

a proprietary overlay on the same engine, under contract

a MODELLED PNT-resilience study of your system, done for you

Licence

AGPL-3.0 (GNU Affero General Public License, version 3), or a commercial licence

proprietary

contract

How to start

install or open kshana.dev

request a Pro evaluation

request a study

Paper

What it shows

Engine command

Anticipating the Optimism Gap: Predicting Distribution-Shift Degradation of RF-Impairment Detectors from In-Distribution StatisticsarXiv:2606.22054 · doi:10.48550/arXiv.2606.22054

The drop in a GNSS interference detector's score once conditions shift can be predicted from in-distribution statistics alone, on an open synthetic testbed and then on open field recordings.

cargo run --release --example optimism_study -- paper-artifacts/optimism-study.json

A Conditional Timing Protection Level: Holdover-Limited Undetected Time Error Under GNSS SpoofingarXiv:2606.24210 · doi:10.48550/arXiv.2606.24210

A GNSS timing receiver under spoofing has no finite unconditional bound on undetected time error, so the paper gives a conditional one, calibrated on a recorded over-the-air spoof from the public JammerTest 2024 campaign.

cargo run --release --example tpl_jammertest

How Stable Is a PNT Resilience Score? Decision-Instability of Single-Number Resilience Ratings under Framework-Aligned WeightingarXiv:2607.05415 · doi:10.48550/arXiv.2607.05415

A single composite resilience score is a stable basis for a decision only where one design dominates; where designs contend, re-weighting alone can change the winner.

cargo run --release --example resilience_report -- paper-artifacts/resilience-study.json

Earth-baseline VLBI restores the observability of a lunar surface station in joint orbit-and-clock determinationarXiv:2607.02566 · doi:10.48550/arXiv.2607.02566

Ranging inside a lunar constellation leaves a surface station's absolute position unobservable; a very-long-baseline interferometry (VLBI) delay from Earth restores it when the constellation is sparse, and sharpens it when it is rich.

the lunar-joint-od-clock kind: kshana example lunar-joint-od-clock > s.toml && kshana s.toml

The Cost of Lunar South-Polar Geometry, and Surface Beacons as the Efficient Fix: A Dilution-of-Precision AnalysisarXiv:2607.06212 · doi:10.48550/arXiv.2607.06212

Planned constellations of four to six satellites give poor geometry at the lunar south pole, and a few surface ranging beacons fix it far more cheaply than more satellites.

the lunar-beacon kind: kshana example lunar-beacon > s.toml && kshana s.toml

Figure of merit

How Kshana computes it

Timing Performance (clock/orbit packs)

clock-phase error RMS + 95th-percentile over the outage, in nanoseconds (timing_rms_ns) — a timing metric, not position

Positioning Performance (inertial/hybrid packs)

1-DOF position-error RMS + 95th-percentile over the outage, in metres (pos_rms_m); single-axis. A single run is flagged monte_carlo: false; set runs = N for a Monte Carlo ensemble that reports each metric's mean, spread, and bootstrap 95% CI (confidence interval). Still not a 2-D CEP/2DRMS (circular error probable / twice the distance root mean square) or DOP-weighted accuracy (those need the 3-axis model — roadmap)

Autonomy

holdover duration — time in-spec after GNSS loss (grid-quantised: a lower bound)

Resilience

error-growth slope during the outage

Availability

fraction of the run with an in-spec solution

Integrity

filter self-consistency — fraction of outage samples whose error stays inside the Kalman filter's own k-sigma bound. Not an aviation HPL/VPL/RAIM integrity figure (see docs/INTEGRITY.md)

Security

analytic spoof-detectability bound from clock stability — how small/slow a time-spoof a single-clock consistency monitor could flag. Meaningful only with a configured attack; not a multi-satellite RAIM detector

Channel

Install / get

Contents

crates.io

cargo install kshana · kshana = "0.35"

Rust library + CLI

crates.io

cargo install kshana-mcp

the MCP server

PyPI (Python Package Index)

pip install kshana

abi3 wheels (Linux/macOS/Windows) + sdist (source distribution)

npm

npm install kshana

WebAssembly module + JS wrapper

ghcr.io

docker run -i ghcr.io/ashfordeou/kshana-mcp

multi-arch OCI (Open Container Initiative) image — no toolchain needed

npm

npx -y kshana-mcp@0.35.0

launcher: downloads the release binary, verifies SHA256SUMS, runs it

PyPI

uvx kshana-mcp==0.35.0 · pipx run kshana-mcp==0.35.0

the same launcher for Python

Homebrew · Scoop · winget

brew install ashfordeOU/tap/kshana-mcp · scoop install kshana-mcp · winget install AshfordeOU.KshanaMcp

the kshana-mcp binary, generated from each release's SHA256SUMS

Claude Desktop

double-click kshana-mcp-<target>.mcpb from the release

the extension, with the binary inside

official MCP registry

auto-discovered by MCP clients

io.github.ashfordeOU/kshana-mcp (OCI image, npm and PyPI packages)

JetBrains Marketplace

IDE → Plugins → search "Kshana"

the Kshana — PNT simulator IDE plugin

GitHub Releases

download

the kshana command-line binary for Linux x86-64, macOS (Apple silicon and Intel) and Windows x86-64, the kshana-mcp binary for each of those systems and Linux Arm, a .mcpb Claude Desktop extension per system, a CycloneDX SBOM, SLSA build provenance, an HTML validation summary and a SHA256SUMS checksum file

Zenodo

DOI

a citable archive of every release

kshana.dev

open in a browser

Kshana Studio, the in-browser WebAssembly app, rebuilt from each release tag (so the version it shows is the version it runs)

Document

For whom

What's in it

Concepts primer

everyone, start here

what Kshana does and why, from zero to the physics

Kshana Studio

everyone

run the engine in your browser (WebAssembly); build &amp; deploy notes

Glossary

everyone

plain-language definitions of every term

Architecture

developers / reviewers

module map, engine pipeline, dispatch, and diagrams

Validation status

reviewers / citers

what is validated vs not modeled, with evidence

Verification matrix

reviewers / citers

the machine-checked evidence ledger — every capability row with its status, module, test and external oracle, generated from src/verification.rs

Modelled rationale

reviewers

why each Modelled row has no external oracle, stated row by row

Provenance

reviewers / citers

every sensor parameter, model, and dataset traced to its published source, in one citable table

Reproducibility &amp; provenance

reviewers / packagers

determinism guarantees, golden-pinning, SBOM (software bill of materials), build provenance

Wheel platform tags

packagers

the abi3 Python wheel matrix — which platform tag pip install kshana resolves

Positioning

evaluators

where Kshana sits vs RTKLIB/gLAB (complementary), and the zero-install browser tier

Kshana Pro

evaluators / programme managers

what the proprietary Pro overlay adds over the same engine: design optimiser, uncertainty and sensitivity, mission dossier, campaign watch, spectrum coexistence, on-premises job service, requirements traceability; what each produces and what it does not do

Technical report · JOSS paper

reviewers / citers / evaluators

the full extended research paper — architecture, per-domain models, validation, case studies, and limitations — plus the concise JOSS (Journal of Open Source Software) submission

SGP4 validation

reviewers / citers

agreement with the AIAA 2006-6753 reference (666 states, ~4 mm) and a head-to-head against the independent sgp4 crate (agree to sub-micron / 4.12 mm)

Force-model validation

reviewers / citers

the full-force engine (src/precise_od.rs) fit to agency ephemerides — methodology and validated residuals

Real TLE guide

users

driving scenarios from real Celestrak / Space-Track constellation TLEs (vs the bundled synthetic Walker set)

Integrity FoM

evaluators

what the integrity / security figures mean — and what they are not vs aviation HPL/VPL

ARAIM reference

reviewers / integrators

the open MHSS ARAIM protection-level implementation — the b_k nominal-bias projection, σ_URA vs σ_URE, and the fault-mode priors

Quantum models · details

reviewers

the cold-atom-interferometer physics layer, and where coefficients are still looked up

Compliance

evaluators

DO-229E / DO-316 algorithm scope, and what is not a conformance claim

Maritime trust

mariners / integrators

the 0-100 GNSS trust score for a vessel's NMEA, its monitors and its limits (advisory, not type-approved navigation equipment)

NMEA training streams

maritime trainers

synthetic bridge NMEA with scripted jamming and spoofing and an instructor log; text only, never for live navigation

Interference map

analysts / mariners

where aircraft and ships reported degraded navigation data, and how much of a route it touches

Evidence packs

operators / insurers

signed technical records of a trust event and how to verify one

Trust telemetry

operations / security teams

the trust stream as Prometheus metrics, SIEM events and OpenTelemetry, with a Grafana dashboard

Marine integrations

boat owners / integrators

the Signal K plugin, OpenCPN gate mode and the reference build

Test bench

receiver makers

replaying an exported scenario through a laboratory simulator and scoring the receiver's log

Compliance mapping

evaluators

public resilience frameworks mapped to Kshana outputs, with sources and gaps; kshana compliance-report

Notebooks

users

runnable tutorials with their rendered text

Standards &amp; interoperability

integrators

the GNSS / flight-dynamics / agency interchange formats Kshana reads and writes (RINEX, SP3, CCSDS OEM/OMM/TDM/Space-Packet, …)

LEO PNT fusion

users / evaluators

fused MEO + LEO positioning, navigation and timing: Doppler, joint pseudorange, PPP convergence, 5G NTN, polar coverage and LEO time transfer over any constellation; the optional presets and their public sources

Campaigns

users / evaluators

composing scenarios: chained mission timelines, parameter sweeps, Monte Carlo ensembles and shared-condition runs, with the composition identities the tests pin

Scenario catalogue

users / integrators

every dispatchable kind with its required and optional TOML fields — generated from api::list_scenario_kinds()

Result schema

integrators

every field of the result JSON, with units and a source pointer

Python API

Python users

the PyO3 binding surface — calling the engine, the scenario/result types, and examples

Claims vs reality

reviewers

the overclaim-closure ledger + the CI guard (tests/no_overclaims.rs) that keeps it resolved

Roadmap

everyone

the phased roadmap — what has shipped and what is next

MCP server · JetBrains plugin

agents / IDE users

run Kshana from an AI assistant or a JetBrains IDE

Agent guide · Surfaces

agents / integrators

which tool answers which question, what to keep with each answer; where each capability is reachable (CLI, Rust, Python, WASM, MCP, plugin, JetBrains, notebooks) and why a cell is N/A

Changelog

everyone

released history (Keep a Changelog + SemVer, Semantic Versioning)

Contributing

contributors

build, guards, test/citation discipline, DCO (Developer Certificate of Origin)

Governance

contributors / community

how Kshana is governed — who decides, how, and the open/closed boundary

Code of Conduct

community

expected conduct (Contributor Covenant)

Security policy

reporters

how to report a vulnerability; dual-use note