arXiv subjects

Chakshu Baweja

Publications and source records attributed to Chakshu Baweja.

5 recordsLinked to original sources

arXiv2026

The Cost of Lunar South-Polar Geometry, and Surface Beacons as the Efficient Fix: A Dilution-of-Precision Analysis

Lunar PNT architectures, NASA's Lunar Augmented Navigation Service (LANS), ESA's Moonlight, and allied concepts, place a small number of satellites in elliptical lunar frozen orbits (ELFO) to serve the south-polar region prioritized for exploration. We report a result that reframes the design trade: for a user at the lunar south pole, the satellite count needed to reach good geometry is roughly double what is currently planned, because the visible satellites cluster into a small solid angle overhead and dilution of precision is limited by their angular spread rather than their number. In a time-averaged simulation, orbit-only ELFO constellations of the planned size (4 to 6 satellites) give a south-polar median geometric DOP (GDOP) of 16 to 21, far worse than the GDOP of about 6 routine for terrestrial GNSS, and the constellation must grow to about 12 satellites before the median GDOP crosses 6. We then show that a small number of surface ranging beacons, a configuration absent from the lunar PNT literature, reaches the same geometric quality far more cheaply by supplying the near-horizon diversity the overhead cluster lacks: three beacons on elevated terrain around a -80 deg latitude user cut the median GDOP from 16.2 to 1.6, a factor of about 10, moving the user from 15% to 100% of the time below GDOP 6, geometry a purely orbital solution reaches only near a 24-satellite fleet. Because there is no atmospheric refraction, surface-to-surface line of sight is bounded by the geometric horizon, so beacon siting on crater rims and elevated terrain is itself a design variable. Surface-beacon augmentation is the lowest-cost, highest-leverage improvement available to lunar south-polar PNT, deployable on assets already planned for the region. The geometry engine is Validated against an independent DOP computation; the constellation and beacon scenario are Modelled.

astro-ph.EP↗

arXiv2026

Earth-baseline VLBI restores the observability of a lunar surface station in joint orbit-and-clock determination

Lunar positioning, navigation, and timing (PNT) is moving from concept to hardware, ESA's Moonlight/LCNS, NovaMoon reference stations, LunaNet, and Coordinated Lunar Time, all reducing to one estimation core: fix the orbits and clocks of the lunar infrastructure and tie them to an Earth/inertial frame. We ask which measurements make a surface station's absolute position observable, and prove the answer. In a snapshot batch fit, the internal observables (station-to-satellite and inter-satellite ranging plus clock-sync) constrain only relative geometry and leave a six-dimensional rigid-body datum defect: three translations and three rotations of the cluster. The clocks are fully observable, so the defect is purely positional, and closing it needs a tie to the Earth frame. Two such ties exist and are not interchangeable. An indirect tie (Earth-to-satellite ranging through the constellation) reaches the station only when the satellite geometry is rich; a direct tie (an Earth-baseline VLBI delay to the station beacon) fixes it regardless. This gives a conditional design law, not a single number: VLBI restores absolute observability when the constellation cannot supply it, and merely sharpens the bound when it can. For a sparse three-satellite constellation the station lies in the null space of the Fisher information until VLBI is added, reaching a Cramer-Rao bound of 20.1 m; for a rich six-satellite constellation VLBI tightens the bound from 23.2 m to 9.7 m. A single-epoch baseline informs at most two of three axes, so the datum closes at three non-collinear Earth stations. The Gauss-Newton estimator attains the bound (efficiency 1.02), with a 91x median station-error improvement in the sparse regime. The FIM/CRLB engine is validated against NumPy and published closed forms; the lunar application stays modelled, every figure deterministic and reproducible.

eess.SP↗

arXiv2026

Anticipating the Optimism Gap: Predicting Distribution-Shift Degradation of RF-Impairment Detectors from In-Distribution Statistics

Detectors for GNSS radio-frequency impairments (jamming, spoofing, multipath) are usually reported with a single AUC measured on the distribution they were tuned on. That number falls once conditions move, and the size of the drop is rarely known in advance because labelled field data is scarce. We ask whether this optimism can be predicted before any out-of-distribution data is seen. On an open, parameter-grounded synthetic testbed with a tunable severity shift, we evaluate thirteen detectors (five physics baselines, full-feature logistic regression and multilayer perceptrons, and single-feature learned controls) across four impairment classes. The optimism gap, the difference between in-distribution and shifted AUC, grows monotonically as the shift deepens (mean Spearman correlation 0.50). It is driven by how many observables a detector uses rather than by whether it is learned, and it varies systematically by class. Centrally, a ridge model built only from in-distribution score statistics predicts the gap for a detector it has never seen (R^2 = 0.47) and for an impairment class it has never seen (R^2 = 0.46); both are significant against a 2000-fold permutation null (p < 0.001) and survive removing the feature that is, by construction, part of the target. The headline findings are synthetic. We then run the pre-registered protocol on three open field corpora: on Jammertest 2024 the cross-detector prediction holds (R^2 = 0.11, p = 0.009), and on SatGrid, whose spoofer power sweep gives a calibrated severity axis, in-distribution AUC overstates higher-severity AUC by up to 0.22 and to the point of sign inversion, with in-distribution AUC and realised gap perfectly rank-correlated (Spearman rho = 1.0). The mechanism survives contact with real data, at smaller magnitude than in simulation. We release the testbed, a software-receiver front end, the ingest adapters and the protocol.

eess.SP↗

arXiv2026

A Conditional Timing Protection Level: Holdover-Limited Undetected Time Error Under GNSS Spoofing

A GNSS timing receiver under spoofing has no nominal-geometry fault for position-domain RAIM to bound: the threat is a slow, common-mode pull of served clock time that the receiver's own time-accuracy flag need not reveal. We make three graded contributions. First, a field measurement: solving the receiver clock trajectory from raw L1 pseudoranges and broadcast ephemeris, we show a recorded over-the-air spoof from the public JammerTest 2024 campaign pulled a u-blox ZED-F9P by about 1.01 ms of served time while it reported at most 51 ns, a gap near 20,000x. Second, an impossibility: against an adversary free to choose the ramp rate, no finite unconditional bound on undetected time error exists under a single self-referential clock-aided monitor, because a ramp slow enough to keep the disciplined reference in lock-step is never alarmed while the error grows without limit, so any finite guarantee is conditional. Third, the conditional bound: the Timing Protection Level (TPL), a model-free monitor's static detectability floor plus the oscillator's coast over the detection latency, holds given detection by an independent cross-satellite consistency check a coherent spoofer does not drive in lock-step. Each term is a closed form over a primitive verified in the open Kshana simulator, so the sum is reproducible by hand. Calibrated on the recorded attack, the budget is 114 ns at one-second recovery and 458 ns at a 60-second coast, thousands of times below the 1.01 ms accepted; a clock-aided sequential test alone gives essentially no protection on this slow ramp (it alarms only near the ~1 ms capture), while the model-free monitor alarms during the ramp. We are explicit: the bound is calibrated, not field-validated; carries no integrity-risk budget; and is reported as a band at long coast. The simulator, bound, and calibration example are open source under AGPL-3.0.

eess.SP↗

arXiv2026

How Stable Is a PNT Resilience Score? Decision-Instability of Single-Number Resilience Ratings under Framework-Aligned Weighting

Authoritative positioning, navigation, and timing (PNT) resilience frameworks (the DHS Resilient PNT Conformance Framework, RPCF, and peers) define what resilience means but supply only self-attestation: a checklist or a maturity Level, with no engine and no measurement. We build the missing measurement layer as an open, deterministic scoring engine over a PNT simulator, emitting per-dimension sub-scores traceable to a scenario and an oracle, and ask whether a single composite score or maturity Level is a stable basis for a decision. Across seven architectures spanning cross-dimension tradeoffs, a Dirichlet simplex over the seven RPCF categories, and a five-threat ensemble, the answer splits in two. The composite winner is stable under active denial and under near-equal weightings (about 1 percent flip rate), so a single number is safe precisely where one design dominates; but re-weighting alone flips it in up to 22 percent of draws under nominal conditions, where designs contend, a known composite-indicator sensitivity. The sharper, weighting-invariant failure is categorical: a weakest-link maturity Level (our minimum-over-categories operationalization of the RPCF ladder, not the framework's rule) depends on the threat assumed, not the architecture, changing for one architecture in seven. Because the composite rewards declared techniques, a constructed single-band receiver declaring all seven outscores a more resilient system: self-attestation can be gamed by declaration. And apparent fourfold GNSS redundancy reduces, by the definition of a shared common-mode failure domain, to an effective diversity of one. Conclusions hold under +/-20 percent perturbation of every driver within the reduction. We report per-dimension sub-scores with provenance and a rank range, not a phantom single number. A self-assessment aligned to RPCF v2.0, not a certification.

cs.CR↗