ALIS (Advanced Location Intelligence System): A Physics‑First Trust Layer for Resilient Positioning and Verifiable Location

Executive Summary

Modern systems do not fail because they lack position. They fail because they act on positions that should not have been trusted.

Position, Navigation, and Timing (PNT) underpins defence, infrastructure, autonomy, and digital trust. Yet most PNT architectures implicitly assume that reported coordinates are truthful if they are precise and continuously available. In contested or degraded environments, this assumption collapses. The central challenge is no longer availability alone, but integrity—whether a location claim can be defended against physical reality under adversarial conditions.

ALIS (Advanced Location Intelligence System) is a physics‑first trust layer designed to address this gap. Rather than producing coordinates by default, ALIS evaluates location assertions against invariant physical structure—principally the Earth's magnetic field—together with inertial and environmental sensing. It does not depend on external transmissions and does not assume the correctness of GNSS.

ALIS treats location as a claim, not a fact. Its function is to bound, verify, and audit location assertions using physics‑constrained evidence. When the environment and measurements support a defensible conclusion, ALIS reports a bounded estimate with explicit confidence. When they do not, ALIS produces an auditable "insufficient evidence" outcome rather than asserting false precision.

The Verification Gap

Current PNT resilience frameworks address what happens when GPS fails. They do not adequately address how to determine whether a GPS-derived position should be trusted in the first place.

Spoofing attacks manipulate receivers into computing incorrect positions from ostensibly valid signals. Signal authentication mechanisms such as CHIMERA and OSNMA verify that navigation messages originate from legitimate satellites, but cannot confirm that the resulting position solution corresponds to the receiver's actual physical location.

An adversary with sufficient capability can produce authenticated signals that yield false positions. The missing capability is independent verification: a physics-based measurement that confirms whether a claimed location is consistent with the geophysical properties of that place.

This exposes a deeper architectural gap: there is no independent, physics‑anchored mechanism for deciding whether a reported location should be believed. Resilient PNT therefore requires more than redundancy or diversity of signals. It requires a trust layer that fails differently from RF‑based services, does not rely on external transmissions, and can explicitly defend or reject location assertions under scrutiny.

Geophysical Fingerprinting

ALIS employs sensor fusion across multiple geophysical dimensions to construct probabilistic location estimates independent of radionavigation signals. The system measures magnetic field vector components, barometric pressure gradients, and inertial signatures using commercial-grade sensors, then matches these observations against pre-characterised reference databases using octree-based spatial probability models.

The fundamental insight is that every location possesses a unique geophysical signature that cannot be replicated or transmitted remotely. The Earth's magnetic field exhibits stable structure across global, regional, and local scales—the main field generated by convection in the liquid outer core, with crustal anomalies superimposed from magnetised geological structures and ferromagnetic infrastructure. Barometric microstructure reflects local terrain and atmospheric conditions. These properties are measurable, persistent, and resistant to electronic manipulation.

Unlike satellite or terrestrial RF signals, the quasi‑static magnetic field cannot realistically be generated at a distance. To counterfeit a field signature matching a distant location, an adversary would need to place ferromagnetic masses or electromagnets in the immediate vicinity of the device with the correct geometry—impractical for most attack scenarios. The field penetrates structures where GPS fails: indoors, underground, in urban canyons, and within Faraday‑shielded environments.

Technical Status

Working prototypes using unmodified smartphone sensors demonstrate horizontal positioning accuracy of 300–600 metres. Ongoing development integrates USGS magnetic anomaly reference data and enhanced probability weighting algorithms, targeting sub-10 metre accuracy in characterised corridors.

The approach is documented in U.S. Patent 12,306,291 B2, covering GPS-independent positioning methodology, spoofing detection architecture, and five industrial application domains including emergency response, logistics, autonomous systems, defence operations, and freight fraud prevention.

The system runs on smartphones, vehicles, drones, maritime platforms, wearables, and fixed infrastructure nodes—any platform capable of calibrated magnetic and inertial sensing.

Role in Layered PNT Architectures

Within a layered PNT architecture, ALIS functions as an independent trust and verification layer. It validates or challenges GNSS‑derived positions without assuming their correctness. It constrains inertial drift by re‑anchoring motion to external physical structure. It supports operation in GNSS‑denied or deceptive environments without reliance on transmissions. And it operates passively, reducing electromagnetic exposure and attack surface.

ALIS does not replace GPS. It provides a verification layer that operates on different physics. When GPS reports a position, ALIS can independently assess whether the geophysical measurements at that location are consistent with the claim. This creates a trust primitive that complements signal authentication and receiver-level integrity monitoring.

Information‑Bounded Confidence

ALIS is explicitly information‑bounded by physics. This is its defining trust property.

Crucially, ALIS treats the physical model and its uncertainty as first‑class inputs. Confidence is not inferred heuristically or learned opaquely; it is derived from the information content of the environment and the quality of the measurements. The system reports confidence only when the environment and measurements support a defensible conclusion. When they do not, ALIS reports "insufficient evidence" rather than asserting false precision.

Assurance and Governance

For mission‑critical use, ALIS should be governed as an assured trust capability—with defined operating envelopes, explicit confidence reporting, calibration discipline, and integration into architectures designed to fail differently.

Trust is not established by certainty claims, but by defensibility under challenge.

Conclusion

ALIS is a physics‑first trust layer for location. It complements GNSS and inertial navigation by providing an independent, non‑RF, auditable basis for accepting or rejecting location claims in contested environments. For critical infrastructure and defence applications where position integrity directly affects safety or mission success, geophysical verification addresses a threat category that current resilience architectures do not fully mitigate.