Mechanism
A cooperative positioning mesh resolves member positions by combining governance-credentialed inter-agent range observations into a cooperative localization solution. The precision of the mesh-derived coordinates is bounded by ranging-modality accuracy and by reference-node density within ranging distance of the consuming agents. When no anchor observations are available, an anchor-less bootstrap mechanism produces a relative-only coordinate frame; admitted reference-node positions bind that frame to an external reference. A reference node is a mesh participant that contributes a governance-credentialed anchor position into the cooperative localization engine, with its position established at installation through a governance-policy-defined initial-coordinate method such as surveyed installation, relative installation using measured offsets from a known survey point, or consensus-calibrated installation.
Each reference node contributes its anchor position through the anchor observation admission interface, which admits governance-credentialed anchor position contributions into the cooperative localization engine. The engine determines agent positions through multilateration from admitted range observations and anchor positions, while a transitive localization extender produces agent positions through neighbor references when direct-anchor ranging is insufficient. A precision-and-uncertainty propagator propagates ranging precision and ranging-covariance through the localization chain, producing per-position uncertainty estimates, so that added reference nodes within ranging distance of a region reduce the uncertainty of positions in that region. An adversarial-range rejection mechanism rejects spoofed, injected, or otherwise inadmissible range observations, and an ambiguity-resolution mechanism selects among multiple solutions when multilateration admits more than one.
A densification-need detector identifies regions where precision falls below governance-policy-defined thresholds. A candidate-deployment evaluator then selects deployment locations and modalities appropriate to the detected need, and a deployment-admissibility evaluator evaluates each candidate deployment against governance policy before it is acted on. The deployment locations are chosen relative to existing reference-node coverage so that the added nodes fall within ranging distance of the regions whose precision must be improved.
Densification is the operational act of deploying reference nodes into an existing region. A deployment executor physically places, airdrops, hand-places, vehicle-deploys, or drone-positions the reference nodes. A post-densification integration engine integrates each deployed node through cooperative localization, so that neighbors begin including the node's anchor position in their localization and the precision improvement is distributed across the region within ranging distance. A densification-lineage recorder records each detection, deployment, and resulting precision improvement in the governance-chain lineage.
Operating Parameters
Densification is governance-policy-configurable per deployment. The densification-need detector operates on a precision-requirement signal: governance policy defines the precision thresholds below which a region is flagged, and the detector identifies regions falling below those thresholds. Deployment is parameterized by the densification form available in the deployment context and by the deployment intervals bounded by that form, which range from seconds for airdropped nodes and minutes for hand-placed and drone-positioned nodes to longer intervals for vehicle-deployed or survey-placed nodes.
Anchor position contributions are admitted through the anchor observation admission interface, which admits only governance-credentialed contributions. The deployment-admissibility evaluator evaluates each candidate deployment per the composite admissibility evaluation of the governed mesh before the node is integrated, and the adversarial-range rejection mechanism rejects spoofed, injected, or otherwise inadmissible range observations once the node is participating. Admission and rejection events are recorded in the governance-chain lineage.
Range observations from each participating node are subject to per-modality reliability weighting and to the composite admissibility evaluation, so that contributions are weighted by authority, sensing-modality reliability, and inter-source consistency rather than treated as uniformly trusted. The architecture supports a range of reference-node forms, from pre-placed permanent and deployable semi-permanent nodes intended to remain in place, to airdroppable expendable nodes introduced for surge precision. A self-healing topology maintainer updates the coordinate graph under agent failure, removal, or addition, and the densification-lineage recorder records each deployment and resulting precision change.
Alternative Embodiments
In a first alternative embodiment, mobile reference nodes on authority-credentialed platforms provide transient densification, contributing anchor positions during their presence in the operating region and withdrawing on departure. In a second embodiment, reference nodes take human-factor forms, including ingested or worn reference nodes. In a third embodiment, densification forms span pre-placed permanent reference nodes, deployable semi-permanent reference nodes, airdroppable expendable reference nodes, vehicle-deployable reference nodes, drone-positionable reference nodes, hand-placeable reference nodes, and any governance-policy-defined reference-node form, each integrating into the same mesh-derived coordinate system through cooperative localization.
A further embodiment supports adversarial-environment operation in which anchor authenticity must be governance-credentialed before admission; the anchor observation admission interface admits only governance-credentialed contributions, and the adversarial-range rejection mechanism rejects spoofed, injected, or otherwise inadmissible observations regardless of their geometric plausibility. Yet another embodiment combines mesh-derived positions with externally-sourced positions, such as satellite navigation, inertial dead-reckoning, or visual-inertial odometry, through the composite admissibility evaluation, with each external position admitted into a common coordinate frame. A coordinate-frame federation mechanism aligns two or more independent mesh-derived coordinate systems, and the coordinate-frame specifier defines the frame type, origin, orientation, scale, and temporal association of the coordinate system.
Composition
Reference node densification composes with the cooperative localization engine through the anchor observation admission interface: a deployed reference node's anchor position is admitted as one more governance-credentialed contribution into the engine that already processes inter-agent range observations and anchor positions. It composes with the governed mesh credentialing such that admitted anchor positions are governance-credentialed, and with the deployment-admissibility evaluation that gates candidate deployments in adversarial settings. The densification-need detector drives actuation: it identifies regions where precision falls below governance-policy-defined thresholds, the candidate-deployment evaluator selects locations and modalities to meet the need, and the precision-and-uncertainty propagator reports the resulting per-position uncertainty.
Composition with the precision-and-uncertainty propagator surfaces densification effects to consuming agents in the coordinate system itself: each consuming agent receives per-position uncertainty estimates that reflect current reference-node density, so the effect of an added or departed node is observable as a change in the uncertainty of the affected positions rather than through a separate central dashboard. The self-healing topology maintainer updates the coordinate graph as transient mobile reference nodes on authority-credentialed platforms arrive and depart, and the densification-lineage recorder preserves the record of each such change in the governance chain.
Composition with phased deployment is structural: a region may begin with low reference-node density and operate at the precision that density supports, then add reference nodes on demand as requirements grow, with each stage operational at the precision its current density supports rather than gating operations on a complete buildout. Because densification forms range from survey-placed nodes through hand-placed, drone-positioned, vehicle-deployed, and airdropped expendable nodes, the deployment interval is bounded by the form chosen for each stage, allowing rapid initial coverage to be established and later supplemented as sustained operations permit.
The disclosure of these densification mechanisms, including the densification-need detector, candidate-deployment evaluator, deployment-admissibility evaluator, deployment executor, post-densification integration engine, and densification-lineage recorder, is the subject of a priority claim under United States provisional application 64/049,409. The provisional discloses the on-demand densification mechanism together with the alternative reference-node forms and operational compositions described above.
Prior-Art Distinction
Prior differential-positioning and assisted-positioning systems operate on reference-station networks maintained by positioning-service operators, whereas the present primitive self-organizes through mesh agents without dependence on a positioning-service operator. Prior positioning systems also treat reference-node density as a deployment-time configuration, a region is provisioned at a chosen density and operates at the resulting precision. The disclosure instead provides on-demand densification, in which a densification-need detector flags regions below governance-policy-defined precision thresholds and additional reference nodes are deployed and integrated into the existing mesh-derived coordinate system through cooperative localization, with a self-healing topology maintainer updating the coordinate graph as nodes are added or removed.
Prior positioning systems using static identifiers, such as satellite pseudo-random-noise codes, beacon broadcast addresses, or fixed-identifier access points, are vulnerable to identifier spoofing, whereas the present primitive authenticates each range observation through the governance-chain continuity identity and admissibility evaluation, weighting contributions by authority, sensing-modality reliability, and inter-source consistency. Each detection, deployment, and resulting precision improvement is recorded by the densification-lineage recorder in the governance chain, permitting deterministic reconstruction of how a region's precision was changed, which prior fixed-anchor architectures do not provide.
Disclosure Scope
The disclosure encompasses on-demand reference node densification in cooperative positioning meshes through a densification-need detector, candidate-deployment evaluator, deployment-admissibility evaluator, deployment executor, post-densification integration engine, and densification-lineage recorder, together with the governance-policy-configurable parameters described above. It encompasses the alternative reference-node forms, including pre-placed permanent, deployable semi-permanent, airdroppable expendable, vehicle-deployable, drone-positionable, hand-placeable, mobile reference nodes on authority-credentialed platforms, ingested or worn reference nodes in human-factor applications, and any governance-policy-defined reference-node form. It encompasses composition with the cooperative localization engine, governance credentialing and admissibility evaluation, and phased deployment. It applies across two-dimensional, three-dimensional, and time-extended cooperative solutions and to any mesh architecture admitting governance-credentialed anchor position contributions.
This article concerns subject matter disclosed in U.S. Provisional Application No. 64/049,409.
