Collaborative Geolocation via Dynamic Tracking Filter Adaptation
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Solution Overview
Problem
Existing geolocation methods in heterogeneous networks with mobile nodes of varying mobility types and dynamic state changes are sub-optimal, especially in 3D navigation scenarios and during GPS signal degradation, as they fail to adapt to changing mobility states and assume static models.
Innovation Solution
A method and system that dynamically selects appropriate tracking filters based on node mobility changes, using quasi-static nodes as anchors for 2D geolocation and subsequently estimating altitude, allowing continuous geolocation across different mobility types, including ground and air vehicles, even in the absence of GPS signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static tracking filters are used for geolocation, then the system is simpler to implement, but it cannot adapt to dynamic changes in node mobility types
Solution Approach 1:
The patent implements dynamic adaptability by enabling tracking filters to automatically adjust their parameters and models based on real-time detection of mobility type changes. Each node monitors its own mobility characteristics and dynamically selects appropriate tracking filter configurations (e.g., switching between static, slow-moving, or fast-moving node models), allowing the system to adapt to changing mobility conditions without manual intervention or system reconfiguration.
2Measurement precision
If 3D geolocation is implemented for all nodes, then complete spatial positioning is achieved, but observability is lost when nodes are concentrated in the same plane
Solution Approach 1:
The patent applies local quality by adapting the geolocation dimensionality to the specific spatial distribution characteristics of nodes. When nodes are detected to be concentrated in a planar configuration, the system automatically switches to 2D geolocation processing for those nodes, while maintaining 3D capabilities for nodes with sufficient vertical separation. This localized adaptation of processing dimensionality optimizes both accuracy and observability based on the actual geometric configuration of the node network.
3Reliability
If GPS signal is relied upon for geolocation, then global positioning is available, but service continuity is lost during GPS signal degradation or denial
Solution Approach 1:
The patent introduces intermediary elements in the form of collaborative node networks that mediate geolocation when GPS is unavailable. When GPS signal degradation or denial is detected, the system transitions to using telemetry measurements and collaborative tracking between network nodes as intermediaries to maintain geolocation services. These node-based intermediaries provide alternative positioning references that do not depend on satellite signals, ensuring service continuity during GPS outages.
Solution Approach 2:
The patent implements beforehand cushioning by pre-establishing collaborative tracking capabilities and alternative geolocation methods during normal GPS operation. The system continuously maintains node position information and tracking filter models that can immediately take over when GPS fails, providing a cushion against service disruption. This preparatory establishment of alternative positioning infrastructure ensures seamless transition during GPS signal loss without service interruption.
4Adaptability or versatility
If predefined covariances are assigned to fixed anchors, then the system can handle heterogeneous mobility types, but the tracking filter becomes inappropriate when mobility changes occur
Solution Approach 1:
The patent resolves this contradiction by making tracking filter parameters dynamic rather than static. Instead of assigning fixed covariances to anchors, the system continuously updates tracking filter models based on real-time mobility type detection. When a node's mobility characteristics change (e.g., from stationary to moving, or changing speed patterns), the tracking filter automatically adjusts its covariance matrices and process models to match the new mobility regime, maintaining both heterogeneity support and tracking accuracy simultaneously.
Data Source
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AI summary
Collaborative radiolocation network and method comprising at least three nodes communicating with each other by radio means characterized in that each of said nodes is equipped with a module for controlling the mobility state of said node, a communication module adapted to transmit information relating to its mobility state to the other nodes of the network, a processor adapted to choose a tracking filter IMM adapted to determine the position of said node Mi in order to allow said node to geolocate itself as well as to geolocate the other nodes of the network.