DAA Track Integrity Checks for False Association Detection
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Solution Overview
Problem
Existing DAA tracking systems for UAS face challenges in ensuring the integrity of estimated tracks formed through sensor associations, leading to potential mis-associations, false tracks, and incorrect guidance maneuvers due to sensor measurement errors and faults.
Innovation Solution
A system that integrates a track integrity module with solution separation techniques to ensure the integrity of tracks estimated by DAA tracking systems, using cooperative and non-cooperative sensors, by performing fault detection and exclusion, and employing discriminators and decision thresholds to validate the association of measurement tracks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple sensors are used to track air traffic, then the coverage and detection capability are improved, but the risk of mis-association and false tracks increases
Solution Approach 1:
The patent divides the track estimation into multiple independent components: main solution tracks and sub-solution tracks. Each sub-solution track represents a possible association hypothesis, and the system evaluates each separately before selecting the final track. This segmentation allows the system to maintain multiple sensor sources while controlling association errors through systematic evaluation of each hypothesis.
Solution Approach 2:
The patent implements an integrity evaluation feedback loop that continuously monitors track quality metrics and adjusts the association process. The system uses discriminators and decision thresholds to evaluate sub-solution tracks and feeds this information back to the data association module, allowing dynamic adjustment of association decisions based on real-time track integrity assessment.
2Area of stationary object
If sensor measurements are associated to form tracks, then the tracking coverage is improved, but the probability of false tracks and mis-associations increases
Solution Approach 1:
The patent generates more sub-solution tracks than the final number of tracks needed, creating a set of candidate associations that exceeds the minimum required. This excessive generation allows the system to then selectively filter and validate tracks using integrity discriminators, ensuring that only accurate tracks are selected while maintaining comprehensive coverage.
Solution Approach 2:
The patent introduces sub-solution tracks as intermediary structures between raw sensor measurements and final track solutions. These sub-solution tracks serve as intermediate hypotheses that can be evaluated and filtered, acting as a buffer that prevents direct mis-association of sensor measurements while maintaining the ability to derive accurate final tracks.
3Reliability
If track integrity checks are performed, then the reliability of tracks is improved, but the processing time and computational complexity increase
Solution Approach 1:
The patent performs integrity evaluations and discriminator calculations in advance during the track generation process itself, rather than as a separate post-processing step. By embedding integrity checks within the track formation procedure and pre-evaluating sub-solution tracks, the system reduces overall computational complexity while maintaining thorough integrity verification.
Data Source
AI summary
A system comprises a processor onboard a vehicle, surveillance sensors, and a DAA module that receives sensor measurement tracks and includes a tracking system that tracks objects in an environment around the vehicle. The tracking system comprises a data association module that includes a track-to-track function that outputs main solution and sub-solution tracks with track information. An integrity module communicates with the DAA module and comprises a track integrity system in communication with the data association module and operative to provide integrity checks. The track integrity system compares, selects, and outputs a main solution track or sub-solution tracks based on correlated tracks provided by the track-to-track function and solution separation; sends a track solution that passes integrity tests to a prune function, and sends tracks that fail to pass integrity tests to the data association module; and assures the integrity of tracks correlated and estimated by the tracking system.