Track Integrity Checking for Multi-Sensor DAA Correlation
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Solution Overview
Problem
Existing DAA tracking systems for UAS face challenges in ensuring the integrity of tracks estimated by associating measurement data from multiple sensors, leading to potential mis-associations, false tracks, and incorrect guidance maneuvers.
Innovation Solution
A system that incorporates a track integrity module with solution separation techniques to ensure the integrity of tracks by detecting and excluding faulty sensor measurements, using a combination of cooperative and non-cooperative sensors to provide statistically optimal track estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If measurement tracks from multiple sensors are associated to form estimated tracks, then tracking capability is improved, but track integrity deteriorates due to potential mis-associations and false tracks
Solution Approach 1:
The patent segments the track formation process into multiple solution tracks (primary solution track and alternative solution tracks) by systematically excluding different sensor combinations. This segmentation allows the system to evaluate multiple possible track formations and select only those that pass integrity tests, thereby maintaining tracking capability while improving track integrity through selective acceptance of segmented track solutions.
Solution Approach 2:
The patent implements a feedback mechanism where integrity test results are fed back to the track selection process. The integrity module evaluates each solution track against predetermined criteria and provides feedback to the data association module, which then determines whether to accept or reject each track. This feedback loop ensures that only reliable tracks are used for guidance decisions, resolving the contradiction between tracking capability and track integrity.
2Measurement precision
If multiple sensors are used to track air traffic, then detection accuracy is improved, but false tracks and mis-associations increase
Solution Approach 1:
The patent converts the potentially harmful effect of multiple sensor measurements into a beneficial process by using solution separation techniques. Instead of directly combining all sensor measurements which creates false tracks, the system separates measurements into different solution tracks and uses integrity tests to identify and eliminate false tracks. This transforms the complexity of multi-sensor data into a structured approach that improves detection accuracy while minimizing false tracks.
Solution Approach 2:
The integrity module serves as an intermediary between the data association module and the guidance system. It receives multiple solution tracks from the data association process, evaluates their integrity using discriminators and decision thresholds, and selectively passes only reliable tracks to the guidance system. This intermediary function filters out false tracks and mis-associations while preserving accurate detections from multiple sensors.
3Area of stationary object
If track associations are formed through sensor data correlation, then tracking coverage is improved, but incorrect guidance maneuvers may result
Solution Approach 1:
The patent applies preliminary action by performing integrity tests on solution tracks before they are used for guidance decisions. The integrity module evaluates track quality criteria (such as spatial consistency, temporal continuity, and sensor reliability) in advance, and only tracks that pass these preliminary checks are accepted for guidance. This preliminary verification prevents incorrect guidance maneuvers while maintaining comprehensive tracking coverage through multiple sensors.
Data Source
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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.