Sense-and-Avoid Track Initialization for UAS Sensor Fusion
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Solution Overview
Problem
Current unmanned aircraft systems (UAS) lack a certified sense-and-avoid (SAA) capability, essential for safe operation in National Air Space, as they cannot detect and track intruder aircraft, hindering self-separation and collision avoidance maneuvers.
Innovation Solution
A method to initialize tracks from sensor measurements using a 3/3 measurement-to-measurement data association algorithm, which identifies tentative tracks, computes state vector statistics, and confirms or deletes tracks using gates, enabling effective detection and tracking of intruder aircraft.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional track initialization methods are used, then tracks can be established from sensor measurements, but false track initialization increases and computational burden increases
Solution Approach 1:
The patent applies preliminary action by requiring measurements from multiple sensors (at least three) to be collected and associated before track initialization occurs. The system pre-associates measurements from different sensors with potential tracks before confirmation, which reduces false initializations by ensuring multiple independent observations support each track. This preliminary measurement association filtering reduces the computational burden during actual track confirmation by eliminating unlikely tracks early in the process.
2Reliability
If multiple sensors are used for track initialization, then detection reliability improves, but processing time increases
Solution Approach 1:
The patent applies segmentation by dividing the track initialization process into distinct stages: measurement collection from multiple sensors, measurement association with tentative tracks, and track confirmation. By segmenting the processing into these phases, the system can efficiently handle sensor data in organized batches rather than processing all sensor inputs simultaneously, reducing overall processing time while maintaining detection reliability through multi-sensor validation.
3Reliability
If conservative track confirmation criteria are used, then false tracks are reduced, but legitimate tracks may be deleted
Solution Approach 1:
The patent applies feedback by implementing a track confirmation process where measurements from multiple sensors are continuously evaluated against established criteria. When measurements consistently support a tentative track across multiple sensor observations, the track is confirmed. This feedback loop allows the system to adjust track status based on accumulating evidence, reducing false tracks while preserving legitimate ones that meet the confirmation thresholds through repeated validation.
Data Source
AI summary
A method to initialize tracks from sensor measurements is provided. The method includes identifying at least one tentative track based on data collected from at least one sensor at three sequential times; initializing a confirm/delete track filter for the identified tentative tracks; and using gates computed from state vector statistics to one of: confirm the at least one tentative track; reprocess the at least one tentative track; or delete the at least one tentative track.