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A New Multiple Hypothesis Tracker Integrated with Detection Processing.

Ziwei Wang¹, Jinping Sun¹, Qing Li²

¹School of Electronics & Information Engineering, Beihang University, Beijing 100191, China.

Sensors (Basel, Switzerland)

|December 6, 2019

Summary

This summary is machine-generated.

This study introduces an integrated radar detection and tracking method. The novel approach improves tracking accuracy, especially in challenging environments with dense clutter and closely spaced targets.

Keywords:

multiple hypothesis tracker, adaptive detection threshold, score function, sequential probability ratio test

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Area of Science:

Radar Signal Processing
Target Tracking Systems

Background:

Current radar systems perform detection and tracking independently, leading to performance degradation with false alarms and missed targets.
Tracking accuracy is heavily reliant on detection accuracy, particularly in dense clutter or scenarios with closely spaced targets.

Purpose of the Study:

To propose a novel method integrating multiple hypothesis tracking (MHT) with detection processing for enhanced radar performance.
To improve radar tracking accuracy in challenging environments by adaptively adjusting detection thresholds.

Main Methods:

Developed a novel method integrating the multiple hypothesis tracker (MHT) with detection processing.
Detector acquires an adaptive detection threshold from MHT algorithm output.
Utilized the adaptive threshold for data association and track estimation tasks, including score function and sequential probability ratio test (SPRT) threshold computation.

Main Results:

Comparative analysis conducted in a dense clutter scenario.
The proposed integrated MHT and detection processing method demonstrated superior tracking accuracy.
Outperformed standard MHT and Global Nearest Neighbor (GNN) algorithms in simulation.

Conclusions:

The integrated MHT and detection processing method offers significant improvements in radar tracking accuracy.
This approach effectively mitigates performance degradation caused by false alarms and missed detections.
The adaptive thresholding strategy is key to enhancing tracking performance in complex scenarios.