Fully Adaptive Radar for Multiple Target Tracking

This work focuses on the development of a fully adaptive radar multiple target tracking (FAR-MTT) model and demonstrates its benefit over static parameter selections. The FAR-MTT framework is an extension of the fully adaptive radar (FAR) framework for single-target tracking (STT). In transitioning FAR-STT concepts to FAR-MTT, the focus was on developing a multiple target Fisher information matrix to capture the effects of multiple targets on the radar measurements, and on developing a robust but straightforward optimization scheme/objective function in the FAR executive processor. Simulation and experimental examples are presented to demonstrate the performance of the FAR-MTT approach. Compared to the fixed parameter case, the FAR-MTT technique is capable of obtaining specified tracking performance for each target and ensuring target separation while reducing sensor resource usage in a variety of multiple target environments. In Monte Carlo testing the method resulted in track merges 28% of the time compared with 50% of the time for a static parameter approach.

Automated summary

This work introduces a fully adaptive radar multiple target tracking (FAR-MTT) model, which outperforms static parameter selections. By developing a multiple target Fisher information matrix and an optimization scheme, the model achieves accurate tracking of each target and reduces resource usage in multiple target environments.