Tracker-aware adaptive detection: An efficient closed-form solution for the Neyman-Pearson case

2010-09-01
A promising line of research for radar systems attempts to optimize the detector thresholds so as to maximize the overall performance of a radar detector-tracker pair. In the present work, we attempt to move in a direction to fulfill this promise by considering a particular dynamic optimization scheme which relies on a non-simulation performance prediction (NSPP) methodology for the probabilistic data association filter (PDAF), namely, the modified Riccati equation (MRE). By using a suitable functional approximation, we propose a closed-form solution for the special case of a Neyman-Pearson (NP) detector. The proposed solution replaces previously proposed iterative solution formulations and results in dramatic improvement in computational complexity without sacrificed system performance. Moreover, it provides a theoretical lower bound on the detection signal-to-noise ratio (SNR) concerning when the whole tracking system should be switched to the track before detect (TBD) mode.

Citation Formats
M. S. Aslan, A. Saranlı, and B. Baykal, “Tracker-aware adaptive detection: An efficient closed-form solution for the Neyman-Pearson case,” DIGITAL SIGNAL PROCESSING, vol. 20, no. 5, pp. 1468–1481, 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40543.