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


Aslan M. S., SARANLI A., BAYKAL B.

DIGITAL SIGNAL PROCESSING, vol.20, no.5, pp.1468-1481, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 20 Issue: 5
  • Publication Date: 2010
  • Doi Number: 10.1016/j.dsp.2010.01.008
  • Journal Name: DIGITAL SIGNAL PROCESSING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1468-1481
  • Keywords: Non-simulation performance prediction, Modified Riccati equation, Detector threshold optimization, Neyman-Pearson detector, Track before detect, Probabilistic data association filter
  • Middle East Technical University Affiliated: Yes

Abstract

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. (C) 2010 Elsevier Inc. All rights reserved.