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

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

DIGITAL SIGNAL PROCESSING, cilt.20, sa.5, ss.1468-1481, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 20 Sayı: 5
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1016/j.dsp.2010.01.008
  • Dergi Adı: DIGITAL SIGNAL PROCESSING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1468-1481
  • Anahtar Kelimeler: Non-simulation performance prediction, Modified Riccati equation, Detector threshold optimization, Neyman-Pearson detector, Track before detect, Probabilistic data association filter
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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.