Signal Parameter Estimation for Passive Bistatic Radar with Waveform Correlation Exploitation

Fangzhou Wang, Hongbin Li, Xin Zhang, Braham Himed

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

This paper addresses the problem of target delay and Doppler frequency estimation for passive bistatic radar employing noncooperative illuminators of opportunity (IOs), where the receivers are contaminated by nonnegligible noise, clutter, and direct-path interference. A parametric approach is proposed by modeling the unknown signal transmitted from the IO as an autoregressive process whose temporal correlation is jointly estimated and exploited for passive estimation. An iterative estimator based on the expectation-maximization (EM) principle is utilized to solve this highly nonlinear problem. We also discuss the initialization of the EM-based estimator and a fast implementation based on the fast Fourier transform and interpolation techniques. In addition, we derive the Cramér-Rao lower bound for the estimation problem to benchmark the performance of the proposed estimator. Simulation results show that the proposed estimator behaves similarly to a clairvoyant EM estimator, which assumes knowledge of the IO waveform covariance matrix, and significantly outperforms other methods that ignore the waveform correlation.

Original languageEnglish
Pages (from-to)1135-1150
Number of pages16
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume54
Issue number3
DOIs
StatePublished - Jun 2018

Keywords

  • Autoregressive (AR) process
  • clutter
  • direct-path interference (DPI)
  • passive bistatic radar
  • signal parameter estimation
  • waveform correlation exploitation

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