TY - JOUR
T1 - Signal Parameter Estimation for Passive Bistatic Radar with Waveform Correlation Exploitation
AU - Wang, Fangzhou
AU - Li, Hongbin
AU - Zhang, Xin
AU - Himed, Braham
N1 - Publisher Copyright:
© 1965-2011 IEEE.
PY - 2018/6
Y1 - 2018/6
N2 - 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.
AB - 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.
KW - Autoregressive (AR) process
KW - clutter
KW - direct-path interference (DPI)
KW - passive bistatic radar
KW - signal parameter estimation
KW - waveform correlation exploitation
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U2 - 10.1109/TAES.2017.2775898
DO - 10.1109/TAES.2017.2775898
M3 - Article
AN - SCOPUS:85035758299
SN - 0018-9251
VL - 54
SP - 1135
EP - 1150
JO - IEEE Transactions on Aerospace and Electronic Systems
JF - IEEE Transactions on Aerospace and Electronic Systems
IS - 3
ER -