TY - JOUR
T1 - Joint delay and Doppler estimation for passive sensing with direct-path interference
AU - Zhang, Xin
AU - Li, Hongbin
AU - Liu, Jun
AU - Himed, Braham
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/2/1
Y1 - 2016/2/1
N2 - We consider the problem of joint delay-Doppler estimation of a moving target in a passive radar that employs a non-cooperative illuminator of opportunity (IO) for target illumination, a reference channel (RC) steered to the IO to obtain a reference signal, and a surveillance channel (SC) for target monitoring. We consider a practically motivated scenario, where the RC receives a noise-contaminated copy of the IO signal and the SC observation is polluted by a direct-path interference that is usually neglected by prior studies. We develop a data model without discretizing the parameter space, which may lead to a straddle loss, by treating both the delay and Doppler as continuous parameters. We propose an expectation-maximization based estimator, as well as a modified cross-correlation (MCC) estimator that is a computationally simpler solution resulting from an approximation of the former. In addition, we derive the Cramér-Rao lower bound for the estimation problem. Simulation results are presented to illustrate the performance of the proposed estimators and the widely used CC estimator.
AB - We consider the problem of joint delay-Doppler estimation of a moving target in a passive radar that employs a non-cooperative illuminator of opportunity (IO) for target illumination, a reference channel (RC) steered to the IO to obtain a reference signal, and a surveillance channel (SC) for target monitoring. We consider a practically motivated scenario, where the RC receives a noise-contaminated copy of the IO signal and the SC observation is polluted by a direct-path interference that is usually neglected by prior studies. We develop a data model without discretizing the parameter space, which may lead to a straddle loss, by treating both the delay and Doppler as continuous parameters. We propose an expectation-maximization based estimator, as well as a modified cross-correlation (MCC) estimator that is a computationally simpler solution resulting from an approximation of the former. In addition, we derive the Cramér-Rao lower bound for the estimation problem. Simulation results are presented to illustrate the performance of the proposed estimators and the widely used CC estimator.
KW - Direct-path interference
KW - Joint delay-Doppler estimation
KW - Noisy reference
KW - Passive sensing
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U2 - 10.1109/TSP.2015.2488584
DO - 10.1109/TSP.2015.2488584
M3 - Article
AN - SCOPUS:84988447918
SN - 1053-587X
VL - 64
SP - 630
EP - 640
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 3
M1 - A630
ER -