TY - JOUR
T1 - Moving target feature extraction with polarisation diversity in the presence of arbitrary range migration and phase errors
AU - Liu, G.
AU - Li, H.
AU - Li, J.
PY - 2000/8
Y1 - 2000/8
N2 - High range resolution (HRR) moving target indication (MTI) is increasingly important in many military and civilian applications such as the detection and classification of moving targets in strong clutter backgrounds. Meanwhile using polarisation diversity in radar systems has been shown to result in improved performance as compared with using only a single polarisation channel. The authors extract HRR moving target features with polarisation diversity in the presence of strong stationary clutter. The problem considered takes into account arbitrary range migration and phase errors, which may be induced by unknown target and platform motions as well as atmosphere turbulence and/or system instability. A relaxation-based algorithm is presented for the joint clutter suppression and super resolution target feature extraction and its performance is compared to the Cramér-Rao bound, the best performance bound an unbiased estimator can achieve. Numerical results are also provided to demonstrate the performance of the proposed algorithm.
AB - High range resolution (HRR) moving target indication (MTI) is increasingly important in many military and civilian applications such as the detection and classification of moving targets in strong clutter backgrounds. Meanwhile using polarisation diversity in radar systems has been shown to result in improved performance as compared with using only a single polarisation channel. The authors extract HRR moving target features with polarisation diversity in the presence of strong stationary clutter. The problem considered takes into account arbitrary range migration and phase errors, which may be induced by unknown target and platform motions as well as atmosphere turbulence and/or system instability. A relaxation-based algorithm is presented for the joint clutter suppression and super resolution target feature extraction and its performance is compared to the Cramér-Rao bound, the best performance bound an unbiased estimator can achieve. Numerical results are also provided to demonstrate the performance of the proposed algorithm.
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U2 - 10.1049/ip-rsn:20000464
DO - 10.1049/ip-rsn:20000464
M3 - Article
AN - SCOPUS:85047675504
SN - 1350-2395
VL - 147
SP - 208
EP - 216
JO - IEE Proceedings: Radar, Sonar and Navigation
JF - IEE Proceedings: Radar, Sonar and Navigation
IS - 4
ER -