Abstract
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 Cramer-Rao bound, the best performance bound an unbiased estimator can achieve. Numerical results are also provided to demonstrate the performance of the proposed algorithm.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
