1. Sea Clutter Covariance Matrix Estimation and Its Application to Whitening Filter
- Author
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Ji-Min Song, Hyeonmu Jeon, Yong-Seek Chung, Hoon-Gee Yang, Sang-Hyun Choi, and Jongmann Kim
- Subjects
QC501-766 ,020301 aerospace & aeronautics ,Radiation ,Computer Networks and Communications ,Covariance matrix ,Computer science ,020208 electrical & electronic engineering ,doppler frequency ,02 engineering and technology ,covariance matrix estimation ,clutter suppression ,whitening filter ,TK1-9971 ,Electricity and magnetism ,0203 mechanical engineering ,Whitening filter ,Doppler frequency ,0202 electrical engineering, electronic engineering, information engineering ,Clutter ,Electrical engineering. Electronics. Nuclear engineering ,Electrical and Electronic Engineering ,Instrumentation ,Algorithm - Abstract
The accurate estimation of clutter covariance matrix (CCM) is essential in designing a radar detector/filter to suppress sea clutter. This estimation might not be easily accomplished because of the scarcity of valid training vectors adjacent to the range cell under test (CUT). We propose a new CCM estimation algorithm that is derived by modeling time-series clutter returns into a clutter Doppler spectrum in the frequency domain and exploiting mutual independence among spectral components. To justify its excellence over the conventional sample covariance matrix (SCM) algorithm, we design two filters—a maximum signal-to-interference-plus-noise ratio (SINR)-based filter and a whitening filter—that use the estimated CCMs and compare their performance in a numerically simulated sea clutter scenario. Comparisons are made by showing the eigenvector spectra of the estimated CCMs and the frequency responses and outputs of the filters. Moreover, SINRs at the target Doppler bin are examined and compared with a theoretical, analytically derived SINR.
- Published
- 2021
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