A Novel Clutter Covariance Matrix Estimation Method Based on Feature Subspace for Space-Based Early Warning Radar
| Autor: | Yongliang Wang, Zhihao Wang, Ning Qiao, Shuangxi Zhang, Mengdao Xing, Tianfu Zhang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
spatial-temporal adaptive processing (STAP)
Atmospheric Science Early-warning radar business.industry Computer science Covariance matrix QC801-809 Geophysics. Cosmic physics Sample (statistics) Pattern recognition Covariance matrix estimation Space (mathematics) heterogeneous environment Signal Ocean engineering training sample Feature (computer vision) space-based early warning radar (SBEWR) Clutter Artificial intelligence Computers in Earth Sciences business TC1501-1800 Subspace topology |
| Zdroj: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 11217-11228 (2021) |
| ISSN: | 2151-1535 |
| Popis: | Accurate estimation of the clutter covariance matrix for the cell under test (CUT) is a committed step in the spatial-temporal adaptive processing (STAP) algorithm. The unique nonstationary characteristic of signal for space-based early warning radar (SBEWR) leads to the spatial variation of training sample and the insufficient number of optional independent identically distributed (i.i.d.) training samples, which brings difficulties to training sample selection and covariance matrix estimation. To improve the estimation accuracy of clutter covariance matrix and the performance of STAP for SBEWR in a heterogeneous environment, a novel training sample selection and clutter covariance matrix estimation method is proposed. The method based on clutter subspace reconstruction and spectrum correction technology can improve the estimation accuracy of clutter covariance matrix in the case of nonstationary signals and heterogeneous environments. The clutter covariance matrix estimated by the proposed method is similar to the clutter covariance matrix of the CUT, and the performance of STAP is improved. The experimental results confirm the performance of the proposed method. |
| Databáze: | OpenAIRE |
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