Space–time adaptive processing (STAP) algorithm plays a crucial role in clutter suppression for space-based radar (SBR) systems, while its performance is affected directly by the estimation accuracy of the clutter covariance matrix (CCM). However, due to the higher orbital altitudes and the Earth's rotation, the clutter of the SBR exhibits nonstationary characteristics, posing a formidable obstacle to the precise estimation of the CCM, thereby substantially increasing the complexity and challenges associated with clutter suppression. This article introduces a clutter suppression algorithm rooted in the design of a radar transmitting pulse structure, with the objective of improving the estimation accuracy of the CCM. Furthermore, this algorithm enhances the performance of the STAP algorithm while simultaneously minimizing computational complexity and hardware costs. The proposed algorithm incorporates a two-stage processing procedure. In the first stage, the near-range nonstationary clutter is extracted utilizing the orthogonal coded pulses, ensuring its purity by being devoid of ambiguity components. Subsequently, the construction of a near-range clutter subspace is facilitated after extraction, which is isolated from the contamination of far-range clutter and cross-terms, thereby enhancing the accuracy of the CCM. Following this, the orthogonal projection algorithm is employed in conjunction with the time-domain sliding window method to effectively suppress near-range nonstationary clutter. The second stage of the processing involves the application of a cascaded two-dimensional STAP algorithm to suppress the far-range stationary clutter. Simulation results under two types of clutter backgrounds demonstrate the effectiveness and robustness of the proposed algorithm.


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    Title :

    A Clutter Suppression Algorithm for Space-Based Radar Based on Orthogonal Coded Pulses


    Contributors:
    Wu, Jiaye (author) / Zhang, Shuangxi (author) / Liu, Weijian (author) / Zhang, Zhaojian (author) / Chen, Wei (author) / Wang, Yong-Liang (author)


    Publication date :

    2025-06-01


    Size :

    5178965 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






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