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Fast inverse covariance matrix computation based on element-order recursive method for space-time adaptive processing

基于阵元阶数递推的快速协方差矩阵求逆STAP算法

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Abstract

Because of large computational complexity in the inverse space-time covariance matrix computation, the conventional space-time adaptive processing (STAP) is unsuitable for practical implementation. According to the block Hermitian matrix property of covariance matrix, a new element-order recursive method is proposed in this paper to calculate the inverse space-time covariance matrix for STAP weight vector. In the proposed method, the inverse space-time covariance matrix of first element-order is initially calculated recursively based on block Hermitian matrix property, and then the inverse space-time covariance matrix of high element-order is correspondingly deduced recursively based on obtained inverse covariance matrix of previous element-order. Finally, STAP weight vector is calculated based on the final inverse covariance matrix. Afterwards, a modified reduced-dimension STAP method is derived by combining the proposed method with the m-Doppler Transformation (mDT-SAP) STAP approach. Based on the simulated and the actual airborne phased array radar data, the proposed method verified that the computational complexity is much smaller than conventional STAP methods. The proposed element-order recursive method for STAP is applicable for practical airborne phased radar system.

摘要

主要创新点

由于空时协方差矩阵求逆存在巨大的运算复杂度, 传统空时自适应处理(STAP)技术难以满足目前技术水平下系统实时性的要求。 本文根据空时协方差矩阵为Hermitian矩阵, 能利用阵元分块递推的特性, 提出基于阵元阶数递推计算空时协方差矩阵逆的STAP算法。 本方法首先根据分块Hermitian矩阵性质, 递推得到第1个阵元的协方差逆矩阵, 然后按照阵元阶数逐级递推得到最终的空时协方差逆矩阵, 进而得到STAP自适应权值。 同时, 本方法还可以有效地与m多普勒邻域(mDT-SAP)等降维STAP算法结合使用。 仿真与实测数据处理结果表明, 本方法在极大降低计算复杂度的同时, 能够获得和直接协方差矩阵求逆STAP算法同样的杂波抑制性能。

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Authors and Affiliations

  1. School of Information and Electronic, Beijing Institute of Technology, Beijing, 100081, China

    XiaoPeng Yang, YuZe Sun, Tao Zeng & Teng Long

  2. Southwest China Research Institute of Electronic Equipment, Chengdu, 610036, China

    YongXu Liu

Authors
  1. XiaoPeng Yang
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  2. YuZe Sun
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  3. YongXu Liu
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  4. Tao Zeng
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  5. Teng Long
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Correspondence to XiaoPeng Yang.

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Yang, X., Sun, Y., Liu, Y. et al. Fast inverse covariance matrix computation based on element-order recursive method for space-time adaptive processing. Sci. China Inf. Sci. 58, 1–14 (2015). https://doi.org/10.1007/s11432-014-5250-1

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  • DOI: https://doi.org/10.1007/s11432-014-5250-1

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