Sparsity-Based Direct Data Domain Space-Time Adaptive Processing with Intrinsic Clutter Motion
Sparsity-Based Direct Data Domain Space-Time Adaptive Processing with Intrinsic Clutter Motion
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DOI：
10.1007/s00034-016-0301-z
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发表时间：
2016-03
期刊：
影响因子：
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通讯作者：
Zhaocheng Yang;Yuliang Qin;R. D. Lamare;Hongqiang Wang;Xiang Li
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作者：
Zhaocheng Yang;Yuliang Qin;R. D. Lamare;Hongqiang Wang;Xiang Li
提出了一种考虑杂波固有运动的机载雷达直接数据域空时自适应处理（D3-STAP）算法。所提出的D3-STAP方案将存在ICM的接收到的返回建模为稀疏测量模型。然后，我们推导了基于稀疏性的D3-STAP的原理，它使用焦点欠定系统解（FOOLS）方法。提出的D3-STAP算法估计杂波协方差矩阵的Hadamard积的协方差矩阵锥度（CMT）和杂波协方差矩阵估计与FOOLS技术。此外，我们开发了一个CMT自适应方法，建议D3-STAP算法自动选择最佳CMT。仿真结果表明，该算法的性能优于现有的D3-STAP使用最小二乘技术和基于稀疏性的D3-STAP算法没有CMT。
In this paper, we propose a sparsity-based direct data domain space-time adaptive processing (D3-STAP) algorithm for airborne radar that considers the intrinsic clutter motion (ICM). The proposed D3-STAP scheme models the received returns in the presence of ICM as a sparse measurement model. Then, we derive the principle of the sparsity-based D3-STAP that uses the focal underdetermined system solution (FOCUSS) method. The proposed D3-STAP algorithm estimates the clutter covariance matrix by a Hadamard product of the covariance matrix taper (CMT) and the clutter covariance matrix estimate with the FOCUSS technique. In addition, we develop a CMT adaptation approach for the proposed D3-STAP algorithm to automatically select the best CMT. Simulation results show that the proposed algorithm outperforms the existing D3-STAP using the least-squares technique and the sparsity-based D3-STAP algorithm without CMT.