Moving target feature extraction for airborne high-range resolution phased-array radar
Moving target feature extraction for airborne high-range resolution phased-array radar
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DOI：
10.1109/78.902110
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发表时间：
2001-02
期刊：
影响因子：
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通讯作者：
Jian Li;Guoqing Liu;N. Jiang;P. Stoica
中科院分区：
文献类型：
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作者：
Jian Li;Guoqing Liu;N. Jiang;P. Stoica
研究机载高距离分辨率（HRR）相控阵雷达在时间和空间相关地杂波情况下运动目标的特征提取问题。为了避免HRR雷达数据中出现的距离徙动问题，我们首先将HRR距离像分成低距离分辨率（LRR）段。由于每个LRR段包含HRR距离仓的序列，因此没有信息由于划分而丢失，因此没有分辨率的损失发生。首先介绍了如何利用向量自回归（VAR）滤波技术抑制地杂波，然后提出了一种参数估计算法用于目标特征提取。从VAR滤波的数据，目标多普勒频率和空间特征向量的估计，首先通过使用最大似然（ML）方法。然后通过最小化加权最小二乘（WLS）代价函数从空间特征向量估计目标相位历史和到达方向（DOA）（或未知阵列流形的阵列导向向量）。然后利用基于松弛的高分辨率特征提取算法RELAX从估计的目标相位历史中提取目标散射体的雷达散射截面（RCS）相关复振幅和距离相关频率。数值结果证明了所提出的算法的性能。
We study the feature extraction of moving targets in the presence of temporally and spatially correlated ground clutter for airborne high-range resolution (HRR) phased-array radar. To avoid the range migration problems that occur in HRR radar data, we first divide the HRR range profiles into low-range resolution (LRR) segments. Since each LRR segment contains a sequence of HRR range bins, no information is lost due to the division, and hence, no loss of resolution occurs. We show how to use a vector auto-regressive (VAR) filtering technique to suppress the ground clutter, Then, a parameter estimation algorithm is proposed for target feature extraction. From the VAR-filtered data, the target Doppler frequency and the spatial signature vectors are first estimated by using a maximum likelihood (ML) method. The target phase history and direction-of-arrival (DOA) (or the array steering vector for an unknown array manifold) are then estimated from the spatial signature vectors by minimizing a weighted least squares (WLS) cost function. The target radar cross section (RCS)-related complex amplitude and range-related frequency of each target scatterer are then extracted from the estimated target phase history by using RELAX, which is a relaxation-based high-resolution feature extraction algorithm. Numerical results are provided to demonstrate the performance of the proposed algorithm.