Adaptive Rao Detection of Radar Targets Based on the Priori-Knowledge of Sea Clutter
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摘要: 针对非高斯非均匀海杂波背景下雷达海面目标检测性能改善的问题，该文基于海杂波的先验知识提出了一种自适应Rao雷达目标检测方法。首先将海杂波的纹理分量和散斑协方差矩阵分别建模为逆高斯随机变量和逆复Wishart分布的随机矩阵，然后基于Rao检验和未知参数估计，设计了一种匹配海杂波特性的雷达目标自适应Rao检测方法。通过理论推导和实验验证了所提检测方法对杂波平均功率和协方差均值矩阵具有恒虚警特性。仿真数据和实测数据实验结果表明，在非高斯非均匀环境下所提检测方法优于已有检测方法，并且具有良好的鲁棒性。Abstract: An adaptive Rao detection method for radar targets is proposed based on the priori knowledge of sea clutter to improve the radar’s target detection performance in non-Gaussian and nonhomogeneous sea clutter. First, the texture component and the speckle covariance matrix of sea clutter are modeled as an inverse Gaussian random variable and an inverse complex Wishart random matrix, respectively. Then, an adaptive Rao detection method for radar targets, with quite similar characteristics as sea clutter, is designed based on the Rao test and unknown parameter estimation. The detection method is verified by theoretical derivation and experiments in demonstrating constant false alarm characteristics for the mean power and covariance mean matrix of sea clutter. The experimental results of the simulated and experimental data reveal that the proposed detection method outperforms existing detection methods in non-Gaussian and nonhomogeneous sea clutter environments with good robustness.
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Key words:
- Radar targets /
- Adaptive Rao detection /
- Sea clutter /
- Priori knowledge
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