摘要
针对采样数据少的情况下近场最小方差无畸变(MVDR)算法定位性能差的问题,提出一种基于矢量对角加载的近场MVDR定位方法。首先推导了基于任意型矢量阵的近场MVDR算法,并分析了算法在快拍数较少时性能下降原因;矢量对角加载方法利用采样数据协方差矩阵的标准差作为加载量完成对角加载处理,获得改善的协方差矩阵;最后通过仿真和实验数据验证改进算法的有效性和稳定性。验证结果表明,提出的方法能克服小快拍数据的影响,提高水雷对近场区域目标的定位稳定性。
The performance of standard near MVDR(Minimum Variance Distortionless Response) algorithm would be decreased sharply when the sampled data is small. This paper proposed a near MVDR localization method based on vector diagonal loading. Firstly, the near MVDR algorithm based on arbitrary vector array was derived detailedly and the reasons for the performance degradation of the algorithm were analyzed when the snapshots number was small. Vector diagonal loading method used the standard deviation of sampling data covariance matrix as loading amount to complete diagonal loading processing and an improved covariance matrix was proposed. Finally, the effectiveness and robustness of the proposed algorithm was verified by simulation and experiment data. Simulation results revealed that the proposed algorithm could overcome the influence of small snapshots and improved the stability of near-field target location.
引文
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