基于稀疏加权重构的互耦阵列方位估计算法
发布时间：2018-12-17 21:03
【摘要】：为降低阵元互耦对目标方位估计的影响,提高估计精确度,提出了一种基于稀疏信号加权重构的多目标方位估计算法。该算法将空间以1°为间隔,划分为网格。利用空域目标方位的稀疏性,给出了基于Capon谱函数的加权值选取方法。然后,运用稀疏重构方法和奇异值分解方法对信号进行降维处理。最后,通过L1范数约束优化模型进行DOA估计。仿真结果表明,相比于传统算法,所提出的算法具有更高的方位估计精度、更低的均方根误差,能更好地抑制阵元互耦对目标方位估计的影响。
[Abstract]:In order to reduce the influence of mutual coupling of array elements on target azimuth estimation and improve the accuracy of estimation, a multi-objective azimuth estimation algorithm based on sparse signal weighted reconstruction is proposed. In this algorithm, the space is divided into meshes at an interval of 1 掳. In this paper, the method of selecting weighted values based on Capon spectral function is presented by using the spatial target azimuth sparsity. Then, the sparse reconstruction method and singular value decomposition method are used to reduce the dimension of the signal. Finally, DOA estimation is carried out by L1 norm constrained optimization model. The simulation results show that the proposed algorithm has higher azimuth estimation accuracy and lower root mean square error than the traditional algorithm, and it can better suppress the influence of array element coupling on the target azimuth estimation.
【作者单位】： 北京理工大学信息与电子学院;
【分类号】：TN911.7
[Abstract]:In order to reduce the influence of mutual coupling of array elements on target azimuth estimation and improve the accuracy of estimation, a multi-objective azimuth estimation algorithm based on sparse signal weighted reconstruction is proposed. In this algorithm, the space is divided into meshes at an interval of 1 掳. In this paper, the method of selecting weighted values based on Capon spectral function is presented by using the spatial target azimuth sparsity. Then, the sparse reconstruction method and singular value decomposition method are used to reduce the dimension of the signal. Finally, DOA estimation is carried out by L1 norm constrained optimization model. The simulation results show that the proposed algorithm has higher azimuth estimation accuracy and lower root mean square error than the traditional algorithm, and it can better suppress the influence of array element coupling on the target azimuth estimation.
【作者单位】： 北京理工大学信息与电子学院;
【分类号】：TN911.7
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