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利用扩展阵列流形向量的共置 MIMO 雷达到达角估计新方法。

A Novel Approach for Direction of Arrival Estimation in Co-Located MIMO Radars by Exploiting Extended Array Manifold Vectors.

机构信息

Department of Mechanical Engineering, Chulalongkorn University, Bangkok 10330, Thailand.

School of Information Science and Technology, University of Science and Technology of China (USTC), Hefei 230026, China.

出版信息

Sensors (Basel). 2023 Feb 24;23(5):2550. doi: 10.3390/s23052550.

Abstract

Multiple-input multiple-output (MIMO) radars enable better estimation accuracy with improved resolution in contrast to traditional radar systems; thus, this field has attracted attention in recent years from researchers, funding agencies, and practitioners. The objective of this work is to estimate the direction of arrival of targets for co-located MIMO radars by proposing a novel approach called flower pollination. This approach is simple in concept, easy to implement and has the capability of solving complex optimization problems. The received data from the far field located targets are initially passed through the matched filter to enhance the signal-to-noise ratio, and then the fitness function is optimized by incorporating the concept of virtual or extended array manifold vectors of the system. The proposed approach outperforms other algorithms mentioned in the literature by utilizing statistical tools for fitness, root mean square error, cumulative distribution function, histograms, and box plots.

摘要

多输入多输出(MIMO)雷达相对于传统雷达系统能够提高分辨率并实现更好的估计精度,因此近年来受到了研究人员、资助机构和从业者的关注。本工作的目的是通过提出一种称为花授粉的新方法来估计共位 MIMO 雷达目标的到达方向。该方法概念简单,易于实现,并且能够解决复杂的优化问题。远场目标的接收数据首先通过匹配滤波器进行处理,以提高信噪比,然后通过结合系统的虚拟或扩展阵列流形向量的概念来优化适应度函数。所提出的方法通过利用适应度、均方根误差、累积分布函数、直方图和箱线图的统计工具,优于文献中提到的其他算法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4bb/10007184/a8c68b44d8b5/sensors-23-02550-g001.jpg

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