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基于频域协方差矩阵重构的卫星干扰源到达方向（DOA）估计

Satellite Interference Source Direction of Arrival (DOA) Estimation Based on Frequency Domain Covariance Matrix Reconstruction.

作者信息

Yao Jinjie, Zhao Changchun, Bai Jiansheng, Ren Yang, Wang Yangyang, Miao Jing

机构信息

Shanxi Key Laboratory of Signal Capturing & Process, North University of China, Taiyuan 030051, China.

College of Mechanical Engineering, Suzhou University of Science and Technology, Suzhou 215009, China.

出版信息

Sensors (Basel). 2023 Aug 31;23(17):7575. doi: 10.3390/s23177575.

DOI:10.3390/s23177575
PMID:37688029
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10490708/
Abstract

Direction of arrival (DOA) estimation is an effective method for detecting various active interference signals during the satellite navigation process. It can be utilized for both interference detection and anti-interference applications. This paper proposes a DOA estimation algorithm for satellite interference sources based on frequency domain covariance matrix reconstruction (FDCMR) to address various types of active interference that may occur in the satellite navigation positioning process. This algorithm can estimate the DOA of coherent signals from multiple frequency points under low signal-to-noise ratio (SNR) conditions. The signals received from the array are transformed from the time domain to the frequency domain using a fast Fourier transform (FFT). The data corresponding to the frequency point of the target signal is extracted from the signal in the frequency domain. The frequency domain covariance matrix of the received array signals is reconstructed by utilizing its covariance matrix property. The spatial spectrum search method is used for the final DOA estimation. Simulation experiments have shown that the proposed algorithm performs well in the DOA estimation under low SNR conditions and also resolves coherency. Moreover, the algorithm's effectiveness is verified through comparison with three other algorithms. Finally, the algorithm's applicability is validated through simulations of various interference scenarios.

摘要

到达方向（DOA）估计是卫星导航过程中检测各种有源干扰信号的有效方法。它可用于干扰检测和抗干扰应用。本文提出了一种基于频域协方差矩阵重构（FDCMR）的卫星干扰源DOA估计算法，以解决卫星导航定位过程中可能出现的各种有源干扰。该算法能够在低信噪比（SNR）条件下估计多个频率点上相干信号的DOA。利用快速傅里叶变换（FFT）将阵列接收到的信号从时域转换到频域。从频域信号中提取目标信号频率点对应的数据。利用其协方差矩阵特性重构接收阵列信号的频域协方差矩阵。采用空间谱搜索方法进行最终的DOA估计。仿真实验表明，所提算法在低SNR条件下的DOA估计中表现良好，并且能够解决相干性问题。此外，通过与其他三种算法的比较验证了该算法的有效性。最后，通过各种干扰场景的仿真验证了该算法的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/1052d413f753/sensors-23-07575-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/5fe7fc83a05c/sensors-23-07575-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/cc17ecda663d/sensors-23-07575-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/dff901c5e3c6/sensors-23-07575-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/62c9987b9c09/sensors-23-07575-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/f81bfda525ac/sensors-23-07575-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/de598c954b5b/sensors-23-07575-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/ba06a5516bda/sensors-23-07575-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/01074815b813/sensors-23-07575-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/cc98f33503c2/sensors-23-07575-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/1052d413f753/sensors-23-07575-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/5fe7fc83a05c/sensors-23-07575-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/8172219644d6/sensors-23-07575-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/471b9d99e398/sensors-23-07575-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/d18e41a1ab47/sensors-23-07575-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/cc17ecda663d/sensors-23-07575-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/dff901c5e3c6/sensors-23-07575-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/62c9987b9c09/sensors-23-07575-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/f81bfda525ac/sensors-23-07575-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/de598c954b5b/sensors-23-07575-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/ba06a5516bda/sensors-23-07575-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/01074815b813/sensors-23-07575-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/cc98f33503c2/sensors-23-07575-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6757/10490708/1052d413f753/sensors-23-07575-g013.jpg

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