基于空时频协方差矩阵重构的高效跳频信号DOA估计

Efficient Frequency Hopping Signal DOA Estimation Based on Spatial Time-Frequency Covariance Matrix Reconstruction

  • 摘要: 为了充分利用跳频信号的空域信息来进行信号的DOA估计,在信号空时频分析的基础上,本文提出了一种基于协方差矩阵重构的高效跳频信号DOA估计方法。首先将接收信号的均匀线阵(uniform linear array, ULA)平均划分成2个子阵,分别对每个子阵接收到的信号进行时频分析,在时频域选择有效跳,构造每跳的空时频矩阵(spatial time-frequency distribution, STFD),然后求得2个子阵的互协方差矩阵。将2个子阵的互协方差矩阵进行重构运算得到等效的信号子空间,最后构造空间谱多项式求根估计出信号的DOA。仿真结果表明该方法相比于以往改进类子空间算法能够有效提高估计精度和降低算法复杂度。

     

    Abstract: In order to make full use of the spatial domain information of frequency hopping signals for DOA estimation of signals, based on the analysis of signal space-time-frequency analysis, an efficient frequency hopping signals DOA estimation method based on covariance matrix reconstruction is proposed in this paper. Firstly, the uniform linear array of the received signal is divided into two sub-arrays, and the time-frequency analysis is performed on the signals received by each sub-array. Effective hops are selected from the time-frequency domain and every hop’s spatial- frequency matrix is built. The cross-covariance matrix of two sub-arrays are computed. Reconstructing the cross-covariance matrix of two sub-arrays to obtain the equivalent signal subspace, and finally the spatial spectral polynomial is used to estimate the DOA of the signal. The simulation results show that the proposed method can improve the estimation accuracy and reduce the complexity of the algorithm compared with the improved subspace algorithm.

     

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