阵列误差下的近场源PCA-BP参数估计算法

doi:10.19665/j.issn1001-2400.2022.01.018

Abstract

Abstract:

The steering vector of the array will be biased when there is an error in the signal receiving array,which will affect the performance of the parameter estimation algorithm.In order to reduce the influence of the array error on the parameter estimation results and reduce the computational complexity,a combination of intelligent algorithms and principal component analysis is used.First,in order to avoid the tedious process of error modeling,the back propagation neural network method is used to include errors and other factors in the network model.Second,it takes too long and is quite complicated for the back propagation neural network to train the near-field source parameter estimation model.In order to shorten the training time and reduce the amount of calculation,the principal component analysis method is introduced in the back propagation neural network model to reduce the dimension of the signal feature matrix.Then the reduced-dimensional signal feature matrix is used as the input feature of the back propagation neural network,and the near-field source parameters are used as the expected output for training,so as to simplify the network structure and shorten the training time.Finally,the received data containing signal information to be estimated is input into the trained network model to obtain the estimated value of the signal incident direction.This algorithm can accurately estimate the parameters of the near-field source in the presence of errors in the receiving array,and improve the estimation performance of the near-field source signal parameters under a low signal-to-noise ratio.Simulation experimental results show the effectiveness of the algorithm in this paper.

Key words: principal component analysis, near field source, the back propagation neural network, direction of arrival, covariance matrix

CLC Number:

TN911.7

WANG Le,ZHAO Peiyao,WANG Lanmei,WANG Guibao. Parameter estimation of the near-field source using the PCA-BPalgorithm with the array error[J].Journal of Xidian University, 2022, 49(1): 181-187.

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Parameter estimation of the near-field source using the PCA-BPalgorithm with the array error

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