Performance Analysis and Deviation Correction Method of Direct Position Determination in the Presence of Array Modeling Errors
CHEN Xin1,2, WANG Ding1,2, TANG Tao1,2, YIN Jie-xin1,2, WU Ying1,2
1. Institute of Information System Engineering, PLA Information Engineering University, Zhengzhou, Henan 450001, China;
2. National Digital Switching System Engineering and Technology Research Center, Zhengzhou, Henan 450001, China
Abstract：Compared with the conventional two-step (including parameter estimation and position solution) localization mode,direct position determination (DPD) algorithm has more advantages,such as higher position estimation accuracy,strong resolution capability,etc.However,the performance of DPD algorithm is affected by the array modeling errors.In this paper,the localization deviation for multiple signal classification (MUSIC)-based DPD algorithm is derived quantitatively by using first-order Taylor expansion in the presence of array modeling errors.The result demonstrates that there is a nonlinear relationship between the true location of the radiation source and biased position estimation obtained from MUSIC-DPD,but this relationship cannot be accurately expressed in practice.To solve this problem,we propose the use of a multilayer perceptron (MLP) neural network (NN) for localization deviation correction of DPD.This method can effectively correct the localization deviation of DPD caused by array modeling errors through adaptive learning of NN.
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2019, Vol. 47 
