Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (2): 593-600.doi: 10.13229/j.cnki.jdxbgxb20210200

Previous Articles    

TDOA/FDOA localization based on chaotic sparrow search algorithm

Qiang GUO(),Guo-hui ZHU,Wan-chen LI   

  1. College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China
  • Received:2021-03-15 Online:2023-02-01 Published:2023-02-28

Abstract:

In the actual localization scenarios, the receiving station is usually installed on the moving platform, which leads to the random error in its moving state information. However, the target source location accuracy is very sensitive to the location information of the receiving station, and the small error in the location of the receiving station will lead to a large error in the estimation of the target source position. Therefore, considering the random error of the location information of the receiving station, a solution to locate the mobile source using the measured values of the time difference of arrival and the frequency difference of arrival is proposes in this paper. Logistic chaotic mapping is introduced into sparrow search algorithm to locate and track the target. Logistic chaotic mapping can reduce the risk of the algorithm convergence to local optimal, so as to solve the problem of poor localization accuracy in the case of low sensor position error. The analysis of simulation results shows that the accuracy of the proposed algorithm is closer to the Cramer-Rao lower bound than that of semi-definite programming and reformulation linearization technique(SDP-RLT), genetic algorithm, sparrow search algorithm and ant colony algorithm under the condition of low sensor position error.

Key words: information processing technology, time difference of arrival, frequency difference of arrival, sparrow search algorithm, logistic chaotic mapping

CLC Number: 

  • TP277

Fig.1

Distribution of αt when σ takes different values"

Fig.2

Distribution of αt with the value of σ and α0"

Table 1

Position and velocity of receiving station and target source"

接收站及近场源xiyizix˙iy˙iz˙i
130010015030-2020
2400150100-301020
330050020010-2010
4350200100102030
5-100-100-100-201010
近场源600650550-201540

Fig.3

Comparison of convergence curves of two algorithms of CSSA and SSA"

Fig.4

Location RMSE curve of five algorithms in near-field source"

Fig.5

Location bias curve of five algorithms in near-field source"

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