Passive Target Localization Problem Based on Improved Hybrid Adaptive Differential Evolution and Nelder-Mead Algorithm
Joint Authors
Simić, Mirjana
Rosić, Maja B.
Pejović, Predrag V.
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-27
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
This paper considers a passive target localization problem in Wireless Sensor Networks (WSNs) using the noisy time of arrival (TOA) measurements, obtained from multiple receivers and a single transmitter.
The objective function is formulated as a maximum likelihood (ML) estimation problem under the Gaussian noise assumption.
Consequently, the objective function of the ML estimator is a highly nonlinear and nonconvex function, where conventional optimization methods are not suitable for this type of problem.
Hence, an improved algorithm based on the hybridization of an adaptive differential evolution (ADE) and Nelder-Mead (NM) algorithms, named HADENM, is proposed to find the estimated position of a passive target.
In this paper, the control parameters of the ADE algorithm are adaptively updated during the evolution process.
In addition, an adaptive adjustment parameter is designed to provide a balance between the global exploration and the local exploitation abilities.
Furthermore, the exploitation is strengthened using the NM method by improving the accuracy of the best solution obtained from the ADE algorithm.
Statistical analysis has been conducted, to evaluate the benefits of the proposed modifications on the optimization performance of the HADENM algorithm.
The comparison results between HADENM algorithm and its versions indicate that the modifications proposed in this paper can improve the overall optimization performance.
Furthermore, the simulation shows that the proposed HADENM algorithm can attain the Cramer-Rao lower bound (CRLB) and outperforms the constrained weighted least squares (CWLS) and differential evolution (DE) algorithms.
The obtained results demonstrate the high accuracy and robustness of the proposed algorithm for solving the passive target localization problem for a wide range of measurement noise levels.
American Psychological Association (APA)
Rosić, Maja B.& Simić, Mirjana& Pejović, Predrag V.. 2020. Passive Target Localization Problem Based on Improved Hybrid Adaptive Differential Evolution and Nelder-Mead Algorithm. Journal of Sensors،Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1190411
Modern Language Association (MLA)
Rosić, Maja B.…[et al.]. Passive Target Localization Problem Based on Improved Hybrid Adaptive Differential Evolution and Nelder-Mead Algorithm. Journal of Sensors No. 2020 (2020), pp.1-20.
https://search.emarefa.net/detail/BIM-1190411
American Medical Association (AMA)
Rosić, Maja B.& Simić, Mirjana& Pejović, Predrag V.. Passive Target Localization Problem Based on Improved Hybrid Adaptive Differential Evolution and Nelder-Mead Algorithm. Journal of Sensors. 2020. Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1190411
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190411