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A Bilevel Gene-Based Multiobjective Memetic Algorithm for Passive Localization System Deployment Optimization

delete2023-04-01
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PRE
AI
王
王昭 (Zhao Wang)
M
Maoguo Gong *
P
Peng Li
F
Fei Xie
M
Mingyang Zhang
DOI:10.1109/TEVC.2022.3168427delete
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摘要

摘要

En 中文
The passive localization system (PLS) is fundamental to many wireless applications. The deployment of the monitoring stations plays a key role in the performance of the PLSes. However, the workflow of the emerging cutting-edge PLSes is becoming more flexible in the complicated environment, which makes it hard to optimize the deployment. To fulfill the requirement of the real-world applications, we propose a multiobjective PLS deployment optimization model, including a surrogate geometric dilution of precision (S-GDOP) model and a system coverage indicator to meet the demand for the detection performance of the known and unknown targets. The proposed S-GDOP is separable and open to various performance-related factors in this article. Motivated by the various cooperation mechanisms and the empirical deployment patterns, we propose a bilevel gene-based multiobjective memetic algorithm within the decomposition framework to solve this problem. By maintaining an adaptive multicomponent gene population (MCGP) and a local pivot (LP)-based local search, the population evolves on two precise and consecutive gene levels, which effectively utilizes the problem and evolution-related heuristic information. The proposed algorithm outperforms another four popular algorithms in 83.3% bilateral comparisons and obtains more implicit deployment patterns, clearer deployment structures, and better converged Pareto fronts.
Keyword:
Location awareness
Optimization
Memetics
Statistics
Sociology
Measurement uncertainty
Heuristic algorithms
Geometric dilution of precision (GDOP)
memetic algorithm
Index Terms
multiobjective evolutionary algorithm (MOEA)
passive localization system (PLS)

期刊

IEEE Transactions on Evolutionary Computation 封面图
IEEE Transactions on Evolutionary Computation
IF:
12
论文数:
1.9K
被引数:
2.4W

机构

X
Xidian University
学者数:
2.4W
论文数: 1.9W
被引数: 9.7K
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