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Time Difference Localization algorithm Based on Improved eel and grouper Optimizer

CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2025年第5期44卷 3223-3257页

作者： Zhang, Xinrong Zhang, Bojun Fang, Liping Huaiyin Inst Technol Fac Automat Huaian 223003 Peoples R China

As is well known, Time Difference of Arrival (TDOA) is a technique used for locating the position of a signal source based on the time difference of when the signal arrives at multiple receivers. The iterative method enhances the function through repeated iterations, which involve both deterministic iterations with initial values and stochastic optimizations with various algorithms. However, conventional optimization techniques often encounter issues such as slow convergence rates and becoming trapped in local optima. Stochastic optimization algorithms are an effective approach for solving TDOA problems. This research introduces and enhances the latest eel and grouper optimization (EGO) algorithms to address such issues. First, the initial population is randomized using primarily Bernoulli chaos sequences. Next, the exploration phase is enhanced by replacing the random search agents with a Logistic-Sine-Cosine Map chaos improvement, enabling more effective position updates and improving algorithm accuracy. Simulation results demonstrate that the enhanced EGO algorithm possesses strong exploration and convergence capabilities. The performance improvement is statistically significant, showcasing robust exploration abilities and efficient convergence speeds. The algorithm can quickly and reliably converge to the source location, providing high positioning accuracy.

关键词： Indoor localization Time difference of arrival Intelligent optimization algorithm eel and grouper optimization algorithm

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