微型电脑应用2026，Vol.42Issue(3)：161-164,4.
基于模拟卡尔曼滤波的无线通信传感器网络覆盖优化方法
Coverage Optimization Method of Wireless Communication Sensor Networks Based on Simulated Kalman Filter
摘要
Abstract
Aiming at the coverage optimization problem of wireless sensor networks(WSN),this paper proposes a solution based on simulated Kalman filter(SKF)algorithm.The main purpose of using SKF algorithm is to maximize the sensor cover-age in the interested area to improve the service quality of WSN.Specifically,the candidate solution of the network coverage is generated by random initialization,and it is predicted,measured,and estimated based on the Kalman filtering process in each iteration to continuously optimize the sensor position distribution.The experimental results show that the coverage of SKF al-gorithm is better than that of particle swarm optimization(PSO)algorithm and genetic algorithm(GA)in various network con-figurations,especially in medium and high-density networks,SKF algorithm can significantly improve coverage and show strong convergence performance.关键词
网络覆盖/二值感知模型/模拟卡尔曼滤波/无线传感器网络Key words
network coverage/binary sensing model/SKF/WSN分类
信息技术与安全科学引用本文复制引用
黄海生..基于模拟卡尔曼滤波的无线通信传感器网络覆盖优化方法[J].微型电脑应用,2026,42(3):161-164,4.基金项目
2023年广东电网有限责任公司广州供电局科研项目(0301002023030301XG00101) （0301002023030301XG00101）
