关键词: 支持向量机, 粒子群优化算法, 室内定位, 无线网络

Abstract: In order to improve location accuracy and reduce environmental impact on indoor wireless location, this paper presents a novel indoor location method based on particle swarm optimization algorithm and support vector machine. Firstly, the indoor reference nodes are selected and the learning samples of indoor wireless location are obtained, and then support vector machine is used to establish the nonlinear model which can describe the relationship between input and output while and the parameters of support vector machine is optimized by particle swarm optimization algorithm, finally, the simulation is carried out to test the performance. The experimental results show that the proposed method has improved location accuracy and can control location error in effective range, and can meet the real-time requirement of indoor wireless location.

Key words: Support Vector Machine（SVM）, Particle Swarm Optimization（PSO） algorithm, indoor location, wireless network