Research on Optimization Algorithm of RSSI Positioning Parameters Based on Improved Particle Swarm Optimization

Abstract

The paper put forward to an algorithm based on hybrid mutation particle optimization swarm strategy (HMPOA), it can solve the position coordinates of the unknown nodes. The algorithm uses static sampling to determine the performance index values of particles, then the arc grouping method is used to divide the particle swarm into several subgroups. Finally, the hybrid mutation strategy is used to improve the convergence speed and positioning accuracy of the algorithm, which can overcome the location accuracy of unknown node that overly dependent on the RSSI physical measurement value. Numerical experiments show that the algorithm has fast convergence speed and high positioning accuracy for unknown nodes, and it is feasible for RSSI positioning.