Target Positioning and Tracking in WSNs Based on AFSA

In wireless sensor networks (WSNs), the target positioning and tracking are very important topics. There many different methods used in tracking, for example, angle of arrival (AOA), time (TOA), difference (TDOA), received signal strength (RSS). This paper uses an artificial fish swarm algorithm (AFSA) indicator (RSSI) channel model indoor tracking. The performance eight method combinations fixed or adaptive steps, region segmentation (RSM), Hybrid Adaptive Vision Prey (HAVP) method, a Dynamic AF Selection (DAFS) proposed this is investigated when number 100, 72, 52, 24, 12. simulation results show that using HAVP total average error reduced by 96.1%, shortened 26.4% position. Adopting HAVP, RSM, DAFS can be greatly 42.47% without degrading success rate.