Research on APIT and Monte Carlo Method of Localization Algorithm for Wireless Sensor Networks
Traditional approximate point-in-triangulation test (APIT) localization algorithm requiring low equipped hardware, having relatively high location accuracy, is easy to implement, and widely used in wireless sensor network positioning system. However, the location accuracy of unknown node in triangle overlap region should be further improved, especially in the sparse beacons environment, the location accuracy is seriously affected. In this paper, MC-APIT algorithm is proposed, which implements random sampling using the Monte Carlo method in the overlap region, and filters samples through the target nodes RSSI (Received Signal Strength) sequence values, in order that Mathematical expectation of the sample values could converge to that of the target node. Simulation results show that: the algorithm can reduce the sampling area and the location energy consumption, to a certain extent restrained the propagation error. Compared with APIT algorithm, the location accuracy has been markedly improved.
wireless sensor networks localization algorithms APIT Monte Carlo
Jia Wang Fu Jingqi
College of Mechanical and Electrical Engineering and Automation,Shanghai University, Shanghai 200072, China
国际会议
无锡
英文
128-137
2010-09-17（万方平台首次上网日期，不代表论文的发表时间）