Range-free localization schemes for large scale sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
Using proximity and quantized RSS for sensor localization in wireless networks
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Improvement on APIT Localization Algorithms for Wireless Sensor Networks
NSWCTC '09 Proceedings of the 2009 International Conference on Networks Security, Wireless Communications and Trusted Computing - Volume 01
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
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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 node's 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.