Performance Evaluation of Localization Algorithms with Measurement Errors in WSNs

Node localization is an important area in wireless sensor networks (WSNs). Because there are unavoidable measurement errors by the popular distance measurement techniques such as RSSI and TOA, the localization precision is the main evaluation criteria for localization algorithms. In this paper, we compare the performances of localization algorithms in different error models by simulation and show that some algorithms are more sensitive to measurement errors than others. The localization errors are more serious when measurement error models are different for distance from various beacon nodes. We give a nonlinear optimal model for this case and employ the Newton Iteration algorithm to solve this problem. Simulation shows it is better when give different weights to different error models can give a better measurement precision.