Node Localization Based on Trust Region Algorithm in Wireless Sensor Networks

In traditional localization methods based on distance measurement in wireless sensor networks, a lot of optimization algorithms are employed to improve the precision of location. However, the optimization performance may degrade because of the low SNR environment and the non-Gaussian noise distribution. To overcome this problem, the trust region (TR) algorithm based on the conic model is employed for iterative localization. The cone model is used for approximating the objective function of localization, and the optimization process is converted into a series of optimization sub-problems. Simulation results show that the TR based method acquires better performance, especially in low SNR environment.