Based On The Mobile Beacon For Wireless Sensor Network Localization Algorithm

The foreground of Wireless Sensor Network(WSN) is wide. As a key supporting technique of WSN, node self-localization has become a research hot spot. According to the idea of virtual beacons originated from mobile beacon, Random Walk Model(RWM), Random Way Point Model(RWPM), Gaussian Markov Model(GMM) are researched. Through simulation experiment, the localization coverage rate of the three mobility model are presented under different mobility parameters. In the same condition, GMM and RWPM are better than RWM. But GMM is more realistic.A new range-based localization algorithm based on mobile beacon and Extended Kalman Filter(EKF) has been presented. At first, the mobile beacon is moved, the initial coordinate is computed through Weighted Centroid algorithm. Then the EKF is used to promoted localization precision. The simulation is conducted under different mobile time, speeds, iterative times. The simulation results shows the proposed algorithm reaches high precision. In the same condition, the proposed algorithm is better than LSE and WLSE based on mobile beacon. In addition, the algorithm need less static beacons and the effect of node radius is little so it can save network cost.An improved range-free DV-Hop algorithm based on mobile beacon is proposed. The coordinate of unknown node is computed using weighted least Squares method. The localization effect of mobile beacon is researched. Through simulation comparison with traditional DV-Hop and Centroid algorithm based on mobile beacon, the improved DV-Hop can reach relative high precision and low cost localization.According to the simulation of the presented two algorithms, the two algorithms are extensibile and can make good use of localiztion information. The two algorithms have relative high application value.