A Simultaneous Localization and Tracking Algorithm Based on Compressing Kalman Filter

Simultaneous Localization and tracking was studied to solute the problem of tracking a moving target in a sensor network while simultaneously localizing and calibrating the nodes of the network. RSSI is used for measuring the distance between the nodes pairs, multidimensional scaling techniques are used for the initial position of wireless sensor network based on the distance matrix. Then the compression Kalman filter is used to estimate and update the sensor node position and the target position. Simulation results show that the algorithm has high accuracy and real-time performance under low network, especially for long distance tracking. Copyright © 2014 IFSA Publishing, S. L.