Mobility Prediction Based Tracking of Moving Objects in Wireless Sensor Networks

This paper investigates the multi-sensor fused localization of moving targets in a wireless sensor network. Each ultra-wide band (UWB) is assigned stability weight according to its survival time prediction. The measurement accuracy each into constraints distribution based on interactive multi-model method, double algorithm that considers and proposed. Based algorithm, information UWB sensor, inertial unit (IMU)-based state vector UWB-based by federated Kalman filter are integrated realize correction IMU. Finally, several numerical simulations performed show proposed can effectively suppress dropout when tracking network, it also automatically adjust error covariance improve accuracy.