The Distributed Tracking Algorithm Based On Wireless Sensor Network

As a new attractive IT technology, wireless sensor network (WSN) is very promising in many military and civil applications. In the military field, the target tracking technolodge based on wireless sensor network can be applied to missile defense, air defense and surveillance operations, etc. In the civilian areas, it can be used for traffic control, navigation and robot path planning and obstacle avoidance, etc. Therefore the study of target tracking is of great theoretical and practical significance.Since the limited energy of the sensors and the weak processing capability, it is significant to design an alogorithm with low complexity as well as high efficiency. There is a contradiction between the extreme complexity of target tracking and the low capacity of each sensor node. Distributed is an essential characteristic of WSN, which is also a powerful measure to solve this contradiction. Through the collaborative work among all neighboring nodes, the lack of powerful capcity for a single node is overcome in order to satisfy the application requirements.In order to realize real-time and accurate localization and tracking of mobile target on known wireless sensor network, we propose a novel algorithm:JPEKF (Jointed Particle and Extended-Kalman Filter). This alogrthm has two modules:it first applies insensitiveness of Particle Filter to initial estimation error to catch the target, which avoids the divergence due to the big error in initial estimation when using Extended Kalman Filter (EKF), and then uses EKF to keep the tracking of target. When the target is missing, the system will start relocalization mechanism and JPEKF also will initialize.The simulation results show that JPEKF is a robust algorithm with high accuracy and computing efficency.