Research On Maneuvering Target Location And Tracking Algorithm In Wireless Sensor Networks

With the development of science and technology, sensor technology and wireless communication technology have been an unprecedented development. Because of Wireless sensor network’s (Wireless Sensor Network, WSN) its low cost, low power consumption and environmental adaptability characteristics, WSN has become a new access to information and information processing platforms which also become scholars research hotshot in recent years. Mass deployment of wireless sensor nodes in the target area form a network in the form of self-organization, and then to carry a variety of sensors (such as temperature, humidity, etc.) for a variety of environments in the network or detecting objects in real-time monitoring and sensing and access information. Being Able to quickly layout, strong adaptability and high precision monitoring, covering a wide range of features make the wireless sensor network is widely used in environmental monitoring, forest fires, medical care, national defense and target tracking.Wireless sensor network positioning and maneuvering target tracking is to use sensor nodes carry detectors (such as radio frequency, ultrasonic, infrared or radar, etc.) in which the movement of the target (such as robots, aircraft, ships, etc.) measurements, moving target speed, position, acceleration and methods to estimate the state information tracking. Because of the detection of the measurement equipment and the environment data generated interference, the processing of the measured data is necessary, because the target tracking process is a process to eliminate interference information environment.This paper researches a wireless sensor network localization and tracking maneuvering targets. The main content of the work are the following:First, according to sensor node localization algorithm, this paper puts forward to a new local coordinate system positioning itself sensor algorithm in wireless sensor networks. Each node relies on ultrasound and RF technology, access node to the time difference of arrival method by between adjacent sensor nodes distance, and then each node in the network to obtain the exact position of the local coordinate system by the autonomous positioning method.Secondly, it introduces the basic concepts, principles of particle filtering algorithm, the current location and the mathematical model for maneuvering target tracking, and the establishment of a state model motion state model of the mobile robot and multi-target tracking and analysis of the particle filter algorithm shortcomings and limitations. Combining with genetic variance optimization, this paper put forward to an adaptive particle filter algorithm. Using genetic algorithms to choose the initial particle, particle operator can increase diversity through genetic manipulation, then the noise variance adaptive method is modified by variance system in real time process model in order to achieve the purpose of improving the importance density function. Simulation results show that the improved method is better than the standard particle filter algorithm and the improved algorithm in the reflection. Simulation results show that the improved algorithm is superior to the standard particle filter.Finally, this paper researches a wireless sensor network positioning and maneuvering target tracking technology and describes the data fusion method for multi-maneuvering target tracking process and introduces the K-nearest neighbor classification algorithm and is applied to the maneuvering target location and tracking system by improved algorithm. By single-target tracking and multi-target tracking simulation experiments, this paper demonstrates the effectiveness of the improved method.