Abstract
Wireless sensor network (WSN) is a self-organizing network which is composed of a large number of cheap microsensor nodes deployed in the monitoring area and formed by wireless communication. Since it has the characteristics of rapid deployment and strong resistance to destruction, the WSN positioning technology has a wide application prospect. In WSN positioning, the nonline of sight (NLOS) is a very common phenomenon affecting accuracy. In this paper, we propose a NLOS correction method algorithm base on the time of arrival (TOA) to solve the NLOS problem. We firstly propose a tendency amendment algorithm in order to correct the NLOS error in geometry. Secondly, this paper propose a particle selection strategy to select the standard deviation of the particle swarm as the basis of evolution and combine the genetic evolution algorithm, the particle filter algorithm, and the unscented Kalman filter (UKF) algorithm. At the same time, we apply orthogon theory to the UKF to make it have the ability to deal with the target trajectory mutation. Finally we use maximum likelihood localization (ML) to determine the position of the mobile node (MN). The simulation and experimental results show that the proposed algorithm can perform better than the extend Kalman filter (EKF), Kalman filter (KF), and robust interactive multiple model (RIMM).
Highlights
Due to the development of microelectromechanical systems, wireless communication, and microprocessor, Wireless sensor network (WSN) has been developed rapidly
The input of the algorithm is dikði = 1, 2, 3 ⋯, NÞ, and N is the number of beacon nodes. di1∣k is the output of orthogon filter (OF) while the di2∣k is the output of robust extend Kalman filter (REKF), fuse these data with the Markov chain and the output is dik, after that, use the tendency amendment to eliminate the distance data with obvious nonline of sight (NLOS) noise
The hardware version of the UWB beacon node used in the real experiment is D-DWMPG1.7V, which is an evaluation board based on DWM1000 official positioning module
Summary
Due to the development of microelectromechanical systems, wireless communication, and microprocessor, WSN has been developed rapidly. We urgently need a positioning system which is less disturbed by obstacles and has high positioning accuracy compared with GPS. At this time, wireless positioning system has been increasingly valued by people, which can accurately locate in a complex environment such as an indoor or urban area. Wireless positioning system set a number of beacon nodes (BN) in the area to locate the position of MN. It can be widely used in many ways. It can track the enemy target, and in civilian, it can be used to help people to get the location of friends and so on
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