Maneuvering Target Tracking In LOS/NLOS Hybrid Environment

With the increasing demand for location information, and the further research of the corresponding professional direction, more and more researchers pay attention to it. In the process of tracking, None-line-of-sight(NLOS), multipath effect, channel noise and other serious impact will influence the accuracy of tracking. Among them, NLOS is the greatest impact on the positioning accuracy. In this background, this paper discusses and studies the target tracking on the line-of-sight(LOS) and non-line of sight hybrid environment, which gives two ways to deal with it. In addition, this paper will be extended the model from a single target tracking method to multiple maneuvering targets based on probability hypothesis density. The simulation results show that the proposed methods for tracking maneuvering target in LOS/NLOS environment hybrid is feasible and effective. Also the multiple target tracking method can ensure high tracking accuracy.This paper briefly introduces the common problems of target tracking and the background and significance of the research on target tracking in LOS/NLOS hybrid environment. A simple analysis of the development of the research on the single machine moving target tracking and multi maneuvering target tracking is given. For the maneuvering target tracking scenario, several classical filtering methods are introduced, including Bayes filtering, extended Kalman filter(EKF) algorithm, unscented Kalman filter(UKF) algorithm and the interacting multiple model(IMM). This part of the thesis gave the basic theory to the following parts.In the third chapter, two different methods of tracking maneuvering target under the LOS/NLOS hybrid environment have been introduced. One of the methods is based on IMM-UKF-CS, and the other one is based on HIMM-UKF. The tracking method based on IMM-UKF-CS is specifically designed to describe the target’s maneuvering scene through LOS and NLOS model sets, and the model can effectively switch under the framework of IMM. Tracking method based on HIMM-UKF is composed of two layers in Markov switching model framework. The upper layer is used to handle the switching between the LOS and the NLOS environments. The lower-layer is used to deal with the maneuvers of the target. Simulation results demonstrate the effectiveness of the above two methods. In addition, this paper in the fourth chapter present a method based on probability hypothesis density of multiple maneuvering targets. It is in the framework of random finite set, using the probability hypothesis density with UKF for multiple maneuvering targets tracking in high clutter. Simulation results show that the proposed method can ensure the high precision and stability of the positioning accuracy in multi maneuvering target tracking scenarios.In the end, the theoretical knowledge and algorithm framework in the paper are summarized and discussed. The further research also prospected.