Multi-target Positioning And Tracking Method Based On Sensor Network

The sensor network system consists of the sensor transmitter and receiver which located in different places. By coalescing the echo which received by a large number of sensor receivers separated in space, the locations and tracks of the targets could be gained. Compared to the traditional single sensor system, sensor network has many advantages, such as higher reliability, larger scope, more accurately of the position. The key issue of the traditional sensor network is the matching relation between targets and the echoes, while it will cause huge calculation and the problem of extracting the targets accurately. The location algorithm of multiple targets based on imaging strategy which could solve the matching relation problem of echoes effectively is studied in this paper, and the main work and innovation are as follows:1. The basic theories of locations and tracking of multiple targets based on sensor networks is studied in this thesis. The traditional model of time difference of arrival(TDOA) has been introduced, and the shortcomings of traditional TDOA in the course of location and tracking for multiple targets have been analyzed; Aiming at the shortcomings of TDOA, the principles of location for multiple targets have been studied in detail based on imaging strategy. Further, two kinds of location methods based on observation space projection and the bistatic range space projection(BRSP) have been studied detailedly. In the end, the relevant theories and elements of tracking for multiple targets have been stated.2. The BRSP-TL method for multiple targets location based on hierarchical strategy has been proposed in this thesis. The existent problem of the BRSP algorithm has been studied. According the huge computation of the original method, the hierarchical strategy has been proposed in thesis: obtaining the imaging result in the condition of low resolution, then selecting area which might own targets as the next projection area, improving the resolution gradually and accomplishing the projection imaging. Aiming at the location of the original method is not accurate enough, this thesis uses the positioning results of BRSP location method as initial value, then the positioning accuracy is improved by using Taylor series expansion algorithm. It has been proved that the BRSP-TL for multiple targets location based on hierarchical policies has more accurate location results and the running speed increases a lot than that of the original method.3. The multiple maneuvering targets location and tracking algorithm based on sensor networks has been studied. First of all, the IMM-JPDA algorithm for multiple targets based on BRSP-TL algorithm has been studied, which utilizes the logical approach to accomplish the track initiation, then the tracking results can be gained though the IMM-JPDA method. Aiming at the gain tracking error of the IMM-JPDA algorithm when targets fly with maneuvering, two methods have been proposed: One is measurements updating of IMM-JPDA algorithm, which reduces the effects of state prediction by using the measurements to update the outcome of IMM-JPDA algorithm; The other is adaptive model probability of IMM-JPDA algorithm, which improves probability of the response speed of the motor model by using adaptive modification factor to modify the model probability. Further, the proposed methods have been proved that the tracking precision of the targets have been improved by simulation.