Geometry-based target tracking methods in multistatic radar systems

Abstract

In this dissertation, target tracking schemes that can track targets with low complexity are studied in multistatic radar system. The first study deals with track initiation scheme utilizing the geometric characteristics of multistatic radar system with multiple transmitter multiple receiver (MTMR). Multistatic radar system, composed of monostatic radar and bistatic radar, has been recently studied actively because it can have the advantages of both radars. To initiate tracks in Multitarget tracking (MTT), the MTT problem should be solved, but is further complicated in multistatic radar system where the number of receivers and transmitters for target tracking increases. In this study, we propose a novel method to solve the MTT problem in MTMR. The proposed algorithm solves the uncertainty probelm between measurements and targets by using the geometric characteristic of multistatic radar system. Unlike the conventional methods of track initiation by calculating a likelihood function, it is shown that the proposed algorithm can initiate the tracks with less complicated computation. In the second study, a position dilution of precision (PDOP)-based target tracking algorithm in single transmitter multiple receiver (STMR) is proposed. Performance of estimation accuracy improves when the target position is estimated by using more measurements received in STMR, but the computational complexity also increases. Therefore, we proposed a PDOP-based target tracking algorithm with high estimation accuracy while reducing the computational complexity. PDOP is determined by the location of transmitters, receivers, and a target in multistatic radar system where the lower value of PDOP improves estimation accuracy. However, it is difficult to track the target using the optimal receivers in real time because exhaustive search is only the method to find the receivers having the lowest PDOP value. Therefore, in this study, we derive a method for finding receivers with low PDOP value for the minimum number of receivers required for target tracking. It is shown that the estimation accuracy of the proposed algorithm is comparable with that of exhaustive search that provides optimal receivers.