Target tracking algorithms for UWB radar network

Recently, it has been shown that UWB radar networks (UWB-RN) represent a strong tool for a short-range detection and localization of moving persons. In order to improve the accuracy of the target localization, a target tracking is usually implemented as the final phase of the radar signal processing. For the target tracking by a single UWB sensor, the linear Kalman filter is used frequently. On the other hand, in the case of UWB-RN, a target tracking can be implemented simultaneously within several nodes. Moreover, it can be combined with point-to-track and track-to-track association algorithms. In this paper, three algorithms of the target tracking by UWB-RN with a centralized architecture are introduced and compared. The proposed algorithms consist of two steps. Firstly, a standard tracking algorithm is used within multiple target tracking algorithm implemented in the basic nodes of UWB-RN. For that purpose, the linear Kalman filter, the modified gain Kalman filter and the H-infinity a posteriori filter will be considered. Then, a track-to-track association and multiple track fusion are implemented in the central node of UWB-RN. The proposed approach of the target tracking has been analyzed for through-the-wall multiple target tracking by two-node UWB-RN. The obtained results indicate that the application of the modified gain Kalman filter overcomes the performance of the other tested algorithms.