A centralized asynchronous fusion algorithm for sensors with different resolution via DP-TBD

This paper addresses multiple targets tracking problem using multiple different resolution sensors via Dynamic Programming (DP) based Track-Before-Detect (TBD). Generally, DP-TBD is a grid-based method that estimates target trajectories by means of searching all the physically admissible paths in a determinate discrete state space. In actual war, by using the Radar Cross Section (RCS) spatial diversity, the spatial gain of targets can be obtained. So it is necessary to use multiple sensors to detect targets for better detection performance. In addition, when various radars are used, different radars own different resolution and sampling periods. But traditional DP-TBD can not deal with these measurement data directly. To alleviate this problem, a centralized asynchronous fusion algorithm for sensors with variable resolution via DP-TBD is proposed in this work. This algorithm is divided into two steps. In the first step, the echo data obtained from different resolution sensors are aligned to the measurement space of same cell size. In the second step, measurement data derived from sensors with different sampling periods is sent to the fusion center in time order. Next, DP-TBD is used to dispose these data and generate recover track. Besides, a method of adaptively adjusting transition states number is proposed to improve the efficiency of asynchronous fusion. Simulation results show that the proposed algorithm is able to solve sensors with different resolution asynchronous fusion problems and effectively improve the tracking performance of DP-TBD comparing to single sensor.