Automotive radar tracking of multi-target for vehicle CW/CA systems
An automotive radar tracking method for vehicle collision warning and collision avoidance (CW/CA) systems is proposed. Currently, the joint probabilistic data association (JPDA) algorithm is a good approach to solve the ambiguity of multi-target data association problem. However, this algorithm might not be easily adapted for a real road application because its computational load is very high. The proposed algorithm provides an optimal method for the track-to-measurement data association by using the decision logic based on order statistics. Simulation results in a cluttered environment show that the tracking performance of the proposed method is better than that of the JPDA filter while maintaining the processing time similar with the probabilistic data association filter, which is a efficient algorithm computationally. To evaluate the performance, the proposed method is implemented using a developed digital signal processing board. Experiments show also the same results as the simulation performances. (C) 2003 Elsevier Ltd. All rights reserved.
tracking joint probabilistic data association multi-target data association detection