Probabilistic data association algorithm based on entropy weight and gray correlation analysis

Data association mainly decided whether the data from different sensors stood for the same target in multi-target information fusion. Tradition data association always took the joint probabilistic data association (JPDA) algorithm as the priority means which depend on the state measurement and was complex with long computation time. A PDA algorithm used in the paper based on gray correlation analysis not only calculated with multiple features of the target, but also was easy and accurate and had short computation time. Compared to the weight factor given by subjective judgments of the experts, a new PDA algorithm was proposed based on entropy weight and gray correlation analysis. The algorithm made the data more theoretical by given the weight factor of entropy weight of the target features adaptively. Experiments showed that the proposed algorithm was effective in engineering.