Track to track association problem is crucial for multi sensor data fusion, and become complicated in the presence of sensor bias, random errors, and false tracks and missed tracks. The optimal Bayes joint decision and estimation (JDE) was applied to the track to track association in the presence of sensor bias and a simplified JDE was developed in the paper. According to optimal Bayes JDE, the estimate error of the relative sensor bias was taken into account when considering the track to track association and vice versa. Hence the accuracy of track to track association was enhanced and the relative bias estimate error was reduced. The proposed simplified JDE algorithm for computational simplicity was slightly worse than the optimal Bayes JDE. The matlab simulation result verified the feasibility and effectiveness of the method.