An approach of tracking multiple maneuvering targets using the
multiple-observation algorithm is developed in this paper. With the
developed algorithm, the sensors can be installed in fixed or moving
systems which will improve the tracking accuracy and reliability of radar
surveillance. Target maneuvering situations are usually existed in radar
tracking systems and the maneuvering will cause severe tracking errors.
Therefore accurately detecting and estimating maneuvering status of targets is one essential step in the reduction of tracking errors. In this paper, we apply a multiple-model estimator to track maneuvering targets for a radar system. Moreover, in order to achieve the optimal correlation between measurements and the existing targets, a data association using Competitive Hopfield Neural Network (CHNN) technique is applied in this system.Applying the proposed approach, the system will obtain the more accurate tracking results.