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Accuracy and precision of estimated state of target depends on the used motion model in tracking algorithm. Motion model of maneuvering targets is changed uncertainly, in each instant for their varying acceleration. In this paper, to minimize the estimation error produced from using mismatch motion model, an adaptive motion model is proposed. It is obtained based on adjusting the maneuvering time...
A significant problem in multi-sensor multi-target tracking system is measurement to track association. Based on fuzzy clustering means algorithm, an efficient algorithm has been proposed to solve this problem. The fuzzy clustering means data association (FCMDA) algorithm has better performance than the other already known fuzzy logic data association algorithms. However, it is still worthy to investigate...
The track fusion combines individual tracks formed by different sensors. Tracks are usually obtained by Kalman filter (KF), since it is suitable for real-time application. The KF is an optimal linear estimator when the measurement noise has a Gaussian distribution with known covariance. However, in practice, some of the sensors do not have these properties, and the traditional KF is not an optimal...
A new hybrid fuzzy adaptive algorithm for tracking maneuvering targets is proposed in this paper. The algorithm is implemented with fuzzy inference system (FIS) and current statistical model and adaptive filtering (CSMAF). The CSMAF algorithm is one of most effective methods for tracking the maneuvering targets. It has a higher precision in tracking the maneuvering targets with larger accelerations...
The current statistical model and adaptive filtering (CSMAF) algorithm is one of the most effective methods for tracking the maneuvering targets. However, it is still worthy to investigate the characteristics of the CSMAF algorithm, which has a higher precision in tracking the maneuvering targets with larger accelerations while it has a lower precision in tracking the maneuvering targets with smaller...
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