Sharif Digital Repository

The adaptive capability of filters is known to be increased by incorporating a neural network into the filtering procedure. In this paper, an adaptive algorithm for tracking maneuvering targets based on neural networks is proposed. This algorithm is implemented with two filters based on the current statistical model and a multilayer feedforward neural network. The two filters track the same maneuvering target in parallel and the neural network automatically considers all the state information of the two filters and adaptively adjusts the process variance of one of them to achieve better performance in different target maneuver tracking. Simulations results show that the proposed adaptive... 

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 Altering (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 while it has a lower precision in tracking the maneuvering targets with smaller acceleration. In the proposed algorithm, to overcome the disadvantage of the CSMAF algorithm, the covariance of process noise CSMAF is adjusted adaptively by the output of a FIS. The input of the FIS is discrepancy of...