This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...

Against the range-dependent accuracy of the tracking radar measurements including range, elevation and bearing angles, a new hybrid adaptive Kalman filter is proposed to enhance the performance of the radar aided strapdown inertial navigation system (INS/Radar). This filter involves the concept of residual-based adaptive estimation and adaptive fading Kalman filter and tunes dynamically the fil...

in this paper, we deal with the problem of adaptive coherent signal detection in gaussian interference (clutter plus noise) for surveillance pulse radars. some of the adaptive radar detectors exploit the ar model for clutter. most of these detectors have been obtained using the glr test. this test relies on the maximum likelihood estimation whose accuracy depends on the number of data. whereas,...

Due to widespread use of Global Positioning System (GPS) in different applications, the issue of GPS signal interference cancelation is becoming an increasing concern. One of the most important intentional interferences is spoofing signals. An effective interference (delay spoof) reduction method based on adaptive filtering is developed in this paper. The principle of method is using adaptive f...

In this paper, we developed an algorithm to remove additive mixed noise in images with the preservation of fine details and edges. The noise characteristics may vary in the same application from one image to another. In these environments, nonlinear general filters will not perform well and adaptive non-linear filters are best suited. The algorithm based on local statistics such as signal varia...

This research proposes an Adaptive Weighted Fuzzy Mean Filter (AWFMF) based on Cloud Model (CM) to remove the salt and pepper noise in the digital images. Also, the performance of the proposed filter is compared with existing variants of median and switching filters using peak signal to noise ratio (PSNR) and quality index. The proposed filter is able to remove salt and pepper noise even at 90%...