in the present study, field oriented control of step motor implementation has been analyzed sothat it can make a sensorless control. efficiency and facilities of step motor is more than othertypes of electromotor. therefore, the numbers of mechanisms and different types of turning canbe made into them. also controlling these motors is easier than other available motors. steppingmotor has been d...

The GPS/INS integration system estimates the navigation errors as well as internal sensor errors through the use of a Kalman filter. The tight integration processing mode uses the GPS range and range-rate measurements in a nonlinear Kalman filter. Extended Kalman filtering (EKF) has been discussed in many publications dealing with GPS/INS integration. The recently developed sigma-point Kalman f...

Visual object tracking is the active area of research in the computer vision. Various techniques have being developed for the object tracking .Particle filter deals with the tracking of the objects having non linear motion .Particle filter has been used in for various fields and application efficiently. Proposed Technique is based on combination of kalman filter, mean shift and particle filter....

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...

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...

Precise point positioning with satellite navigation signals requires knowledge of satellite code and phase biases. In this paper, a new multi-stage method is proposed for estimating of these biases using measurements from a geodetic network. The method first subtracts all available a priori knowledge on orbits, satellite clocks and multipath from the measurements to reduce their dynamics. Secon...

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...

—Traditional Kalman filter (KF) is derived under the well-known minimum mean square error (MMSE) criterion, which is optimal under Gaussian assumption. However, when the signals are non-Gaussian, especially when the system is disturbed by some heavy-tailed impulsive noises, the performance of KF will deteriorate seriously. To improve the robustness of KF against impulsive noises, we propose in ...

In this paper we have applied radial basis function neural networks for equalization of wireless channel in the presence of additive noise. We have been tested the adaptive filter algorithms of simple Kalman filter, extended Kalman filter, rbfn Kalman filter, rbfn extended Kalman filter, fuzzy Kalman filter and fuzzy extended Kalman filter which might be considered applicable for wireless chann...