In this paper, adaptive sensor fusion INS/GNSS is proposed to solve specific problem of non linear time variant state space estimation with measurement outliers, different algorithms are used to solve this specific problem generally occurs in intentional and non-intentional interferences caused by other radio navigation sources, or by the GNSS receiver’s deterioration. Non linear approximation ...

This paper aims to develop an Adaptive Sliding Kalman Filter (ASKF) by fusing the concept of change detection in a data stream, adapting noise covariance matrices and the Sliding Kalman filter (SKF). Adaptive Kalman filtering (AKF) scheme modifies the noise covariance matrix (Q and R) value based on a window of past innovation sequence whereas SKF is a window based filtering technique which use...

The maneuver characteristic of the most commonly used AUV integrated navigation systems was investigated in this paper. After analyzing the error cause of conversional used Kalman filter of SINS/DVL integrated navigation systems in maneuver state, a novel method was proposed which is to use the output of complex navigation systems to revise the SINS in real-time, and an improved adaptive Kalman...

The unscented Kalman filter (UKF) is adopted in the interacting multiple model (IMM) framework to deal with the system nonlinearity in navigation applications. The adaptive tuning system (ATS) is employed for assisting the unscented Kalman filter in the IMM framework, resulting in an interacting multiple model adaptive unscented Kalman filter (IMM-AUKF). Two models, a standard UKF and an adapti...

In this paper, after defining pure proportional navigation guidance in the 3-dimensional state from a new point of view, range estimation for passive homing missiles isexplained. Modeling has been performed by using line of sight coordinates with a particulardefinition. To obtain convergent estimates of those state variables involved particularly inrange channel and unavailable from IR trackers...

A new adaptive Unscented Kalman Filter (UKF) algorithm for actuator failure estimation is proposed. A novel filter method with the ability to adapt to the statistical characteristics of noise is presented to improve the estimation accuracy of traditional UKFs. A new algorithm (Kalman Filter (KF) ‐based adaptive UKF), with the ability to adapt to the statistical characterist...

In this work, a hybrid solar irradiance now-casting mechanism is proposed. The proposed hybrid predictor fuses the results from both Kalman filter predictor and regressor predictor to benefit from the advantages of both techniques. A time-varying adaptive system function for Kalman filter is designed to deal with ramp-down events for more accurate prediction. Three fusion alternatives based on ...

An algorithm for real-time estimation of the pose of a moving object of known geometry is considered. The algorithm is based on a discrete-time Extended Kalman Filter which computes the object pose on the basis of visual measurements of the object features. The robustness of the algorithm with respect to measurement noise and modelling errors is improved by considering a full adaptive version o...

The augmented complex Kalman filter (ACKF) has been recently proposed for the modeling of noncircular complexvalued signals for which widely linear modelling is more suitable than a strictly linear model. This has been achieved in the context of neural network training, however, the extent to which the ACKF outperforms the conventional complex Kalman filter (CCKF) in standard adaptive filtering...