UWB/Binocular VO Fusion Algorithm Based on Adaptive Kalman Filter

Adaptive Kalman Filter for Navigation Sensor Fusion

As a form of optimal estimator characterized by recursive evaluation, the Kalman filter (KF) (Bar-Shalom, et al, 2001; Brown and Hwang, 1997, Gelb, 1974; Grewal & Andrews, 2001) has been shown to be the filter that minimizes the variance of the estimation mean square error (MSE) and has been widely applied to the navigation sensor fusion. Nevertheless, in Kalman filter designs, the divergence d...

Extended Kalman Filter Based Fuzzy Adaptive Filter

Vehicle Tracking based on Kalman Filter Algorithm

Received signal strength indicator (RSSI) is a difficult technique to accurately estimate the distance between two participating entities because of the obscure environmental factors that distort the signal’s strength. In this study, we demonstrate that RSSI can be used in combination with the Kalman Filter to identify the position of a node in a wireless vehicular network. By observing a serie...

Improved CAMshift Algorithm Based on Kalman Filter

In this paper, we describe a Continuously Adaptive Mean Shift (CAMshift) algorithm with a Kalman filter. A CAMshift algorithm does not consider an object’s direction vectors and velocity. In addition, sometimes, CAMshift loses the tracked object when the color of the background is similar to that of the object. However, using a Kalman filter with the CAMshift algorithm can overcome these disadv...

Kalman Filter Algorithm for Adaptive Digital Predistortion

This paper introduces a recursive algorithm of Kalman filter for digital predistorter parameters extraction based on memory polynomials predistorter model. The predistorter model is firstly formulated as linear regression expression. Then we derive the state-space equation of the model and attain the steps of the algorithm. Finally, the accuracy and stability of the algorithm is proved by simul...