Based on the fast stable convergence characteristics of successive over relaxation (SOR) iterative and Jacobi GaussSeidel (JGS) iterative, a blind adaptive SOR/JGS iterative Kalman multi-user detection (MUD) algorithm (SJK) is proposed for multiple access communication system as direct sequence spread spectrum code division multiple access (DSCDMA) system with multi-path fading channel. The pro...

The Global Positioning System (GPS) is a satellite-based navigation system that provides a user with the proper equipment access to useful and accurate positioning information anywhere on the globe. The well-known Kalman filter (Gelb, 1974; Brown & Hwang, 1997; Axelrad & Brown, 1996) provides optimal (minimum mean square error) estimate of the system state vector, and has been widely applied to...

Kalman filter is a well known adaptive filtering Algorithm, widely used for target tracking applications. When the system model and measurements are non linear, variation of Kalman filter like extended Kalman filter (EKF) and Unscented Kalman filters (UKF) are used. For obtaining reliable estimate of the target state, filter has to be tuned before the operation (off line).Tuning an UKF is the p...

Kalman filter technniques are widely used in the areas of attitude and orbit determination, prediction and calibration. These techniques work well if the system dynamics are well-defined. Problems arise, however, when the system parameters are unknown ahead of time or changing over time. This paper discusses an adaptive Kalman filter design that utilizes recursive maximum likelihood parameter i...

It is known that the Kalman filter estimation performance heavily depends on the statistical parameters to both the dynamic and observation models, especially the covariance matrix Q. This paper presents a fast genetic algorithm (GA) to adapt extended Kalman filter (EKF) for real time tracking. In the proposed method, the covariance matrix Q can be real-time adjusted by GA to meet some specific...

One of the most important problems when designing controller is how to deal with all kinds of uncertainties, which, along with the high nonlinearities of most real systems, makes it difficult to guarantee the desired closed loop performance. Recently, nonlinear Kalman-class filter has been extensively researched and several well-known algorithms, including Extended Kalman Filter (EKF), Unscente...

-Remote Sensing technologies provide the spatial data/maps and offer great advantages for a land consolidation project. But sometimes in some regions, optics and infrared remote sensing can not work well. SAR (Synthetic aperture radar), an active microwave remote sensing imaging radar, has the unique capabilities of obtaining abundant electromagnetic information from ground objects all day/all ...

Fault Detection and Isolation (FDI) using Linear Kalman Filter (LKF) is not sufficient for effective monitoring of nonlinear processes. Most of the chemical plants are nonlinear in nature while operating the plant in a wide range of process variables. In this study we present an approach for designing of Multi Model Adaptive Linear Kalman Filter (MMALKF) for Fault Detection and Isolation (FDI) ...

This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix 'R' and the system noise V-C matrix 'Q'. Then, the...