In this paper, a methodology for design of fuzzy Kalman filter, using interval type-2 models, in discrete time domain, via spectral decomposition experimental data, is proposed. The adopted consists recursive parametric estimation local state space linear submodels filter tracking and forecasting the dynamics inherited to an version Observer/Kalman Filter Identification (OKID) algorithm. partit...

Previous research shows that Kalman filter based human-computer interactive Chinese word segmentation achieves an encouraging effect in reducing user interventions, but suffers from the drawback of incompetence in distinguishing segmentation ambiguities. This paper proposes a novel approach to handle this problem by using an adaptive Dirichlet process mixture model. By adjusting the hyperparame...

A method for determining adaptive observation locations is demonstrated. This method is based on optimal estimation (Kalman filter) theory; it determines the observation location that will maximize the expected improvement, which can be measured in terms of the expected reduction in analysis or forecast variance. This technique requires an accurate model for background error statistics that var...

According to the poor adaptive ability of traditional filter algorithm in the estimation for traffic state and travel time with Kalman filter, an improved fuzzy adaptive Kalman filtering method was proposed. The new interest of observation noise was defined, and the fuzzy logic was used to adjust the importance weights of system noise and observation noise through on-line monitoring the interes...

This paper presents an approach to vision-based target tracking with a neural network (NN) augmented Kalman filter as the adaptive target state estimator. The vision sensor onboard the follower (tracker) aircraft is a single camera. Real-time image processing implemented in the onboard flight computer is used to derive measurements of relative bearing (azimuth and elevation angles) and the maxi...

This paper presents an adaptive information fusion method to improve the accuracy and reliability of the altitude measurement information for small unmanned aerial rotorcraft during the landing process. Focusing on the low measurement performance of sensors mounted on small unmanned aerial rotorcraft, a wavelet filter is applied as a pre-filter to attenuate the high frequency noises in the sens...

In this paper we present an adaptive recursive nonlinear filter based on the higher order Volterra series infinite impulse response (IIR) structure. The proposed work is an extension of the work of Roy et al [9] in which they limit the Volterra recursive filter to the second order. Adaptive algorithms based on the exact and the approximate gradient will be derived. Stability issues based on the...

The joint detection of multiple signal streams, usually transmitted using code division multiple access (CDMA), can give much better performance than conventional matched-filter methods. Receivers designed using this idea are generically known as multiuser detectors. Our work in this area has included the development of a recursive chip-rate detector that gives linear minimum mean squared error...

Efficient and accurate clock synchronization is a challenge for wireless sensor networks (WSNs). Unlike previous works on clock synchronization in WSNs that consider communication delay as the main cause of clock inaccuracy, we propose a new adaptive synchronization scheme, AdaSynch, which considers the principium of the clock. We aim to overcome the challenges posed by WSNs’ resource constrain...

The main aim of this paper is to develop a low-cost GNSS/MEMS-IMU tightly-coupled integration system with aiding information that can provide reliable position solutions when the GNSS signal is challenged such that less than four satellites are visible in a harsh environment. To achieve this goal, we introduce an adaptive tightly-coupled integration system with height and heading aiding (ATCA)....