The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper introduces a reformulation of the extended Kalman Filter using the Gauss-Helmert model for least squares estimation. By proving the equivalence of both estimators it is shown how the methods of statistical analysis in least squares estimation can be applied to the prediction and update process in Kalman Filtering. Especially the efficient computation of the reliability (or redundancy) matrix...
Bayesian filtering appears in many signal processing problems, reason which has attracted the attention of many researchers to develop efficient algorithms, yet computationally affordable. Ranging from Kalman Filter (KF) to particle filters, there is a plethora of alternatives depending on model assumptions. We focus our interest into a recently developed algorithm known as the square-root Quadrature...
Based on modern control theory's method, the research and the exploration gush out the process modelling using the Kalman filtering principle to the damp to carry on the real-time forecast. Carries on the description to the gas discharge process is the discrete system, uses the state space model, uses the preceding time the estimated value and the present time observed value renews to the state variable...
The research topic of autonomous underwater vehicles (AUVs) has attracted much attention over years since they provide marine researchers easy ways to access the ocean for surveying and site investigation, etc. To accomplish these applications, an AUV has to know its position accurately. Therefore, AUV localization is very important problem. In this paper, we propose an interactive multiple model...
In this paper, the interaction force between a surgical needle and soft tissue is studied. The force is modeled using nonlinear dynamics based on a modified LuGre model that captures all stages of needle-tissue interaction including puncture, cutting, and friction forces. An estimation algorithm for identifying the associated parameters is then presented. This approach, which is based on extended...
Traffic state estimation is a prerequisite for traffic surveillance and control. For macroscopic traffic flow models several estimation methods have been investigated, including extended and unscented Kalman filters and particle filters. In this paper we propose a fuzzy observer for the continuous time version of the macroscopic traffic flow model METANET. In order to design the observer, we first...
In this paper, an optimization-based adaptive Kalman filtering method is proposed. The method produces an estimate of the process noise covariance matrix Q by solving an optimization problem over a short window of data. The algorithm recovers the observations h(x) from a system x = f (x); y = h(x)+v without a priori knowledge of system dynamics. Potential applications include target tracking using...
In the presence of random disturbances, control and optimization problems of the nonlinear discrete-time stochastic dynamic systems are more difficult to solve rather than the linear stochastic optimal control problem. This is due to the nonlinear structure of plant and the partially known state information. In this paper, we discuss the approach of model-reality differences to solve the nonlinear...
Whenever we apply methods for processing data, we make a number of model assumptions. In reality, these assumptions are not always correct. Robust methods can withstand model inaccuracies, that is, despite some incorrect assumptions they can still produce good results. We often want to know how robust employed methods are. To that end we need to have a yardstick for measuring robustness. In this paper,...
The ever growing demand of more resolution for ground telescopes makes of fundamental importance the use of computationally efficient algorithms. In this paper we consider some efficient algorithms for the adaptive optics system of large telescopes. The main peculiarities of the considered procedures are to be effective and scalable to telescopes of whatever size. In particular, we propose a decoupled...
Being a recursive technique which lends itself to implementation in a microcomputer, the Kalman filter is particularly suitable for on-line estimation. However, when measurement noise covariance R is much larger than process noise Q, the filtering effect will not be satisfied. A new algorithm, which we call innovation mean method, is proposed in this paper. The method makes different periods of measurement...
In this paper we present a framework for correcting the spatial drift that can occur in 3D optical fluorescence microscopy images. These shifts happen during long time acquisition and can corrupt further analysis. This artifact has to be taken into account especially if the application requires an high spatial detection accuracy. Our correction method is based on the use of a microsphere located within...
This paper addresses the problem of Multiple Model Adaptive Estimation (MMAE) for discrete-time, linear, time-invariant MIMO plants with parameter uncertainty and unmodeled dynamics. Model identification is analyzed in a deterministic setting by adopting a Minimum Energy selection criterion. The MMAE system relies on a finite number of local observers, each designed using a selected model (SM) from...
An extended Kalman filter-based interacting multiple model algorithm (IMM-EKF) is proposed for mobile terminal tracking in cellular networks based on time of arrival estimates. The proposed IMM-EKF is able to cope with line-of-sight (LOS) and non-line-of-sight (NLOS) conditions modeled by a Markov chain, where the LOS and NLOS errors are described by different noise models. Road-constraints are included...
An algorithm based on grey innovation model GM (1, 1) of fixed length is introduced for the localization and tracking of moving targets. Kalman filter is an efficient computational method for tracking, but motion and noise assumption limits its process model to constant velocity model or constant acceleration model. The grey system theory uses the data characteristic of extrinsic randomicity and holistic...
This paper consider the nonlinear state estimate problem for tracking maneuvering targets. Two methods are introduced to overcome the difficulty of non-linear model. The first method uses interacting multiple model (IMM) which includes 2, 3, 4 and 10 models. These models are linear, each model stands for an operation point of the nonlinear model. Two model sets are designed using equal-distance model-set...
Novelty detection is concerned with identifying abnormal system behaviours and abrupt changes from one regime to another. This paper proposes an on-line (causal) novelty detection method capable of detecting both outliers and regime change points in sequential time-series data. Our approach is based on a Kalman filter in order to model time-series data and extreme value theory is used to compute a...
In this paper, a scaled unscented Kalman filter (SUKF) based on the quaternion concept is designed for determination of the attitude, velocity and position parameters in inertial navigation system (INS) under large attitude error conditions. In this feedback filter, only bias effects are considered to be independent states and are used to compensate for navigation errors. To preserve the nonlinear...
The present study proposes two alternate model structures to represent exponentially damped sinusoids and proposes a novel method of estimating the parameters of the damped sinusoids by combining Hankel singular value decomposition (HSVD) with the extended complex Kalman filter (ECKF). The ECKF is capable of estimating the parameters and can effectively track the variations of damping constants and...
In Integrated Navigation System, the performance of Fibre Optics Gyroscope (FOG) has great influence to Inertia System. To increase the precision of FOG, the methods of filtering are used frequently. Kalman filter is the one which has already been quite practiced. It adopts the recursion method with a high speed in time domain, and it is convenient for real-time processing in Matlab, which offers...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.