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Standard Kalman Filtering leads to divergence because of inaccurate system model and noise statistic. Researchers have taken relative studies about Kalman filtering optimization method. But now most studies are based on applications, such as integrated navigation system, so most of these methods are lack of general applicability. This paper starts from innovation-based adaptive estimation (IAE) filtering...
Due to the different data rates of the sensors and communication delays in the radar netting, the research of the asynchronous multisensor data fusion problem is more practical than that of the synchronous one. Through discussing the sequential approach, which is the classical asynchronous multisensor data fusion algorithm, a new algorithm based on distributed computation structure is proposed. The...
This paper is concerned with the design problem of multi-sensor optimal H∞ fusion controller for a class of discrete-time systems with missing measurements. Based on Lyapunov theory and linear matrix inequality technology, the centralized and distributed fusion controllers are designed, respectively such that, for all possible missing measurements, the closed-loop systems are asymptotically stable...
Misalignment angles estimation of strapdown inertial navigation system (INS) using global positioning system (GPS) data is highly affected by measurement noises, especially with noises displaying time varying statistical properties. Hence, adaptive filtering approach is recommended for the purpose of improving the accuracy of in-motion alignment. In this paper, a simplified form of Celso's adaptive...
In order to improve the performance of gyroscopes, the random drift error of a micro electro mechanical system (MEMS) gyro was analyzed and modeled. The noise feature of MEMS gyro is analyzed based on the AR model. By introducing a fading factor of Strong Tracking Filter (STF), the Sage-Husa adaptive Kalman filter reduced the effect of the error of model and noise statistical characteristics. The...
For the multisensor single channel autoregressive moving average (ARMA) signal with a white measurement noise and autoregressive (AR) colored measurement noises as common disturbance noises, when the model parameters and noise statistics are partially unknown, a self-tuning weighted fusion Kalman filter is presented based on classical Kalman filter method. The local estimates are obtained by applying...
Aiming to solve the problem of the accuracy of the states and parameters estimation are greatly influenced by initial values in the polynomial systems, this paper proposes a nonlinear filtering based joint state estimation and parameter identification method in the polynomial systems. Using the results of the least square as the initial values in the Extended Kalman Filtering (EKF) algorithm for estimating...
Due to the large misalignment angle, the error model of a strapdown inertial navigation system (SINS) is nonlinear. To solve the problem of the model inaccurateness and the influences on alignment accuracy caused by the linearization of the nonlinear model, the nonlinear model for initial alignment of large misalignment angle in SINS is established. To improve the accuracy of the initial alignment...
In this paper, we propose an initial alignment method for marine strap-down inertial navigation system (SINS) based on transformed cubature Kalman filter (TCKF) under large heading misalignment angle condition, which can alleviate the non-local sampling problem inherent in existing initial alignment method based on cubature Kalman filter (CKF). As can be seen from our simulation results, TCKF outperforms...
According to the existing problems in the WLAN fingerprint positioning technology and wireless signal propagation characteristics under indoor environment, this paper proposes a indoor location method with better rapidity and higher positioning accuracy. WLAN fingerprint positioning method is improved from three aspects in this article: first of all, through Kalman filtering, the data of signal fingerprints...
This paper analyzes the accuracy concerns of self-positioning of some unmanned ground vehicle that is undertaking simultaneous localization and mapping. The environment information description provided by vehicle sensor usually has strong geometric feature. Thus, the paper puts forward a method with geometric feature for simultaneous localization and mapping environment description. After analyzing...
Localization is one of the important topics for autonomous driving of unmanned ground vehicle(UGV). Most problems in localization are due to uncertainties in the modeling and sensors. Therefore, various filters method are developed to estimate the states with noise. Recently, particle filter is widely used because it can be applied to the system with nonlinear model and non-Gaussian noise. In this...
With the development of new technologies and changes in market demand, MEMS gyroscope is widely used, but the low accuracy, large drift and other defects limit their application in some areas. This paper presents a Kalman filter-based multi-sensor fusion algorithm to improve the positioning and tracking accuracy of MEMS devices. The technology of multi-sensor information fusion has been put into use...
In order to obtain the accurate estimation of SOC (State of Charge) and predicted lithium battery SOH (State of Healthy), this article is based upon the internal resistance of the battery model. By using UKF method, the estimation of SOC and SOH can be carried out in the nonlinear conditions. The UKF algorithm considers the internal resistance of the model parameters and SOC as the state parameters...
The online traffic flow prediction is an important part of the road-traffic management system. If the traffic flow prediction real time capability is not strong enough, the prediction outcomes will become uncertain. The adaptive particle filter algorithm suggested in this paper is based on confidence level. And this algorithm can adaptively adjust the number of the particles according to the state...
This study proposes a high precision selective harmonic compensation scheme for active power filters, which designed by using the basic theory of GPC. A generalized predictive control (GPC) strategy based on the transfer function model is adopted. The GPC can compensate the delay in detecting the harmonic and the better result of compensation for harmonic can be achieved. As Kalman filter can detect...
With the wide use of computer and the rapid development of network technology, the research in the emerging area of networked control systems (NCSs) has attracted considerable attention in the research community. The purpose of this survey is to provide a review of state-of-the-art of such research. We particularly discuss things as follows: event-driven sampling for energy and communication efficiency,...
The correction methods of water-level measurements and discharge measurements are a important kind of hydrodynamic model real-time correction methods. The existing hydrodynamic model real-time correction methods are almost designed based on Kalman filter. In which, an implicit condition is that the system noises are obeys a Gaussian distribution with known mean and variance. However, in practice,...
The application of machine vision in the industry has been a hot research. The technology of sorting different workpieces on a conveyor belt has a higher demand in industrial production. This paper applies machine vision technology to build a moving workpiece sorting system. The development of image processing and workpiece recognition algorithm is based on LabVIEW Vision Development Module. The grabbing...
Information transferring process in sensor network will appear delay, out-of-sequence even dropout. How to make full use of such information is extremely important to improve the state estimation accuracy. In this paper, it presents a new method, which can effectively improve the estimation accuracy. Firstly, a local pseudo-measurement model library is established to deal with the measurement with...
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