Multi-Sensor Distributed Fusion Filter for Discrete Stochastic Multi-Delayed Systems with Correlated Noise

نویسندگان

  • Shuli Sun
  • Nan Lv
چکیده

This paper is concerned with the distributed fusion estimation problem for discrete-time linear stochastic multi-delayed systems with multiple sensors and correlated noise. Firstly, a new optimal filter in the least mean square sense is presented for discrete stochastic multi-delayed systems with a single sensor, where the white noise filter is used to obtain the optimal state estimate. Then, a distributed optimal scalarweighted fusion filter is given for discrete-time linear stochastic multi-delayed systems with multiple sensors. A recursive formula for the estimation error cross-covariance matrix between any two local optimal estimates is derived. Compared with the centralized filter, it has a little accuracy loss but better reliability. At last, a simulation example shows the effectiveness of the proposed algorithms.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Implementation of a Low- Cost Multi- IMU by Using Information Form of a Steady State Kalman Filter

In this paper, a homogenous multi-sensor fusion method is used to estimate the trueangular rate and acceleration with a combination of four low cost (< 10$) MEMS Inertial MeasurementUnits (IMU). An information form of steady state Kalman filter is designed to fuse the output of four lowaccuracy sensors to reduce the noise effect by the square root of the number of sensors. A hardware isimplemen...

متن کامل

Model-based Approach for Multi-sensor Fault Identification in Power Plant Gas Turbines

In this paper, ‎the multi-sensor fault diagnosis in the exhaust temperature sensors of a V94.2 heavy duty gas turbine is presented‎. ‎A Laguerre network-based fuzzy modeling approach is presented to predict the output temperature of the gas turbine for sensor fault diagnosis‎. Due to the nonlinear dynamics of the gas turbine, in these models the Laguerre filter parts are related to the linear d...

متن کامل

Distributed Fusion Filter for Multi-rate Sampling Stochastic Singular Systems with Multiplicative Noises

The distributed fusion filtering problem is studied for multi-rate sampling stochastic singular linear systems with multiple sensors and stochastic multiplicative noises. The system is described at the highest sampling rate and different sensors may have different lower sampling rates. The white noise in measurement matrix is introduced to describe the stochastic disturbance. Firstly, based on ...

متن کامل

Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks

The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced using considering the focus measurement in the spatial domain. However, the multi-focus image ...

متن کامل

Measurement Feedback Self-Tuning Weighted Measurement Fusion Kalman Filter for Systems with Correlated Noises

For the linear discrete stochastic systems with multiple sensors and unknown noise statistics, an online estimators of the noise variances and cross-covariances are designed by using measurement feedback, full-rank decomposition, and weighted least squares theory. Further, a self-tuning weighted measurement fusion Kalman filter is presented. The Fadeeva formula is used to establish ARMA innovat...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008