A PCA-Based Kalman Estimation Approach for System with Colored Measurement Noise
عنوان مقاله: A PCA-Based Kalman Estimation Approach for System with Colored Measurement Noise
شناسه ملی مقاله: ICEE20_405
منتشر شده در بیستمین کنفرانس مهندسی برق ایران در سال 1391
شناسه ملی مقاله: ICEE20_405
منتشر شده در بیستمین کنفرانس مهندسی برق ایران در سال 1391
مشخصات نویسندگان مقاله:
Mohammad Afshari - Dept. Of Electrical and Computer Eng., Isfahan University of Technology
Ahmadreza Tavasoli
Jafar Ghaisari
خلاصه مقاله:
Mohammad Afshari - Dept. Of Electrical and Computer Eng., Isfahan University of Technology
Ahmadreza Tavasoli
Jafar Ghaisari
In this article, principal component analysis (PCA) is applied to improve Kalman state estimator performance in the presence of colored measurement noise without extending thestate estimator dimension. Unlike the common methods the proposed PCA-based Kalman state estimator doesn’t use theinformation of noise dynamics. First, measurements of the Sensors are entered to the PCA block. The new measurementdata and the previous ones, stored in PCA buffer, merged and processed. The PCA output will be noiseless data that increase the accuracy of the Kalman state estimator. An illustrativeexample is simulated for comparisons of standard Kalman estimator, state augmented Kalman estimator and the PCA basedKalman estimator. Finally the simulations demonstrate the significant improvement in accuracy and performance of state estimation using the proposed method
کلمات کلیدی: State Estimation; Kalman State Estimator; Principal component Analysis
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/154617/