Title :
Kalman Filter´s Application in Denoising of Power Spectrum Estimate in AR Process
Author :
Wang, Liqi ; Wang, Mingyi ; Zhang, Liyong ; Guo, Jianying ; Zhu, Xiuchao
Author_Institution :
Sch. of Meas. & Commun., Harbin Univ. of Sci. & Technol., Harbin
Abstract :
AR process´s denoising methods are discussed in this paper whose system response being perceived under the additive white noise, within the two discussed methods, the formula analysis method is proved less satisfactory through experiments results whereas in Kalman Filter method both the system impulses of AR process and noise contaminated system response are regarded as inputs and white noise only as parameters involved in computation. Through above process computer simulation shows that influences of noise chaotic factors to the computation results can be reduced.
Keywords :
Kalman filters; autoregressive processes; estimation theory; signal denoising; white noise; Kalman filter application; additive white noise; auto regressive process; formula analysis method; power spectrum estimate denoising; Additive white noise; Application software; Frequency; Kalman filters; Noise measurement; Noise reduction; Pollution measurement; Power measurement; Signal processing algorithms; White noise; Kalman Filter; denoising; power spectrum estimation;
Conference_Titel :
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3505-0
DOI :
10.1109/IITA.Workshops.2008.195