DocumentCode
2485231
Title
MVDR spectral estimation by spectral peak dichotomous search
Author
Peng, Yu ; Gao, Zhifeng ; Peng, Xiyuan
Author_Institution
Autom. Test & Control Inst., Harbin Inst. of Technol., Harbin, China
fYear
2012
fDate
13-16 May 2012
Firstpage
1692
Lastpage
1696
Abstract
Canonical correlation analysis (CCA) and minimum variance distortionless response (MVDR) are typical nonparametric spectral estimation methods based on matched filterbank theory. To avoid the common signal mismatch problem, an algorithm combining CCA and MVDR is proposed for peak frequency modification. It consists of two stages: a coarse-peak search in CCA spectrum, and followed with a fine-peak search using dichotomous search strategy in MVDR spectrum. Furthermore the new algorithm is extended to the magnitude squared coherence (MSC) spectral estimation. Simulations show that the peak frequency estimation accuracy is improved simply and efficiently, with only slight computation increased.
Keywords
frequency estimation; matched filters; search problems; CCA spectrum; MSC spectral estimation; MVDR; MVDR spectral estimation; canonical correlation analysis; dichotomous search strategy; fine-peak search; magnitude squared coherence spectral estimation; matched filterbank theory; minimum variance distortionless response; nonparametric spectral estimation methods; peak frequency estimation accuracy; peak frequency modification; signal mismatch problem avoidance; spectral peak dichotomous search; Accuracy; Band pass filters; Estimation; Filtering theory; Finite impulse response filter; Frequency estimation; Signal resolution; Spectral estimation; dichotomous search; parameter estimation; power spectrum;
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International
Conference_Location
Graz
ISSN
1091-5281
Print_ISBN
978-1-4577-1773-4
Type
conf
DOI
10.1109/I2MTC.2012.6229655
Filename
6229655
Link To Document