Presentation 1995/12/15
A Study of Signal Detection under Low SNR Condition Using Multi-Variable AR Model and DFT
Chiharu YAMANO, Kiyohito TOKUDA,
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Abstract(in English) This paper analyzes signal detection performances under low SNR (Signal-to-Noise power Ratio) condition using multi-variable auto-regressive (MV-AR) model and DFT (Discrete Fourier Transform). The DFT power spectral function primary depends on SNR per a channel, maximum time lag of correlation function and the number of sensors. The MV-AR model power spectral function also depends on SNR per a channel, model order and the number of sensors. This paper clarifies that the improvements of the signal detection performance are achieved by the increasing the number of both model order and sensors under the low SNR conditions.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) signal detection / multi-variable spectral estimation / multi-variable AR model / DFT
Paper # DSP95-134,SST95-108
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Conference Information
Committee DSP
Conference Date 1995/12/15(1days)
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Registration To Digital Signal Processing (DSP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Study of Signal Detection under Low SNR Condition Using Multi-Variable AR Model and DFT
Sub Title (in English)
Keyword(1) signal detection
Keyword(2) multi-variable spectral estimation
Keyword(3) multi-variable AR model
Keyword(4) DFT
1st Author's Name Chiharu YAMANO
1st Author's Affiliation Electronic & Communication Systems Laboratory, Research & Development Group, Oki Electric Industry Co., Ltd.()
2nd Author's Name Kiyohito TOKUDA
2nd Author's Affiliation Electronic & Communication Systems Laboratory, Research & Development Group, Oki Electric Industry Co., Ltd.
Date 1995/12/15
Paper # DSP95-134,SST95-108
Volume (vol) vol.95
Number (no) 417
Page pp.pp.-
#Pages 6
Date of Issue