Time-varying techniques for multisensor signal detection

Kofi Ghartey, Antonia Papandreou-Suppappola, Douglas Cochran

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In source detection and localization, the presence of a common but unknown signal can be detected from several noisy sensor measurements using the generalized coherence (GC) estimate. We propose to improve the performance of the GC estimate for multisensor detection using noise-suppressed signal estimates obtained from time-varying techniques. If one of the sensors has a significantly higher signal-to-noise ratio (SNR) than the other sensors, then it could be preprocessed prior to the GC estimate to improve detection performance for the remaining, lower SNR sensors. We perform this processing by estimating time-varying signals of interest with nonlinear phase functions using two methods: (a) a modified matching pursuit decomposition (MMPD) algorithm whose dictionary is similar, in time-frequency structure, to the signal and (b) an instantaneous frequency (IF) estimation method using highly localized time-frequency representations. The MMPD can yield signal estimates with lower mean square errors than the IF estimation technique but at the expense of higher computational cost and memory requirements. Using simulations, we compare the performance of the GC estimate with the significantly improved performance of the GC estimate that employs the signal estimate from the high SNR sensor. For the two-sensor detection, the estimated signal is also used with a generalized likelihood ratio test statistic to further improve performance.

Original languageEnglish (US)
Pages (from-to)3353-3362
Number of pages10
JournalIEEE Transactions on Signal Processing
Volume54
Issue number9
DOIs
StatePublished - Sep 2006

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Signal detection
Sensors
Signal to noise ratio
Frequency estimation
Decomposition
Glossaries
Mean square error
Statistics
Data storage equipment
Processing
Costs

Keywords

  • Generalized coherence estimate
  • Instantaneous frequency (IF) estimation
  • Multisensor detection
  • Time-frequency representations

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing

Cite this

Time-varying techniques for multisensor signal detection. / Ghartey, Kofi; Papandreou-Suppappola, Antonia; Cochran, Douglas.

In: IEEE Transactions on Signal Processing, Vol. 54, No. 9, 09.2006, p. 3353-3362.

Research output: Contribution to journalArticle

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