Gerschgorin radii based source number detection for closely spaced signals

Jar-Ferr Yang, Hsien Tsai Wu

Research output: Contribution to journalConference article

7 Citations (Scopus)

Abstract

We first analyze the resolution performance of the Gerschgorin radii based source number detector proposed in [1] for independent closely-spaced plane waves. Based upon the analysis, we can easily verify the resolution threshold of the Gerschgorin radii based algorithm. For improvement of the detection performance, we then further propose a weighted Gerschgorin radii algorithm. With closed-form expressions and simulations, we find that the analyzed performances in terms of the number of sensors, the relative angular separation of emitters, and the signal-to-noise ratios can properly characterize their behaviors for source number detection.

Original languageEnglish
Pages (from-to)3053-3056
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume6
Publication statusPublished - 1996 Jan 1
EventProceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) - Atlanta, GA, USA
Duration: 1996 May 71996 May 10

Fingerprint

Signal to noise ratio
Detectors
Sensors

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

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Gerschgorin radii based source number detection for closely spaced signals. / Yang, Jar-Ferr; Wu, Hsien Tsai.

In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Vol. 6, 01.01.1996, p. 3053-3056.

Research output: Contribution to journalConference article

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AB - We first analyze the resolution performance of the Gerschgorin radii based source number detector proposed in [1] for independent closely-spaced plane waves. Based upon the analysis, we can easily verify the resolution threshold of the Gerschgorin radii based algorithm. For improvement of the detection performance, we then further propose a weighted Gerschgorin radii algorithm. With closed-form expressions and simulations, we find that the analyzed performances in terms of the number of sensors, the relative angular separation of emitters, and the signal-to-noise ratios can properly characterize their behaviors for source number detection.

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