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Sensors 2016, 16(5), 637; doi:10.3390/s16050637

Performance Analysis of ICA in Sensor Array

College of Electronic Science and Engineering, National University of Defense Technology (NUDT), Changsha 410073, China
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Academic Editor: Vittorio M. N. Passaro
Received: 29 February 2016 / Revised: 28 April 2016 / Accepted: 28 April 2016 / Published: 5 May 2016
(This article belongs to the Section Physical Sensors)
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Abstract

As the best-known scheme in the field of Blind Source Separation (BSS), Independent Component Analysis (ICA) has been intensively used in various domains, including biomedical and acoustics applications, cooperative or non-cooperative communication, etc. While sensor arrays are involved in most of the applications, the influence on the performance of ICA of practical factors therein has not been sufficiently investigated yet. In this manuscript, the issue is researched by taking the typical antenna array as an illustrative example. Factors taken into consideration include the environment noise level, the properties of the array and that of the radiators. We analyze the analytic relationship between the noise variance, the source variance, the condition number of the mixing matrix and the optimal signal to interference-plus-noise ratio, as well as the relationship between the singularity of the mixing matrix and practical factors concerned. The situations where the mixing process turns (nearly) singular have been paid special attention to, since such circumstances are critical in applications. Results and conclusions obtained should be instructive when applying ICA algorithms on mixtures from sensor arrays. Moreover, an effective countermeasure against the cases of singular mixtures has been proposed, on the basis of previous analysis. Experiments validating the theoretical conclusions as well as the effectiveness of the proposed scheme have been included. View Full-Text
Keywords: blind source separation; independent component analysis; performance analysis; practical factors blind source separation; independent component analysis; performance analysis; practical factors
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MDPI and ACS Style

Cai, X.; Wang, X.; Huang, Z.; Wang, F. Performance Analysis of ICA in Sensor Array. Sensors 2016, 16, 637.

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