Optimal ratio estimator for multisensor systems

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system

Reexamination Certificate

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C702S077000, C702S079000, C702S176000, C702S179000

Reexamination Certificate

active

06577966

ABSTRACT:

The present invention relates generally to an optimal ratio estimator and, more particularly, to an optimal ratio estimator for multi-sensor systems and to applications thereof to blind source separation.
Miniaturized sensors and increased computational power and memory storage in today's digital signal processors make it possible to implement and apply advanced DSP techniques to problems of source separation and noise reduction for small electronic devices such as, for example, speech recognition front ends, personal digital assistants with voice input, mobile phones, smart alarms, etc.). Such devices can take advantage of two or more microphone arrays, and are aimed at improving the directionality of the signal input system, or simply of source separation, while not affecting the quality of the sound, particularly if the sound of interest is speech. In recent years, this domain has been the focus, at the low end of applications, for Blind Source Separation (BSS) and Independent Component Analysis (ICA) Techniques. See, for example, Christian Jutten and Jeanny Herault. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture.
Signal Processing,
24(1):1-10; 1991; Christian Jutten Pierre Comon and Jeanny Herault. Blind separation of sources, part ii: Problems statement.
Signal Processing,
24(1):11-20, 1991; Ehud Weinstein, Meir Feder, and Alan Oppenheim. Multi-channel signal separation by decorrelation. IEEE
Trans. On Speech and Audio Processing,
1(4):405-413, 1993; and Pierre Comon. Independent component analysis, a new concept?
Signal Processing;
36(3):287 314, 1994.
Nevertheless, traditionally array processing and beamforming signal processing techniques were principally concerned with the formation of steered beams for an array of sensors in sonar and radar systems. See, for example, Hamid Krim and Mats Viberg. Two decade of array signal processing research. IEEE
Signal Processing Magazine,
13(4), 1996; and V. Van Veen and Kevin M. Buckley. Beamforming: A versatile approach to spatial filtering. IEEE ASSP Magazine, 5(2), 1988.
It is herein recognized that the ratio of the short time Fourier transform (STFT) coefficients of signals received at two sensors can factor out the role of the power spectrum of emitting sources, under an assumption called disjoint orthogonality. Thus, it can reveal parameters specific to the mixing scenario and serve as a basis for channel estimation techniques.
A signal processing technique is disclosed that can be effectively used for source separation, signal enhancement, and noise reduction when using a twin microphone system. The class of stochastic signals for which ratio-estimates can be computed from histograms is defined. This class fits real-world signals of interest such as voice signals. Theoretical computation in closed form of the optimal estimator for this class of signals is disclosed. Two practical implementation solutions are disclosed as is a practical solution to exploit an echoic environment model. Furthermore, two novel techniques for signal demixing are presented. The application of the optimal estimator and the suboptimal estimator to the case of more than two channels is disclosed.


REFERENCES:
patent: 4983906 (1991-01-01), Hiller
patent: 5808895 (1998-09-01), Ibrahim et al.
patent: 5995914 (1999-11-01), Cabot
patent: 6026418 (2000-02-01), Duncan, Jr.
patent: 6371923 (2002-04-01), Roteliuk et al.

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