Noise and interference reduction in digitized signals

• US 20060035593A1
• Filed: 08/12/2004
• Published: 02/16/2006
• Est. Priority Date: 08/12/2004
• Status: Abandoned Application

• Current Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Original Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Inventors: Leeds, David S.
• Application Number:
  US10/916,806
• Publication Number:
  US 20060035593A1
• Time in Patent Office: Days
• US Class Current: 455/67.130
• CPC Class Codes: G10L 19/265 Pre-filtering, e.g. high frequency emphasis prior to encoding
• CPC Class Codes: G10L 21/02 Speech enhancement, e.g. noise reduction or echo cancellation reducing echo effects in line transmission systems H04B3/20; echo suppression in hands-free telephones H04M9/08
• CPC Class Codes: G10L 25/18 the extracted parameters being spectral information of each sub-band

Abstract

A method (700, 800, 900) and apparatus (1000, 1100) increase a signal quality by analyzing an input signal and output signals from adaptive filters (410, 510, 512, 514) associated with predetermined signal plus noise plus interference classifications. An actual signal plus noise plus interference classification of the input signal is determined and one of the output signals or the input signal is selected based on a favorable Signal to Noise Ratio or a Signal to Interference plus Noise Ratio. The output signals from the adaptive filters are weighted based on analysis such as statistical analysis (310) including quantified auto-regressive analysis, Eigenvalue spread analysis, correlation analysis, feedback analysis, and covariance analysis. The predetermined classifications include various combinations of characteristics associated with the signal and interference components. The adaptive filters include multi-band and single band Adaptive Noise Canceling filters (312, 314), and multi-band and single band Adaptive Line Enhancing filters (316, 318).

Claims

1. A method for increasing a signal quality, the method comprising:

analyzing an input signal and a plurality of output signals output from a plurality of adaptive filters into which the input signal is input, the plurality of adaptive filters associated with a plurality of predetermined classifications associated with the signal quality, the analyzing to determine an actual classification of the input signal; and

selecting one of;

one of the plurality of output signals, and the input signal based on the analyzing to provide a selected one which results in a value of the signal quality associated with an output signal generated based on the analyzing and the selecting.

2. A method in accordance with claim 1, wherein the signal quality includes one of a Signal to Noise Ratio (SNR), and a Signal to Interference plus Noise Ratio (SINR).

3. A method in accordance with claim 1, wherein the predetermined classifications include a signal plus interference plus noise classification.

4. A method in accordance with claim 1, wherein the analyzing includes weighting the plurality of output signals from the plurality of adaptive filters and the selecting the one is based on the weighting.

5. A method in accordance with claim 1, wherein the selecting includes selecting another one of:

one the plurality of output signals, and the input signal different from the selected one, which when combined with the selected one results in a value of the signal quality associated with an output signal generated based on the analyzing and the selecting.

6. A method in accordance with claim 5, wherein the analyzing includes weighting the plurality of output signals from the plurality of adaptive filters and the selecting the one and the selecting the another one are based on the weighting.

7. A method in accordance with claim 1, wherein the input signal includes a signal component and an interference component, and wherein the predetermined classifications include:

the signal component includes mixed periodic energy plus noise energy and the interference component includes mixed periodic energy plus noise energy;

the signal component includes mixed periodic energy plus noise energy and the interference component includes periodic energy;

the signal component includes mixed periodic energy plus noise energy and the interference component includes noise energy;

the signal component includes periodic energy and the interference component includes noise energy.

8. A method in accordance with claim 1, wherein the analyzing includes analyzing using statistical analysis.

9. A method in accordance with claim 1, wherein the analyzing includes analyzing using one or more of the following:

quantified auto-regressive analysis, Eigenvalue spread analysis, correlation analysis, and covariance analysis.

10. A method for processing an input signal to a vocoder to increase a signal quality, the method comprising:

establishing a plurality of adaptive filters configured to adapt to a plurality of predetermined classifications associated with the signal quality;

determining an actual classification of the input signal; and

selecting at least one of a plurality of signals output from the plurality of adaptive filters based on the actual classification to obtain a value of the signal quality.

11. A method in accordance with claim 10, wherein the signal quality includes one of:

a Signal to Noise Ratio (SNR) and a Signal to Interference plus Noise Ratio (SINR)

12. A method in accordance with claim 10, wherein the input signal includes a signal component and an interference component, and wherein the predetermined classifications include:

the signal component includes mixed periodic energy plus noise energy and the interference component includes mixed periodic energy plus noise energy;

the signal component includes mixed periodic energy plus noise energy and the interference component includes periodic energy;

the signal component includes mixed periodic energy plus noise energy and the interference component includes noise energy;

the signal component includes periodic energy and the interference component includes noise energy.

13. A method for processing an input signal to a vocoder to increase a signal quality, the method comprising:

inputting the input signal to a plurality of adaptive filters associated with a plurality of predetermined classifications associated with the signal quality;

analyzing the input signal and a plurality of signals output from the plurality of adaptive filters to determine an actual classification of the input signal and the plurality of signals output from the plurality of adaptive filters; and

selecting one of;

one of the plurality of output signals, and the input signal which results in a value of the signal quality based on the actual classification.

14. A method in accordance with claim 13, wherein the input signal includes a signal component and an interference component, and wherein the predetermined classifications include:

the signal component includes mixed periodic energy plus noise energy and the interference component includes mixed periodic energy plus noise energy;

the signal component includes mixed periodic energy plus noise energy and the interference component includes periodic energy;

the signal component includes mixed periodic energy plus noise energy and the interference component includes noise energy;

the signal component includes periodic energy and the interference component includes noise energy.

15. A method in accordance with claim 13, wherein the analyzing includes analyzing using statistical analysis.

16. A method in accordance with claim 13, wherein the analyzing includes analyzing using one or more of the following:

quantified auto-regressive analysis, Eigenvalue spread analysis, correlation analysis, and covariance analysis.

17. An apparatus for increasing a signal quality in a communication unit, the apparatus comprising:

a memory storing samples of an input signal;

a plurality of adaptive filters each configured with a possible classification for the input signal, each of the plurality of adaptive filters processing the input signal and generating a respective output signal; and

a processor coupled to the memory, the processor configured to;

determine an actual classification of the input signal;

compare the actual classification with the possible classification for the input signal; and

selecting the respective output signal of one of the plurality of adaptive filters if the actual classification matches the possible classification.

18. An apparatus in accordance with claim 17, wherein the input signal includes a signal component and an interference component, and wherein the possible classifications include:

the signal component includes mixed periodic energy plus noise energy and the interference component includes mixed periodic energy plus noise energy;

the signal component includes mixed periodic energy plus noise energy and the interference component includes periodic energy;

the signal component includes mixed periodic energy plus noise energy and the interference component includes noise energy;

the signal component includes periodic energy and the interference component includes noise energy.

19. An apparatus in accordance with claim 17, wherein the plurality of adaptive filters include an Adaptive Noise Canceling filter (ANC), and an Adaptive Line Enhancing filter (ALE).

20. An apparatus in accordance with claim 17, wherein the plurality of adaptive filters include a single band adaptive filter and a multi-band adaptive filter.

21. An apparatus in accordance with claim 17, wherein the plurality of adaptive filters includes a single band Adaptive Noise Canceling filter (ANC), a multi-band ANC filter, a single band Adaptive Line Enhancing filter (ALE), and a multi-band ALE filter.