Methods and apparatus for measuring signal level and delay at multiple sensors

• US 6,430,295 B1
• Filed: 07/11/1997
• Issued: 08/06/2002
• Est. Priority Date: 07/11/1997
• Status: Expired due to Fees

• Current Assignee: Telefonaktiebolaget LM Ericsson
• Original Assignee: Telefonaktiebolaget LM Ericsson
• Inventors: Händel, Peter, Rasmusson, Jim
• Primary Examiner(s): Mei, Xu
• Application Number:
  US08/890,768
• Time in Patent Office: 1,852 Days
• Field of Search: 381/94.7, 381/103, 381/94.1, 381/73.1, 381/66, 381/91, 381/92, 381/122, 381/71.1, 381/71.11, 708/322
• US Class Current: 381/94.7
• CPC Class Codes: G10K 11/345 using energy switching from one active element to another
• CPC Class Codes: H04M 9/08 Two-way loud-speaking telephone systems with means for conditioning the signal, e.g. for suppressing echoes for one or both directions of traffic

Abstract

Methods and apparatus for automatic gain and time delay computations between multiple sensors. In exemplary embodiments, one sensor is treated as a reference sensor with respect to a measured signal quantity which is assumed to be a narrowband process. The relative gain and relative time delay in the additional sensors with respect to the same measured quantity are then automatically calculated based on an adaptive filtering algorithm. Advantageously, the disclosed embodiments are implemented using standard digital signal processing components.

Claims

1. A signal processing device, comprising:

a first signal sensor;

a first filter having an input coupled to an output of said first sensor;

a second signal sensor;

a second filter having an input coupled to an output of said second sensor and having an adjustable filtering characteristic;

a summing device having a first input coupled to an output of said first filter and a second input coupled to an output of said second filter, wherein the adjustable filtering characteristic of said second filter is adjusted in dependence upon an output of said summing device to cause the second filter output to emulate the first filter output; and

a processor for computing an estimate of at least one parameter indicating a relationship between said first and second sensors, wherein the estimate is computed as a function of a filtering characteristic of said first filter and as a function of the adjustable filtering characteristic of said second filter, and wherein the estimate includes estimates of a relative time delay and a relative scale factor between said first and second sensors with respect to a signal source.

2. A signal processing device according to claim 1, wherein said first filter, said second filter, said summing device and said processor are implemented using a digital signal processor (DSP) integrated circuit (IC).

3. A signal processing device according to claim 1, wherein said first filter, said second filter, said summing device and said processor are implemented using an application specific integrated circuit (ASIC).

4. A signal processing device according to claim 1, wherein said signal processing device is a telephone and wherein said first and second sensors are microphones.

5. A signal processing device according to claim 1, wherein said signal processing device is a radio transceiver and wherein said first and second sensors are antenna elements.

6. A signal processing device according to claim 1, wherein said first filter is a finite impulse response (FIR) filter having a fixed filtering characteristic.

7. A signal processing device according to claim 1, wherein the filtering characteristic of said first filter includes at least one passband providing unity gain and zero phase delay at a center frequency of the passband.

8. A signal processing device according to claim 7, wherein the filtering characteristic of the first filter includes a passband corresponding to the 300-600 Hz frequency band.

9. A signal processing device according to claim 1, wherein the filtering characteristic of said first filter includes coefficients which are set to minimize a noise gain of said first filter.

10. A signal processing device according to claim 1, wherein the filtering characteristic of said first filter includes coefficients which are adjusted to optimize a signal-to-noise ratio of said first filter.

11. A signal processing device according to claim 1, wherein the adjustable filtering characteristic of said second filter is adjusted using a Normalized Least Mean Squares (NLMS) algorithm.

12. A signal processing device according to claim 1, wherein the adjustable filtering characteristic of said second filter is adjusted using a Least Mean Squares (LMS) algorithm.

13. A signal processing device according to claim 1, wherein the adjustable filtering characteristic of said second filter is adjusted using a Recursive Least Squares (RLS) algorithm.

14. A signal processing device according to claim 1, further comprising a beamformer for shaping a beam pattern provided by said first and second sensors in dependence upon the estimates of the relative time delay and the relative scale factor between said first and second sensors.

15. A signal processing device according to claim 14, wherein the beam pattern includes a spacial beam aimed toward a particular signal source.

16. A signal processing device according to claim 14, wherein the beam pattern includes a spacial notch aimed against a particular signal source.

17. A signal processing device according to claim 1, wherein said processor selects a signal detected by a particular one of said first and second sensors for transmission in dependence upon the estimates of the relative time delay and the relative scale factor between said first and second sensors.

18. A signal processing device according to claim 1, further comprising at least one additional sensor and at least one additional filter having an adjustable filtering characteristic,

wherein the adjustable filtering characteristic of said additional filter is adjusted in dependence upon a difference between the output of said first filter and an output of said additional filter, and

wherein said processor computes an estimate of at least one parameter relating to said first sensor and said additional sensor in dependence upon the filtering characteristic of said first filter and the adjustable filtering characteristic of said additional filter.

19. A signal processing device according to claim 18, wherein said processor computes estimates of a relative time delay and a relative scale factor between said first sensor and said additional sensor with respect to a signal source.

20. A signal processing device according to claim 1, further comprising an activity detector for detecting when a signal source of interest is active, wherein said processor sets the estimates of the relative time delay and the relative scale factor to predetermined values when said activity detector indicates that no signal source of interest is active.

21. A signal processing device according to claim 20, wherein said processor sets the estimate of the relative time delay to zero and the estimate of the scale factor to one when said activity detector indicates that no signal source of interest is active.

22. A signal processing device according to claim 1, further comprising a fixed-delay block positioned in a signal flow path corresponding to said first sensor.

23. A signal processing device according to claim 1,

wherein filtering characteristics of said first and second filters each include a number L of filtering coefficients,

wherein the filtering characteristic of said first filter includes a number m of passbands, each passband l, l ε

(1,m), having a center frequency ω

_l, and

wherein an estimate {circumflex over (D)}_k of a relative time delay D between said first and second sensors and an estimate Ŝ

_k of a relative scale factor S between said first and second sensors, at a time instant k, are computed based upon the adjustable filtering characteristic ĉ

(k) of said second filter, a matrix L, and a prediction vector p(D), as;

${\hat{S}}_k=\frac{\sqrt{{\left(L<br><br>\hat{c}<br><br>\left(k\right)\right)}^T<br><br>L<br><br>\hat{c}<br><br>\left(k\right)}}{m}$${\hat{D}}_k=\underset{D}{\mathrm{argmin}}<br><br>{<br><br>L<br><br>\hat{c}<br><br>\left(k\right)-{\hat{S}}_k<br><br>p<br><br>\left(-D\right)<br><br>}^2$

where the matrix L and the prediction vector p(D) are computed as;

$L=\left(\begin{array}{ccc}\cos <br><br>\text{\hspace{1em}<br><br>}<br><br>{\mathrm{\omega <br><br>}}_1& \mathrm{\cdots <br><br>}& \cos <br><br>\left(L+1\right)<br><br>{\mathrm{\omega <br><br>}}_1\\ \mathrm{⋮<br><br>}& \text{\hspace{1em}<br><br>}& \mathrm{⋮<br><br>}\\ \cos <br><br>\text{\hspace{1em}<br><br>}<br><br>{\mathrm{\omega <br><br>}}_m& \mathrm{\cdots <br><br>}& \cos <br><br>\left(L+1\right)<br><br>{\mathrm{\omega <br><br>}}_m\\ \sin <br><br>\text{\hspace{1em}<br><br>}<br><br>{\mathrm{\omega <br><br>}}_1& \mathrm{\cdots <br><br>}& \sin <br><br>\left(L+1\right)<br><br>{\mathrm{\omega <br><br>}}_1\\ \mathrm{⋮<br><br>}& \text{\hspace{1em}<br><br>}& \mathrm{⋮<br><br>}\\ \sin <br><br>\text{\hspace{1em}<br><br>}<br><br>{\mathrm{\omega <br><br>}}_m& \mathrm{\cdots <br><br>}& \sin <br><br>\left(L+1\right)<br><br>{\mathrm{\omega <br><br>}}_m\end{array}\right)$$p<br><br>\left(D\right)=\left(\begin{array}{c}\cos <br><br>\left(1-D\right)<br><br>{\mathrm{\omega <br><br>}}_1\\ \mathrm{⋮<br><br>}\\ \cos <br><br>\left(1-D\right)<br><br>{\mathrm{\omega <br><br>}}_m\\ \sin <br><br>\left(1-D\right)<br><br>{\mathrm{\omega <br><br>}}_1\\ \mathrm{⋮<br><br>}\\ \sin <br><br>\left(1-D\right)<br><br>{\mathrm{\omega <br><br>}}_m\end{array}\right).$

24. A method for processing signals, comprising the steps of:

detecting a first signal using a first signal sensor;

filtering the first signal using a first filter to provide a first filtered signal;

detecting a second signal using a second signal sensor;

filtering the second signal using a second filter to provide a second filtered signal;

computing a difference between the first filtered signal and the second filtered signal;

adjusting a filtering characteristic of the second filter in dependence upon the difference obtained in said step of computing to cause the second filter output to emulate the first filter output; and

estimating at least one parameter as a function of a filtering characteristic of said first filter and as a function of the filtering characteristic of said second filter, the at least one parameter including estimates of a relative time delay and a relative scale factor between the first and second sensors with respect to a signal source.

25. A method according to claim 24, wherein the filtering characteristic of the first filter includes at least one passband providing unity gain and zero phase delay at a center frequency of the passband.

26. A method according to claim 24, wherein the filtering characteristic of said second filter is adjusted using a Normalized Least Mean Squares (NLMS) algorithm.

27. A method according to claim 24, further comprising a step of shaping a beam pattern provided by said first and second sensors in dependence upon the relative time delay and the relative scale factor obtained as a result of said step of estimating.

28. A method according to claim 24, further comprising a step of selecting and transmitting a signal detected by a particular one of said first and second sensors in dependence upon the relative time delay and the relative scale factor obtained as a result of said step of estimating.

29. A method according to claim 24, further comprising the steps of detecting whether a signal source of interest is active and setting relative time delay and scale factor estimates to predetermined values when said step of detecting indicates that no source of interest is active.

30. A method according to claim 24, wherein the filtering characteristic of the first filter includes a passband corresponding to the 300-600 Hz frequency band.