Signal processing apparatus and method

• US 7,289,586 B2
• Filed: 12/05/2005
• Issued: 10/30/2007
• Est. Priority Date: 11/13/1998
• Status: Expired due to Term

• Current Assignee: Bitwave Pte Ltd.
• Original Assignee: Bitwave Pte Ltd.
• Inventors: Hui, Siew Kok
• Primary Examiner(s): Lugo; David B.
• Application Number:
  US11/293,183
• Publication Number:
  US 20060072693A1
• Time in Patent Office: 694 Days
• Field of Search: 375/346, 375/347, 375/349, 375/350, 367/119, 367/121, 381/71.8, 381/71.11, 381/94.7
• US Class Current: 375/349
• CPC Class Codes: G10K 11/178 by electro-acoustically regenerating the original acoustic waves in anti-phase

Abstract

A method of processing signals received from an array of sensors includes sampling and digitally converting the received signals. The digitally converted signals are processed to provide an output signal, the processing including filtering the signals using a first adaptive filter that enhances a target signal of the digitally converted signals and a second adaptive filter that suppresses an unwanted signal of the digitally converted signals, and processing the filtered signals in a frequency domain to further suppress the unwanted signal. The digitally converted signals are processed to determine a direction of arrival of the target signal, the processing including filtering the signals using a third adaptive filter.

Claims

1. A method of processing signals received from an array of sensors, the method comprising:

sampling and digitally converting the received signals;

processing the digitally converted signals to provide an output signal, the processing including filtering the signals using a first adaptive filter that enhances a target signal of the digitally converted signals and a second adaptive filter that suppresses an unwanted signal of the digitally converted signals, and processing the filtered signals in a frequency domain to further suppress the unwanted signal;

processing the digitally converted signals to determine a direction of arrival of the target signal, the processing including filtering the signals using a third adaptive filter; and

controlling the first adaptive filter to perform only when the target signal is present.

2. The method according to claim 1, further comprising:

determining a signal energy from the signals; and

determining a noise energy from the signal energy.

3. The method according to claim 2 wherein the signal energy is determined by buffering N/2 samples of the digitized signal into a shift register to form a signal vector of the following form:

$X_r=\left[\begin{array}{c}X<br><br>\left(0\right)\\ X<br><br>\left(1\right)\\ \mathrm{⋮<br><br>}\\ X<br><br>\left(J-1\right)\end{array}\right]$

where J=N/2; and

estimating the signal energy using the following equation;

$E_r=\frac{1}{\left(J-2\right)}<br><br>\underset{i=1}{\overset{J-2}{\sum <br><br>}}<br><br>{X<br><br>\left(i\right)}^2-X<br><br>\left(i+1\right)<br><br>X<br><br>\left(i-1\right)$

where E_r is the signal energy.

4. The method according to claim 2, wherein the noise energy is determined by measuring the signal energy E_r of blocks of the digitally converted signals and calculating the noise energy E_n in accordance with the following equation:

E_n^K+1=α

E_n^K+(1−

α

)E_r^K+1

where the superscript K is the block number and α

is an empirically chosen weight.

5. The method according to claim 2 further comprising:

determining a noise threshold from the noise energy; and

updating the noise energy and the noise threshold when the signal energy is below the noise threshold.

6. The method according to claim 5 further comprising determining when a target signal is present by comparing the signal energy to a signal threshold.

7. The method according to claim 6 further comprising:

determining the signal threshold from the noise energy; and

updating the signal threshold when the signal energy is below the noise threshold.

8. The method according to claim 5 wherein the noise threshold T_n1 is determined in accordance with the following equation:

T_n1=δ

₁E_n

where δ

₁ is an empirically chosen value and E_n is the noise energy.

9. The method as claimed in claim 6 wherein the signal threshold T_n2 is determined in accordance with:

T_n2=δ

₂E_n

where δ

₂ is an empirically chosen value and E_n is the noise energy.

10. The method according to claim 1, where the signals filtered by the third adaptive filter are from two spaced sensors of the array with a third adaptive filter to determine the direction of arrival.

11. The method as claimed in claim 1 further comprising treating the signal as an unwanted signal when the signal has not impinged on the array from within a selected angular range.

12. The method as claimed in claim 1 further comprising calculating a measure of the cross-correlation of signals from two spaced sensors of the array and treating the signal as an unwanted signal when the degree of cross correlation is less than a selected value.

13. The method as claimed in claim 1 further comprising:

processing the signals from two space sensors of the array with the third adaptive filter to determine the direction of arrival; and

calculating a measure of reverberation of the signal from filter weights of the first and third adaptive filters.

14. The method as claimed in claim 13 wherein the reverberation measure C_rv is calculated in accordance with

$C_{\mathrm{rv}}=\frac{W_{\mathrm{td}}^T}{}$

W su 

W td 

⁢



W su 

where T denotes the transpose of a vector, W_su is a filter coefficient of the first filter and W_td is a filter coefficient of the third filter.

15. The method as claimed in claim 13 further comprising treating the signal as an unwanted signal when the reverberation measure indicates a degree of reverberation in excess of a selected value.

16. The method of claim 1, wherein a spectrum of a Fourier transformed signal is calculated, said Fourier transformed signal comprising at least one of a Fourier transform component F(S) of a target signal and Fourier transform component F(I) of an unwanted signal, the method further comprising:

constructing spectrums P(S) and P(I) of at least one equivalent in accordance with the following equations;

P(S)=|Real(F(S))|+|Imag(F(S))|+G[F(S)]*R(S)

P(I)=|Real(F(I))|+|Imag(F(I))|+G[F(I)]*R(I)

where “

Real” and

“

Imag”

refer to absolute values of a real part and an imaginary part of the frequency domain equivalents F(S) and F(I), R(S) and R(I) are scalar adjustment factors, and G[F(S)] and G[F(I)] are functions of F(S) and F(I) respectively.