Signal processing apparatus and method

• US 6,999,541 B1
• Filed: 11/12/1999
• Issued: 02/14/2006
• 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): Tran, Khai
• Assistant Examiner(s): Lugo, David B.
• Application Number:
  US09/831,346
• Time in Patent Office: 2,286 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: 375/350
• 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 is disclosed comprising the steps of sampling and digitally converting the received signals and processing the digitally converted signals to provide an output signal, the processing including filtering the signals using a first adaptive filter arranged to enhance a target signal of the digitally converted signals and a second adaptive filter arranged to suppress an unwanted signal of the digitally converted signals and processing the filtered signals in the frequency domain to suppress the unwanted signal further.

Claims

1. A method of processing signals received from an array of sensors 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;

determining a direction of arrival of the target signal; and

treating a signal of the received signals as an unwanted signal if the signal has not impinged on the array from within a selected angular range.

2. A method as claimed in claim 1 further comprising:

determining a signal energy from the received signals and determining a noise energy from the signal energy;

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.

3. A method as claimed in claim 2 further comprising determining if a target signal is present by comparing the signal energy to a signal threshold.

4. A method as claimed in claim 3 further comprising determining the signal threshold from the noise energy and updating the signal threshold when the signal energy is below the noise threshold.

5. A method as claimed in claim 3 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.

6. A method as claimed in claim 2 wherein the noise threshold T_n1 is determined in accordance with:

T_n1=δ

₁E_n

Where δ

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

7. A method as claimed in claim 1 further comprising:

processing the signals from two space sensors of the array with a 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.

8. A method as claimed in claim 7 wherein the reverberation measure C_rv is calculated in accordance with $C_{\mathrm{rv}}=\frac{W_{\mathrm{td}}^T}{}$

Wsu

Wtd

⁢



Wsu

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.

9. A method as claimed in claim 7 further comprising treating the signal as an unwanted signal when the reverberation measure indicates a degree of reverberation in excess of a selected value.

10. A method as claimed in claim 1 wherein the first adaptive filter has a plurality of channels, comprising a plurality of difference signal channels, the plurality of channels receiving as input, the digitized signals and providing as output, a sum and at least one difference signal, the difference signal channels including filter elements having corresponding filter weights.

11. A method as claimed in claim 10 further comprising calculating a ratio of the energy in the sum and difference channels.

12. A method as claimed in claim 11 further comprising the step of treating the signal as including a said target signal if the ratio indicates that the energy in the sum channel is greater than the energy in the difference channels by more than a selected factor.

13. A method as claimed in claim 12 further comprising treating the signal as including a said target signal only if the signal energy exceeds a threshold.

14. A method as claimed in claim 1 further comprising controlling operation of the second filter to perform adaptive filtering only when said target is deemed not to be present.

15. A method as claimed in claim 1 wherein the second adaptive filter has a plurality of channels, comprising a plurality of difference signal channels, the plurality of channels receiving input signals from the first adaptive filter and providing as output, a sum signal received from the first adaptive filter, an error signal and a plurality of difference signals, the difference signal channels including further filter elements having corresponding further filter weights.

16. A method as claimed in claim 15 further comprising scaling the further filter weights when the norms of the further filter weights exceed a threshold.

17. A method as claimed in claim 15 further comprising combining the sum signal and the error signal to form a single signal S(t) of the form:

S(t)=W₁S_c(t)+W₂e_c(t)

where S_c(t) is the sum signal at time t, e_c(t) is the error signal at time t and W_{1 and W2} are weight values.

18. A method as claimed in claim 17 further comprising combining the difference signals to form a single signal.

19. A method as claimed in claim 17 further comprising applying a Hanning window to the single signal.

20. A method as claimed in claim 1 further comprising transforming the filtered signals into two frequency domain signals, a desired signal S_f and an interference signal I_f, processing the transformed signals to provide a gain for the desired signal and transforming the gain modified desired signal back to the time domain to provide an output.

21. A method as claimed in claim 20 wherein the processing comprises forming spectra for the frequency domain signals.

22. A method as claimed in claim 21 wherein the spectra are modified spectra P_s, P_i of the desired signal and the interference signal of the form:

P_s=|Real(S_f)|+|Imag (S_f)|+F(S_f)*r_s

P_i=|Real(I_f)|+|Imag(I_f)|+F(I_f)*r_i

Where “

Real” and

“

Imag”

refer to taking the absolute values of the real and imaginary parts, r_s and r_i are scalars and F(S_f) and F(I_f) denotes a function of S_f and I_f respectively.

23. A method as claimed in claim 22 wherein the function is a power function.

24. A method as claimed in claim 23 wherein the spectra are of the form:

P_i=|Real(I_f)|+|Imag(I_f)|+(I_f*conj(I_f))*r_i

P_s=|Real(S_f)|+|Imag(S_f)|+(S_f*conj(S_f))*r_s

where “

Conj”

denotes the complex conjugate.

25. A method as claimed in claim 22 wherein the function is a multiplication function.

26. A method as claimed in claim 25 wherein the spectra are of the form:

P_s=|Real(S_f)|+|Imag(S_f)|+|Real(S_f)|*|Imag (S_f)|*r_s

P_i=|Real(I_f)|+|Imag(I_f)|+|Real(I_f)|*|Imag(I_f)|*r_i.

27. A method as claimed in claim 21 wherein the processing includes warping the signal and interference spectra into a Bark scale to form a corresponding signal and interference Bark spectra.

28. A method as claimed in claim 27 wherein the processing further includes calculating a system noise Bark spectrum.

29. A method as claimed in claim 28 further comprising combining the interference Bark spectrum and the system noise Bark spectrum to form a combined noise Bark spectrum.

30. A method as claimed in claim 29 wherein the combined noise Bark spectrum B_y is of the following form:

B_y=Ω

₁B_i+Ω

₂B_n

where Ω

₁ and Ω

₂ are weighting values B_i is the interference Bark spectrum and B_n is the system noise Bark spectrum.

31. A method as claimed in claim 21 further comprising calculating a signal to noise ratio from the spectra and deriving the gain from the signal to noise ratio.

32. A method as claimed in claim 31 further comprising modifying the signal to noise ratio with a scaling factor which gradually increases from a first values at onset of the signal, to a second value, wherein the scaling factor is reset to the first value after the signal is received.

33. A method as claimed in claim 32 wherein the scaling factor changes in a plurality of steps.

34. A method as claim 32 wherein the scaling factor changes exponentially.

35. A method of processing signals received from an array of sensors 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; and

determining a signal energy from the received signals and determining a noise energy from the signal energy;

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;

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

Where J=N/2; and

estimating the signal energy using th following equation;

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

where E_r is the signal energy.

36. A method of processing signals received from an array of sensors 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; and

determining a signal energy from the received signals and determining a noise energy from the signal energy;

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

E_n^K+1=E_n^K+(1−

α

)E_r^K+1

Where the superscript K is the block number and α

is an empirically chosen weight.