Pseudo-median cascaded canceller

US 6,904,444 B2
Filed: 04/12/2001
Issued: 06/07/2005
Est. Priority Date: 04/12/2001
Status: Expired due to Fees

First Claim

Patent Images

1. A signal processing building block for use in an adaptive signal processing system comprising:

a main input channel which receives a main input signal;

an auxiliary input channel which receives an auxiliary input signal; and

a processing mechanism that;

generates a complex adaptive weight, the complex adaptive weight including a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal, and a sample median value of an imaginary part of the ratio of a main input weight training data signal to an auxiliary input weight training data signal, and applies the computed complex adaptive weight to a function of the main input signal and the auxiliary input signal to generate an output signal.

View all claims

1 Assignment

Timeline View

Assignment View

0 Petitions

Accused Products

Abstract

An adaptive signal processing system utilizes a pseudo-median cascaded canceller to compute a set of complex adaptive weights and generate a filtered output signal. The system includes a plurality of building blocks arranged in a Gram-Schmidt cascaded canceller-type configuration for sequentially decorrelating input signals from each other to thereby yield a single filtered output signal. Each building block includes a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a local output channel which sends a local filtered output signal. Each building block generates a complex adaptive weight which is the sample median value of the real and imaginary parts of the ratio of local main input weight training data to local auxiliary input weight training data, and each building block generates a local output signal utilizing the complex adaptive weight. The effect of non-Gaussian noise contamination on the convergence MOE of the system is negligible. In addition, when desired signal components are included in weight training data they cause little loss of noise cancellation.

43 Citations

View as Search Results

22 Claims

1. A signal processing building block for use in an adaptive signal processing system comprising:
- a main input channel which receives a main input signal;
  
  an auxiliary input channel which receives an auxiliary input signal; and
  
  a processing mechanism that;
  
  generates a complex adaptive weight, the complex adaptive weight including a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal, and a sample median value of an imaginary part of the ratio of a main input weight training data signal to an auxiliary input weight training data signal, and applies the computed complex adaptive weight to a function of the main input signal and the auxiliary input signal to generate an output signal.

2. A signal processing building block for use in an adaptive signal processing system comprising:
- a main input channel which receives a main input signal;
  
  an auxiliary input channel which receives an auxiliary input signal; and
  
  a Processing mechanism that;
  
  generates a complex adaptive weight, and applies the computed complex adaptive weight to a function of the main input signal and the auxiliary input signal to generate an output signal, the complex adaptive weight comprising a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal.

3. A signal processing building block for use in an adaptive signal processing system comprising:
- a main input channel which receives a main input signal;
  
  an auxiliary input channel which receives an auxiliary input signal; and
  
  a processing mechanism that;
  
  generates a complex adaptive weight, and applies the computed complex adaptive weight to a function of the main input signal and the auxiliary input signal to generate an output signal, wherein the processing mechanism generates the complex adaptive weight, w_med, according to $w_{med} = \underset{k = 1 to K}{MED} [real (\frac{{z (k)}^{*}}{{x (k)}^{*}})] + j {\underset{k = 1 to K}{MED} [imag (\frac{{z (k)}^{*}}{{x (k)}^{*}})]}$ where K is the number of weight training data samples, z is the main input signal, j is a unit imaginary number, and x is the auxiliary input signal.
- View Dependent Claims (4)
- - 4. A signal processing building block as claimed in claim 3, wherein the processing mechanism generates the output signal, r, according to r=z−
    - w*_medx.

5. An adaptive signal processing system for receiving a plurality of input signals corresponding to a common target signal and for sequentially decorrelating the input signals to cancel the correlated noise components therefrom, the adaptive signal processing system comprising:
- a plurality of building blocks arranged in a cascaded configuration for sequentially decorrelating each of the input signals from each other of the input signals to thereby yield a single filtered output signal;
  
  wherein each building block includes;
  
  a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, anda processing mechanism that calculates a complex adaptive weight, and generates a local output signal, utilizing the complex adaptive weight, the complex adaptive weight comprising a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal, and a sample median value of an imaginary part of the ratio of the main input weight training data signal to the auxiliary input weight training data signal.
- View Dependent Claims (6)
- - 6. An adaptive signal processing system as in claim 5, wherein each building block supplies the local output signal to a local output channel.

7. An adaptive signal processing system for receiving a plurality of input signals corresponding to a common target signal and for sequentially decorrelating the input signals to cancel the correlated noise components therefrom, the adaptive signal processing system comprising:
- a plurality of building blocks arranged in a cascaded configuration for sequentially decorrelating each of the input signals from each other of the input signals to thereby yield a signal filtered output signal;
  
  wherein each building block includes;
  
  a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, anda processing mechanism that calculates a complex adaptive weight, and generates a local output signal, utilizing the complex adaptive weight, wherein each building block generates the complex adaptive weight, w_med, according to $w_{med} = \underset{k = 1 to K}{MED} [real (\frac{{z (k)}^{*}}{{x (k)}^{*}})] + j {\underset{k = 1 to K}{MED} [imag (\frac{{z (k)}^{*}}{{x (k)}^{*}})]}$ where K is the number of weight training data samples, z is the local main input signal, j is a unit imaginary number, and x is the local auxiliary input signal; and
  
  each building block generates the local output signal, r, according to
  r=z−
  
  w*_medx.

8. An adaptive signal processing method comprising:
- receiving a plurality of input signals corresponding to a common target signal;
  
  inputting the input signals into a plurality of building blocks arranged in a cascade configuration for sequentially decorrelating each of the input signals from each other of the input signals;
  
  generating a single filtered output signal;
  
  wherein each building block includes a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a processing mechanism that calculates a complex adaptive weight and generates a local output signal, utilizing the complex adaptive weight, the processing mechanism calculating the complex adaptive weight w_medby calculating a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal and calculating a sample median value of an imaginary part of the ratio of the main input weight training data signal to the auxiliary input weight training data signal.

9. An adaptive signal processing method comprising:
- receiving a plurality of input signals corresponding to a common target signal;
  
  inputting the input signals into a plurality of building blocks arranged in a cascade configuration for sequentially decorrelating each of the input signals from each other of the input signals;
  
  generating a single filtered output signal;
  
  wherein each building block includes a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a processing mechanism that generates a complex adaptive weight, and generates a local output signal, utilizing the complex adaptive weight, wherein said processing mechanism generates the complex adaptive weight w_medby calculating a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal.

10. An adaptive signal processing method comprising:
- receiving a plurality of input signals corresponding to a common target signal;
  
  inputting the input signals into a plurality of building blocks arranged in a cascade configuration for sequentially decorrelating each of the input signals from each other of the input signals;
  
  generating a single filtered output signal;
  
  wherein each building block includes a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a processing mechanism that calculates a complex adaptive weight, and generates a local output signal, utilizing the complex adaptive weight, wherein each building block calculates the complex adaptive weight w_medby calculating a sample median value of an imaginary part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal.

11. An adaptive signal processing method comprising:
- receiving a plurality of input signals corresponding to a common target signal;
  
  inputting the input signals into a plurality of building blocks arranged in a cascade configuration for sequentially decorrelating each of the input signals from each other of the input signals;
  
  generating a single filtered output signal;
  
  wherein each building block includes a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a processing mechanism that calculates a complex adaptive weight, and generates a local output signal, utilizing the complex adaptive weight, wherein each building block calculates the complex adaptive weight, w_med, according to $w_{med} = \underset{k = 1 to K}{MED} [real (\frac{{z (k)}^{*}}{{x (k)}^{*}})] + j {\underset{k = 1 to K}{MED} [imag (\frac{{z (k)}^{*}}{{x (k)}^{*}})]}$ where K is the number of weight training data samples, z is the local main input signal, j is the unit imaginary number, and x is the local auxiliary input signal.
- View Dependent Claims (12)
- - 12. An adaptive signal processing method as claimed in claim 11, wherein each building block generates the local output signal, r, by solving the equation:
    - r=z−
      
      w_medx.

13. An adaptive signal processing system comprising:
- means for receiving a plurality of input signals corresponding to a same target signal;
  
  means for inputting the input signals into a plurality of building blocks arranged in a cascade configuration for sequentially decorrelating each of the input signals from each other of the input signals;
  
  means for generating a single filtered output signal;
  
  wherein each building block includes a means for receiving a local main input signal, means for receiving a local auxiliary input signal, and processing means for calculating a complex adaptive weight and generating a local output signal, utilizing the complex adaptive weight, the complex adaptive weight w_medcomprising a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal, and a sample median value of an imaginary part of the ratio of a main input weight training data signal to the auxiliary input weight training data signal.

14. An adaptive signal processing system comprising:
- means for receiving a plurality of input signals corresponding to a same target signal;
  
  means for inputting the input signals into a plurality of building blocks arranged in a cascade configuration for sequentially decorrelating each of the input signals from each other of the input signals;
  
  means for generating a single filtered output signal;
  
  wherein each building block includes means for receiving a local main input signal, means for receiving a local auxiliary input signal, and processing means for calculating a complex adaptive weight and generating a local output signal, utilizing the complex adaptive weight, wherein the complex adaptive weight w_medcomprises a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal.

15. An adaptive signal processing system comprising:
- means for receiving a plurality of input signals corresponding to a same target signal;
  
  means for inputting the input signals into a plurality of building blocks arranged in a cascade configuration for sequentially decorrelating each of the input signals from each other of the input signals;
  
  means for generating a single filtered output signal;
  
  wherein each building block includes means for receiving a local main input signal, means for receiving a local auxiliary input signal, and processing means for calculating a complex adaptive weight and generating a local output signal, utilizing the complex adaptive weight, wherein each building block calculates the complex adaptive weight, w_med, according to $w_{med} = \underset{k = 1 to K}{MED} [real (\frac{{z (k)}^{*}}{{x (k)}^{*}})] + j {\underset{k = 1 to K}{MED} [imag (\frac{{z (k)}^{*}}{{x (k)}^{*}})]}$ where K is the number of weight training data samples, z is the local main input signal, j is the unit imaginary number, and x is the local auxiliary input signal; and
  
  generates the local output signal, r,
  r=z−
  
  w*_medx.

16. An adaptive signal processing system for receiving a plurality input signals corresponding to a common target signal and for sequentially decorrelating the input signals to cancel the correlated noise components therefrom, the adaptive signal processing system comprising:
- a plurality of building blocks arranged in a cascaded configuration having N input channels and N−
  
  1 rows of building blocks, for sequentially decorrelating each of the input signals from each other of the input signals to thereby yield a single filtered output signal;
  
  wherein each row of building blocks has a first end building block which is fed originally by a main input channel and a last end building block opposite said first end building block, wherein each building block includes;
  
  a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a processing mechanism that calculates a complex adaptive weight and generates a local output signal, utilizing the complex adaptive weight;
  
  wherein said last end building block supplies the local output signal to a separate local output channel for follow on processing, wherein said complex adaptive weight comprises;
  
  a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal, and a sample median value of an imaginary part of the ratio of a main input weight training data signal to the auxiliary input weight training data signal.
- View Dependent Claims (17)
- - 17. An adaptive signal processing system as in claim 16, wherein the Nth input channel is supplied for follow on processing.

18. An adaptive signal processing system for receiving a of plurality input signals corresponding to a common target signal and for sequentially decorrelating the input signals to cancel the correlated noise components therefrom, the adaptive signal processing system comprising:
- a plurality of building blocks arranged in a cascaded configuration having N input channels and N−
  
  1 rows of building blocks for sequentially decorrelating in each of the input signals from each other of the input signals to thereby yield a single filtered output signal;
  
  wherein each row of building blocks has a first end building block which is fed originally by a main input channel and a last end building block opposite said first end building block, wherein each building block includes;
  
  a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a processing mechanism that calculates a complex adaptive weight and generates a local output signal, utilizing the complex adaptive weight;
  
  wherein said last end building block supplies the local output signal to a separate local output channel for follow on processing, wherein said complex adaptive weight comprises a sample median value of a real part of a ratio of a main input weight training data signal to an auxiliary input weight training data signal.

19. An adaptive signal processing system for receiving a plurality input signals corresponding to a common target signal and for sequentially decorrelating the input signals to cancel the correlated noise components therefrom, the adaptive signal processing system comprising:
- a plurality of building blocks arranged in a cascaded configuration having N input channels and N−
  
  1 rows of building blocks, for sequentially decorrelating each of the input signals from each other of the input signals to thereby yield a single filtered output signal;
  
  wherein each row of building blocks has a first end building block which is fed originally by a main input channel and a last end building block opposite said first end building block, wherein each building block includes;
  
  a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a processing mechanism that calculates a complex adaptive weight and generates a local output signal, utilizing the complex adaptive weight;
  
  wherein said last end building block supplies the local output signal to a separate local output channel for follow on processing, wherein said complex adaptive weight w_medis calculated according to $w_{med} = \underset{k = 1 to K}{MED} [real (\frac{{z (k)}^{*}}{{x (k)}^{*}})] + j {\underset{k = 1 to K}{MED} [imag (\frac{{z (k)}^{*}}{{x (k)}^{*}})]},$ where K is the number of weight training data samples, z is the local main input signal, j is the unit imaginary number, and x is the local auxiliary input signal; and
  
  the local output signal r is generated by solving
  r=z−
  
  w*_medx.

20. An adaptive signal processing method comprising:
- receiving a plurality of input signals;
  
  at least once inputting the input signals into a plurality of building blocks arranged in a cascade configuration;
  
  sequentially approximately decorrelating each of the input signals from each other of the input signals; and
  
  generating a filtered output signal;
  
  wherein said decorrelating includes each building block generating a complex adaptive weight w_medby calculating a sample median value of a ratio of a main input weight training data signal to an auxiliary input weight training data signal and generating a local output signal utilizing the complex adaptive weight, each building block including a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a processing mechanism that calculates the complex adaptive weight and generates the local output signal utilizing the complex adaptive weight.
- View Dependent Claims (21)
- - 21. A method according to claim 20, wherein at least one input signal comprises a common target signal or the output signal of the processing mechanism.

22. An adaptive signal processing method comprising:
- receiving a plurality of input signals;
  
  at least once inputting the input signals into a plurality of building blocks arranged in a cascade configuration;
  
  sequentially approximately decorrelating each of the input signals from each other of the input signals; and
  
  generating a filtered output signal;
  
  wherein said decorrelating includes each building block generating a complex adaptive weight w_medaccording to $w_{med} = \underset{k = 1 to K}{MED} [real (\frac{{z (k)}^{*}}{{x (k)}^{*}})] + j {\underset{k = 1 to K}{MED} [imag (\frac{{z (k)}^{*}}{{x (k)}^{*}})]}$ and generating a local output signal utilizing the complex adaptive weight, each building block including a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a processing mechanism that calculates the complex adaptive weight and generates the local output signal utilizing the complex adaptive weight, where K is the number of weight training data samples, z is the local main input signal, j is the unit imaginary number, and x is the local auxiliary input signal.

Specification

Resources

Litigation Campaign Assessment

Current Assignee
United States Secretary of the Navy
Original Assignee
the united states of america as represented by the secretary of the navy
Inventors
Gerlach, Karl, Picciolo, Michael L.
Primary Examiner(s)
Chaki, Kakali
Assistant Examiner(s)
Do, Chat C.

Application Number

US09/835,127
Publication Number

US 20020198914A1
Time in Patent Office

1,517 Days
Field of Search

708300-323
US Class Current

708/322
CPC Class Codes

G06F 17/18 for evaluating statistical ...

Pseudo-median cascaded canceller

First Claim

1 Assignment

0 Petitions

Accused Products

Abstract

43 Citations

22 Claims

Specification

Solutions

Use Cases

Quick Links

Pseudo-median cascaded canceller

First Claim

1 Assignment

Subscription Required

Subscription Required

0 Petitions

Subscription Required

Accused Products

Subscription Required

Abstract

43 Citations

22 Claims

Specification

Subscription Required

Solutions

Use Cases

Quick Links