Sensor Array Processor with Multichannel Reconstruction from Random Array Sampling

• US 20120150493A1
• Filed: 12/13/2010
• Published: 06/14/2012
• Est. Priority Date: 12/13/2010
• Status: Active Grant

• Current Assignee: Southwest Research Institute
• Original Assignee: Southwest Research Institute
• Inventors: Casey, Ryan B., Smith, Christopher B.
• Granted Patent: US 9,015,007 B2
• Time in Patent Office: Days
• US Class Current: 702/188
• CPC Class Codes: H03M 7/3062 Compressive sampling or sensing

Abstract

A method and system for reconstructing random samples taken across multiple sensors of a sensor array, so that each sensor'"'"'s output is reconstructed. The samples are processed using a compressive sensing process. The compressive sensing process uses a time-space transform basis that represents the multi-channel data in terms of both a frequency component and an azimuthal component.

Claims

1. A method of acquiring multi-channel data from a multi-sensor sensor array, the array having multiple sensor elements each of which produce an output signal, comprising:

using an array sampler to pseudo-randomly sample the output signal of each element, thereby acquiring a single-channel signal that represents the sampled output of all sensor elements;

converting the single-channel signal to digital data;

delivering the digital data to a decompression unit operable to construct a signal from every sensor element, using a compression sensing matrix;

wherein the compression sensing matrix is formed from a sampling matrix and a transform matrix;

wherein the transform matrix represents the multi-channel data in terms of a frequency domain and an azimuthal domain; and

wherein the sampling matrix is derived from an array vector matrix comprising vectors e_i where i indicates the array element being sampled.

2. The method of claim 1, wherein the sensor array is an antenna sensor array.

3. The method of claim 1, wherein the transform matrix is derived from a space-time transform.

4. The method of claim 3, wherein the space-time transform is a wavenumber vector Fourier transform.

5. The method of claim 1, wherein the sampling matrix is a product of an identity matrix and the array vector matrix.

6. A system for sampling and reconstructing the output of a multi-sensor sensor array, the array having multiple sensor elements each of which produce an output signal, comprising:

an array sampler configured to pseudo-randomly sample the output signal of each element, thereby acquiring a single-channel signal that represents the sampled output of all sensor elements;

a receiver operable to receive the single-channel signal;

a converter operable to convert the single-channel signal to digital data;

a decompression unit operable to construct a signal from every sensor element from the digital data, using a compression sensing matrix.

Wherein the compression sensing matrix is formed from the sampling matrix and the transform matrix;

wherein the transform matrix represents the multi-channel data in terms of a frequency domain and an azimuthal domain; and

wherein the sampling matrix is derived from an array vector matrix comprising vectors e_i where i indicates the array element being sampled.

7. The system of claim 6, wherein the sensor array is an antenna sensor array.

8. The system of claim 6, wherein the transform matrix is derived from a space-time transform.

9. The system of claim 8, wherein the space-time transform is a wavenumber vector Fourier transform.

10. The system of claim 6, wherein the sampling matrix is a product of an identity matrix and the array vector matrix.

11. The system of claim 6, wherein the decompression unit is implemented with firmware.

12. The system of claim 6, wherein the decompression unit is implemented with software.