System and Method for 3D Imaging using Compressive Sensing with Hyperplane Multi-Baseline Data

• US 20160216372A1
• Filed: 01/23/2015
• Published: 07/28/2016
• Est. Priority Date: 01/23/2015
• Status: Active Grant

• Current Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Inventors: Boufounos, Petros, Liu, Dehong
• Granted Patent: US 9,971,031 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01S 13/904 SAR modes

Abstract

A method and system generates a three-dimensional (3D) image by first acquiring data from a scene using multiple parallel baselines and multiple different pulse repetition frequencies (PRF), wherein the multiple baselines are arranged in a hyperplane. Then, a 3D compressive sensing reconstruction procedure is applied to the data to generate the 3D image corresponding to the scene.

Claims

1. A method for generating a three-dimensional (3D) image, wherein the image is a virtual array image, comprising steps of:

acquiring data from a scene using multiple parallel baselines and multiple different pulse repetition frequencies (PRF), wherein the multiple baselines are arranged in a hyperplane; and

applying a 3D compressive sensing reconstruction procedure to the data to generate the 3D virtual array image corresponding to the scene.

2. The method of claim 1, wherein the data are sampled uniformly for each baseline.

3. The method of claim 1, wherein the baselines tracks parallel to each other.

4. The method of claim 1, wherein each baseline includes multiple antenna elements, and spatial locations of antenna elements are subject to jitter.

5. The method of claim 1, wherein the PRF of each baseline is independent to each other PRF.

6. The method of claim 1, wherein the data are collected from multiple antenna virtual array systems.

7. The method of claim 1, wherein a spatial distribution of the multiple baseline is random.

8. The method of claim 1, wherein an elevation aperture is larger than a single virtual array orbit tube.

9. The method of claim 1, wherein the compressive sensing method is an iterative reconstruction method.

10. The method of claim 1, wherein the elevation resolution is much higher than a conventional 3D virtual array system.

11. The method of claim 1, wherein the total number of baselines is much fewer than a conventional 3D virtual array system.

12. The method of claim 1, wherein locations of the baselines are randomly distributed on an arc of a circle centered at a scene center.

13. The method of claim 1, wherein each baseline is randomly distributed in the hyperplane with different range and elevation coordinates.

14. The method of claim 1, wherein coordinates of the baselines are (u,w) in a range-azimuth-elevation space, and the coordinates of reflectors in the scene are (x,y,z) are parallel to azimuth axis.

15. A system for generating a three-dimensional (3D) image, wherein the image is a virtual array image, comprising:

multiple parallel baselines arranged in a hyperplane, wherein the baselines acquire data from a scene using and multiple different pulse repetition frequencies (PRF); and

a processor connected to the baselines configured to apply a 3D compressive sensing reconstruction procedure to the data to generate the 3D virtual array image corresponding to the scene.