IP Library Granted Patent US 9,239,387
Granted Patent B2
US 9,239,387 · App. 13/721,350 · Granted Jan 19, 2016

Method and system for reconstructing scenes using virtual arrays of transducers and joint sparsity models

Inventor: Petros Boufounos (Boston, MA)
Assignee: Mitsubishi Electric Research Laboratories, Inc.
G01S15/89G01S13/89G01S15/876G06K9/6249G01S7/54G01S15/003
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Quick Facts
Patent No.
US 9,239,387
App. No.
13/721,350
Granted
Jan 19, 2016
Kind
B2
Abstract

A scene is reconstructed by receiving pulses transmitted by a virtual array of transducers. The pulses are reflected by the scene. The virtual array has a set of configurations subject to positioning errors. Each received pulse is sampled and decomposed to produce frequency coefficients stacked in a set of linear systems modeling a reflectivity of the scene. There is one linear system for each configuration. A reconstruction method is applied to the set of linear systems. The reconstruction method solves each linear system separately to obtain a corresponding solution. The corresponding solutions share information during the solving. Then, the solutions are combined to reconstruct the scene.

Claims (19)

1. A system for reconstructing a scene, comprising:

an array of radar transducers configured to transmit pulses at the scene and receive the pulses reflected by the scene, wherein the array has a set of configurations subject to positioning errors;

a processor connected to the array of transducers for sampling and decomposing each received pulse to produce frequency coefficients stacked in a set of linear system of equations modeling a reflectivity of the scene, wherein there is one linear system of equations for each configuration; and

applying a reconstruction method to the set of linear system of equations by

solving each linear system of equations separately to obtain a corresponding solution, while the corresponding solutions share information during the solving; and

combining the solutions to reconstruct the scene, wherein the combining produces an average of the solutions.

2. The system of claim 1 , wherein the information is a support of each solution during the reconstructing.

3. The system of claim 2 wherein the support is common among the solutions during the reconstructing.

4. The system of claim 2 , wherein the support is enforced to be identical for all solutions during the reconstructing.

5. The system of claim 1 , wherein a joint-sparsity model is used during the reconstructing.

6. The system of claim 5 , wherein a convex optimization is used during the reconstructing.

7. The system of claim 5 , wherein a greedy method is used during the reconstructing.

8. The system of claim 1 , wherein a model of the scene is enforced during the reconstructing.

9. The system of claim 1 , wherein the average is an average magnitude of coefficients of the solutions.

10. The system of claim 1 , wherein the average is an average of square magnitudes of coefficients of the solutions.

11. The system of claim 10 , wherein the combining takes a square root of the average.

12. The system of claim 1 , wherein the combining determines a common support for the solutions.

13. The system of claim 1 , further comprising:

merging the linear systems of equations.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 7, 2013
From: BOUFOUNOS, PETROS
To: MITSUBISHI ELECTRIC RESEARCH LABORATORIES, INC.
Reel/Frame 029774/0540 →
Continuity (2)
Continuation In Part 12895408 · Sep 30, 2010
Related Publication 20130107667A1 · May 2, 2013