Heterogeneous data fusion

Patent metadata

Field	Value
Publication number	US-11068756-B2
Application number	US-201916299517-A
Country	US
Kind code	B2
Filing date	Mar 12, 2019
Priority date	Mar 12, 2019
Publication date	Jul 20, 2021
Grant date	Jul 20, 2021

Abstract

Various deficiencies in the prior art are addressed by systems, methods, architectures, mechanisms and/or apparatus configured to fuse data received from a plurality of sensor sources on a network. The fusing data includes forming an empirical distribution for each of the sensor sources, reformatting the data from each of the sensor sources into pre-rotational alpha-trimmed depth regions, applying an affine transformation rotation to each of the reformatted data to form post-rotational pre-rotational alpha-trimmed depth regions, and reformatting each affine transformation into a new data fusion operator.

First claim

What is claimed is:

1. A method for detecting targets in a real-world background, the method comprising:
obtaining data from a plurality of sensor sources on a network;
sending the data to at least one of a data fusion center or a super-sensor;
fusing the data received from said plurality of sensor sources, said fusing comprising:
forming an empirical distribution for each of the sensor sources;
reformatting the data from each of the sensor sources into pre-rotational alpha-trimmed depth regions;
applying an affine transformation rotation to each of the reformatted data to form post-rotational pre-rotational alpha-trimmed depth regions;
reformatting each affine transformation into a new data fusion operator; and

using said fused data to determine whether a target is present in at least one of: on the ground, in the air, or in outer space, in a real-world background.

2. The method of claim 1 , further comprising one or more of storing, post-processing, and disseminating the new data fusion operator.

3. The method of claim 1 , wherein the new data fusion operator is three-dimensional.

4. The method of claim 1 , further comprising solving for an affine transformation value.

5. The method of claim 1 , wherein each of the sensor sources comprises a transceiver.

6. The method of claim 1 , wherein the data is sent to a super-sensor, and the method is performed by a super-sensor on the network.

7. The method of claim 1 , wherein the sensor sources are either similar or dissimilar.

8. The method of claim 1 , wherein the data from the sensor sources is either similar or dissimilar.

9. The method of claim 1 , wherein the data comprises one or more of imaging, radiofrequency, electro-optical, infra-red, communication, acoustic, pressure, temperature, and gravimetric.

10. A data fusion system for a plurality of sensor sources on a network for detecting targets in at least one of: on the ground, in the air, or in outer space, in a real-world background, the data fusion system comprising:
a central fusion center configured to receive data from the sensor sources and fuse the received data into a higher-dimensional statistical population, wherein fusing the received data comprises:
forming an empirical distribution for each of the sensor sources;
reformatting the data from each of the sensor sources into pre-rotational alpha-trimmed depth regions;
applying an affine transformation rotation to each of the reformatted data to form post-rotational pre-rotational alpha-trimmed depth regions; and
reformatting each affine transformation into a new data fusion operator,

wherein said data fusion system is used to detect whether a target is present in at least one of: on the ground, in the air, or in outer space, in a real-world background.

11. The system of claim 10 , wherein fusing the received data further comprises one or more of storing, post-processing, and disseminating the new data fusion operator.

12. The system of claim 10 , wherein the new data fusion operator is three-dimensional.

13. The system of claim 10 , wherein fusing the received data further comprises solving for an affine transformation value.

14. The system of claim 10 , wherein each of the sensor sources comprises a transceiver.

15. The system of claim 10 , wherein the central fusion center is a super-sensor.

16. The system of claim 10 , wherein the sensor sources are either similar or dissimilar.

17. The system of claim 10 , wherein the received data is either similar or dissimilar.

18. The system of claim 10 , wherein the received data comprises one or more of imaging, radio-frequency, electro-optical, infra-red, communication, acoustic, pressure, temperature, and gravimetric.

19. A non-transitory computer-readable medium having stored thereon a computer program for execution by a processor configured to perform a method of fusing data received from a plurality of sensor sources on a network for detecting whether a target is present in at least one of: on the ground, in the air, or in outer space, in a real-world background, the method comprising:
forming an empirical distribution for each of the sensor sources;
reformatting the data from each of the sensor sources into pre-rotational alpha-trimmed depth regions;
applying an affine transformation rotation to each of the reformatted data to form post-rotational pre-rotational alpha-trimmed depth regions;
reformatting each affine transformation into a new data fusion operator; and
using said fused data to determine whether a target is present in at least one of: on the ground, in the air, or in outer space, in a real-world background.

20. The computer-readable medium of claim 19 , further comprising one or more of storing, post-processing, and disseminating the new data fusion operator.

21. The method of claim 1 , wherein at least some of the data received from the sensor sources and fused is at least one of pre-detection and pre-processed data.

22. The method of claim 1 , wherein the fusion center or super-sensor formats and/or stores the data for processing on an at least a near real-time basis.

23. The method of claim 1 , wherein at least two of said plurality of sensors comprise radar systems that are separated by a distance, and said radar systems search for targets with a defined radar-cross section.

24. The method of claim 23 , wherein the sensors comprise part of a system that can detect, discriminate, declare, and identify targets autonomously.

25. The method of claim 24 , wherein said radar comprises part of a fire-control radar system for targeting, tracking, and hitting a target.

Assignees

• Us Gov Air Force
• Us Air Force

Inventors

• Browning James

Classifications

• G01S13/86 Primary

  Combinations of radar systems with non-radar systems, e.g. sonar, direction finder · CPC title

• G06V30/2552

  Combination of methods, e.g. classifiers, working on different input data, e.g. sensor fusion · CPC title

• G06F18/256

  of results relating to different input data, e.g. multimodal recognition · CPC title

• G06F17/14

  Fourier, Walsh or analogous domain transformations {, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms (for correlation function computation G06F17/156; spectrum analysers G01R23/16)} · CPC title

• G01S13/003

  Bistatic radar systems; Multistatic radar systems · CPC title