Ground moving target indicator (GMTI) radar that converts radar tracks to directed graphs (DG), and creates weighted DGs aligned with superimposed with digital maps

• US 9,448,304 B2
• Filed: 03/11/2014
• Issued: 09/20/2016
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: SRC, Inc.
• Original Assignee: SRC, Inc.
• Inventors: MacPherson, David L.
• Primary Examiner(s): Vincent, David
• Application Number:
  US14/204,850
• Publication Number:
  US 20140279820A1
• Time in Patent Office: 924 Days
• Field of Search: 706/12, 706/45
• US Class Current: 1/1
• CPC Class Codes: G01S 13/5242 with means for platform motion or scan motion compensation, e.g. airborne MTI
• CPC Class Codes: G01S 13/66 Radar-tracking systems; Analogous systems
• CPC Class Codes: G01S 13/723 by using numerical data
• CPC Class Codes: G01S 7/003 Transmission of data between radar, sonar or lidar systems and remote stations
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

The present invention is directed to a system that includes a semantic reasoning engine that is configured to convert radar track data into a directed graph representation (DGR) of the predetermined surveillance region and iteratively combine the DGRs to create a weighted directed graph (WDG) aligned and superimposed with the digital map data. The WDG includes first WDG elements corresponding to moving objects detected by a radar system. The WDG is compared to historical data to obtain a surveillance detection parameter. An alarm message is generated if the surveillance detection parameter deviates from the historical data by a predetermined amount. An output device is coupled to the semantic reasoning engine and is configured to provide a representation of the digital map data, the WDG and the at least one alarm message.

Claims

1. A system comprising:

at least one sensor input configured to provide radar track data, the radar track data being derived from one or more radar images, each radar image being obtained by a radar system during a radar imaging dwell of a predetermined surveillance region;

at least one digital memory configured to store digital map data substantially corresponding to the predetermined surveillance region;

a semantic reasoning engine coupled to the at least one sensor input and the at least one digital memory, the semantic reasoning engine being configured to convert the radar track data from each radar image into an directed graph representation (DGR) of the predetermined surveillance region and iteratively combine each succeeding DGR with preceding DGRs obtained during a predetermined time frame to create a weighted directed graph (WDG) aligned and superimposed with the digital map data, the WDG including first WDG elements corresponding to moving objects detected by the radar system during the radar imaging dwell, the semantic reasoning engine also being configured to compare the WDG to historical data to obtain at least one surveillance detection parameter, at least one alarm message being generated if the at least one surveillance detection parameter deviates from the historical data by a predetermined amount; and

at least one output device coupled to the semantic reasoning engine, the at least one output device being configured to provide a representation of the digital map data, the WDG and the at least one alarm message.

2. The system of claim 1, wherein the WDG from the predetermined time frame is combined with preceding WDGs obtained from preceding time frames to obtain a WDG super-frame.

3. The system of claim 2, wherein the WDG super-frame is compared to the historical data to obtain the at least one surveillance detection parameter.

4. The system of claim 3, wherein the historical data includes at least one historical WDG super-frame.

5. The system of claim 1, wherein the predetermined time frame is selected from a range of time periods based on conditions in predetermined surveillance region.

6. The system of claim 1, wherein the at least one sensor input is coupled to a GMTI radar via an RF link.

7. The system of claim 1, wherein the at least one sensor input is configured to provide video data, intelligence data, or electromagnetic sensor (ESM) data.

8. The system of claim 7, wherein the ESM data is elected from a group of ESM data that includes signal direction data, cellular telephone data, radio frequency data, or signal modulation data.

9. The system of claim 1, wherein the at least one digital memory includes a relational database.

10. The system of claim 1, wherein the at least one digital memory includes at least one disk drive memory device or at least one solid state memory device.

11. The system of claim 1, wherein the semantic reasoning engine comprises at least one computing device.

12. The system of claim 11, wherein the at least one computing device is implemented using a computer cluster, a mainframe computer or a multi-slot server computer.

13. The system of claim 1, wherein the semantic reasoning engine is comprised of a computer cluster including N computers disposed in parallel, N being an integer value.

14. The system of claim 13, wherein the N computers includes a head node coupled to N-1 computing nodes, the head node being configured to control data transfers between the N-1 computing nodes.

15. The system of claim 14, wherein at least one node of the N-1 computing nodes is configured to process the WDG and at least one second node of the N-1 computing nodes is configured to process the historical data.

16. The system of claim 15, further comprising a communication interface coupled to at least one remote network, the N-1 computing nodes including 1-M computing nodes disposed in a local ground station and (M+1)-N computing nodes disposed remotely, the 1-M computing nodes being coupled to the (M+1)-N computing nodes via the communication interface, M being an integer value less then N.

17. The system of claim 16, wherein the communication interface is configured to transfer data and/or programming instructions between the 1-M computing nodes and the (M+1)−

N computing nodes.

18. The system of claim 13, wherein each of the N computers runs an identical operating system, or wherein at least one of the N computers runs a first operating system that differs from at least one other of the N computers.

19. The system of claim 1, further comprising at least one communication interface coupled to at least one external network.

20. The system of claim 19, wherein the at least one external network is selected from a group of networks that includes the Internet, a packet switched network, an ATM network, a DSL network, an ISDN network, a cloud based network, a PSTN, a LAN, or a WAN.

21. The system of claim 1, further comprising at least one input device coupled to the semantic reasoning engine, the at least one display and the at least one digital memory via a digital bus fabric.

22. A method comprising:

providing radar track data, the radar track data being derived from one or more radar images, each radar image being obtained during a radar imaging dwell of a predetermined surveillance region;

storing digital map data substantially corresponding to the predetermined surveillance region;

converting the radar track data from each radar image into a directed graph representation (DGR) of the predetermined surveillance region;

iteratively combining each succeeding DGR with preceding DGRs obtained during a predetermined time frame to create a weighted directed graph (WDG), the WDG including WDG elements corresponding to moving objects detected by the radar system during the radar imaging dwell;

aligning and superimposing the WDG with the digital map data to form a WDG map;

comparing the WDG map to historical data to obtain at least one surveillance detection parameter; and

generating at least one alarm message if the at least one surveillance detection parameter deviates from the historical data by a predetermined amount.

23. The method of claim 22, further comprising the step of representing the DGR, the WDG, the digital map, the WDG map and/or the WDG elements on a display.

24. The method of claim 22, further comprising the step of obtaining a WDG super-frame by combining the WDG from the predetermined time frame with WDGs obtained from preceding time frames.

25. The method of claim 24, wherein the WDG super-frame is compared to the historical data to obtain the at least one surveillance detection parameter.

26. The method of claim 25, wherein the historical data includes at least one historical WDG super-frame.

27. The method of claim 24, wherein the predetermined time frame is selected from a range of time frame periods and the WDG super-frame is selected from a range of super-frame time periods based on conditions in the predetermined surveillance region.

28. The method of claim 27, wherein the range of time frame periods includes a one-minute time frame period and the range of super-frame time periods includes a ten minute super-frame time period.