Sensor suite and signal processing for border surveillance

• US 9,696,409 B2
• Filed: 05/11/2015
• Issued: 07/04/2017
• Est. Priority Date: 06/08/2006
• Status: Active Grant

• Current Assignee: Aerostar International LLC (CNH Industrial N.V.)
• Original Assignee: Vista Research, Inc. (Guidepoint Global LLC)
• Inventors: Fox, Phillip A., Maresca, Jr., Joseph W.
• Primary Examiner(s): GREGORY, BERNARR E
• Application Number:
  US14/708,953
• Publication Number:
  US 20160097839A1
• Time in Patent Office: 785 Days
• Field of Search: 342 27, 342 28, 342 52- 60, 342 89-103, 342118, 342134-147, 342175, 342192-197, 342159-164
• CPC Class Codes: G01S 13/522 using transmissions of interrupted pulse modulated waves
• CPC Class Codes: G01S 13/723 by using numerical data
• CPC Class Codes: G01S 13/86 Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 13/886 for alarm systems alarms with electrical actuation G08B13/22
• CPC Class Codes: G01S 7/2922 by using a controlled threshold

Abstract

A land-based Smart-Sensor System and several system architectures for detection, tracking, and classification of people and vehicles automatically and in real time for border, property, and facility security surveillance is described. The preferred embodiment of the proposed Smart-Sensor System is comprised of (1) a low-cost, non-coherent radar, whose function is to detect and track people, singly or in groups, and various means of transportation, which may include vehicles, animals, or aircraft, singly or in groups, and cue (2) an optical sensor such as a long-wave infrared (LWIR) sensor, whose function is to classify the identified targets and produce movie clips for operator validation and use, and (3) an IBM CELL supercomputer to process the collected data in real-time. The Smart Sensor System can be implemented in a tower-based or a mobile-based or combination system architecture. The radar can also be operated as a stand-alone system.

Claims

1. A non-transitory computer-readable medium comprising instructions stored thereon, which when executed by at least one processor, configure the processor to perform operations comprising:

transmitting a plurality of radar pulses by a non-coherent radar toward an area;

receiving a radar return scattered from the area, the radar return including a return from a target and interference from system noise and background noise and clutter; and

processing the radar return for at least one range-azimuth resolution cell in the area to differentiate the return from the target from the interference from the system noise and background noise and clutter, the processing including;

comparing the radar return to a first threshold, the first threshold set at a level to identify multiple radar contacts including the target and false contacts from the interference from system noise and background noise and clutter, wherein a radar contact is declared when the radar return exceeds the first threshold; and

tracking the multiple radar contacts over time to distinguish the target from the false contacts.

2. The non-transitory computer-readable medium of claim 1, wherein said processing the return includes applying an algorithm that determines whether a track derived from the radar return for at least two time intervals is consistent with an expected track for an actual target.

3. The non-transitory computer-readable medium of claim 2, wherein said track is determined by a level of confidence of a probability statistic applied to said radar return.

4. The non-transitory computer-readable medium of claim 3, wherein said probability statistic is defined by a log-likelihood ratio with the assumption that said system noise and clutter within each one of said at least one resolution cell is substantially constant over a period of time, and wherein target-absent statistics over multiple radar scans is determined and used in the determination of the log-likelihood ratio.

5. The non-transitory computer-readable medium of claim 3, wherein said probability statistic is based on Bayesian statistical methods.

6. The non-transitory computer-readable medium of claim 1, wherein said receiving includes collecting and processing at least two samples of said radar returns from said at least one range-azimuth resolution cell.

7. The non-transitory computer-readable medium of claim 1, wherein said processing said radar return includes pre-processing data from said radar return to generate a detection field before said return is differentiated.

8. The non-transitory computer-readable medium of claim 7, wherein said detection field is generated after conditioning operations are performed on said return, wherein said conditioning operations include an operation selected from the group consisting of calibration, spatial registration, pre-filtering, constant background removal, and noise background estimation.

9. The non-transitory computer-readable medium of claim 8, wherein said spatial registration includes aligning resolution cells for direct comparison from one scan to the next scan.

10. The non-transitory computer-readable medium of claim 7, wherein said detection field is generated by segmentation of said data.

11. The non-transitory computer-readable medium of claim 7, wherein said pre-processing includes separating resolution cells into different categories for processing based on the type of noise and clutter present in said resolution cells.

12. A system comprising:

at least one processor;

a memory with instructions stored thereon, which when executed by the at least one processor, configure the at least one process to perform operations comprising;

receiving a radar return resulting from a non-coherent radar transmitting a plurality of radar pulses towards an area, the radar return scattered from the area and the radar return including a return from a target and interference from system noise and background noise and clutter; and

processing the radar return for at least one range-azimuth resolution cell in the area of interest to differentiate the return from the target from the interference from the system noise and background noise and clutter, the processing including;

comparing the radar return to a first threshold, the first threshold set at a level to identify multiple radar contacts including the target and false contacts from the interference from system noise and background noise and clutter, wherein a radar contact is declared when the radar return exceeds the first threshold; and

tracking the multiple radar contacts over time to distinguish the target from the false contacts.

13. The system claim 12, wherein said processing the return includes applying an algorithm that determines whether a track derived from the radar return for at least two time intervals is consistent with an expected track for an actual target.

17. The system of claim 12, wherein the operation of processing the radar return includes an operation of pre-processing data from the radar return to generate a detection field before the return is differentiated.

18. The system of claim 17, wherein the operation of pre-processing includes separating resolution cells into different categories for processing based on the type of noise and clutter present in said resolution cells.

19. The system of claim 17, wherein said detection field is generated by segmentation of the data.

20. The system of claim 12, wherein a second threshold is used to differentiate false contacts due to the noise and clutter from actual targets, the second threshold being based on a track-before-detect method.

14. The system 13, wherein said track is determined by a level of confidence of a probability statistic applied to said radar return.

15. The system of claim 14, wherein said probability statistic is defined by a log-likelihood ratio with the assumption that said system noise and clutter within each one of said at least one resolution cell is substantially constant over a period of time, and wherein target-absent statistics over multiple radar scans is determined and used in the determination of the log-likelihood ratio.

16. The system of claim 14, wherein said probability statistic is based on Bayesian statistical methods.