Detection and identification of stable PRI patterns using multiple parallel hypothesis correlation algorithms

• US 7,133,887 B2
• Filed: 08/08/2003
• Issued: 11/07/2006
• Est. Priority Date: 08/08/2003
• Status: Active Grant

• Current Assignee: Callahan Cellular LLC (Intellectual Ventures LLC)
• Original Assignee: BAE Systems Information and Electronic Systems Integration Incorporated (BAE Systems Plc)
• Inventors: Sirois, Joseph A
• Primary Examiner(s): Mai, Tan V.
• Application Number:
  US10/637,386
• Publication Number:
  US 20050033789A1
• Time in Patent Office: 1,187 Days
• Field of Search: 708/422
• US Class Current: 708/422
• CPC Class Codes: G01S 7/021 Auxiliary means for detecting or identifying radar signals or the like, e.g. radar jamming signals
• CPC Class Codes: G06F 17/15 Correlation function computation including computation of convolution operations arithmetic circuits for sum of products per se, e.g. multiply-accumulators G06F7/5443; digital filters, e.g. FIR, IIR, adaptive filters H03H17/00

Abstract

An algorithmic approaches that can be implemented in software/firmware/hardware that filters out stable PRI patterns detected within a system that is prosecuting against radar based transmissions are disclosed. The algorithms allow downstream computing assets to concentrate their limited resources on the more complex emitter PRI pattern types. Thus, a portion (e.g., stable signals) of the pulse deinterleave and PRI identification problem is solved without requiring the more computationally expensive processing. The disclosed algorithms can be employed, for example, in electronic support measures (ESM) systems, electronic intelligence (ELINT) systems, and/or a electronic countermeasures (ECM) systems. The algorithms employ linear detection, linear regression, or a combination of linear detection and linear regression, thereby providing a “dual voting” scheme that decreases the occurrence of false positives. Other algorithmic approaches can be used as well in a multi-voting scheme that considers PRI estimates from distinct analysis types.

Claims

1. A multiple correlation processor device configured to estimate PRI associated with a received pulse train, the device comprising:

a linear detection module adapted to analyze a set of TOA data associated with the received pulse train, and to estimate a PRI associated with that set;

a linear regression module adapted to analyze the set of TOA data, and to estimate the PRI associated with that set; and

a dual vote module adapted to determine if the estimated PRIs provided by the linear detection and linear regression modules are both passing with respect to predefined pass/fail thresholds.

2. The device of claim 1 wherein the linear detection, linear regression, and dual vote modules are each included in a correlator mask, and the device includes a number of such masks, each mask for analyzing a subset of pulses included in the pulse train.

3. The device of claim 2 wherein analyzing performed by the masks is performed in parallel.

4. The device of claim 2 wherein PRI estimates output by the masks are collected at an output stage, and filtered, thereby separating PRIs identified as stable from uncorrelated PRI data.

5. The device of claim 4 wherein only the uncorrelated PRI data is provided for complex signal processing to identify other PRIs present in the pulse train.

6. The device of claim 4 wherein only the PRIs identified as stable are provided to a final analysis module adapted to perform one or more heuristic tests that assess the results provided by the linear detection, linear regression, or dual vote modules.

7. The device of claim 6 wherein the one or more heuristic tests performed by the final analysis module includes at least one of a one signal present test, a one signal modulo test, a one signal remaining test, a two signals present test, and a two-phase stagger test.

8. The device of claim 6 wherein the final analysis module provides its output to a possible problem module adapted to perform a tie-breaker analysis when analysis performed by the final analysis module indicates a discrepancy.

9. The device of claim 1 wherein at least one of the linear detection, linear regression, and dual vote modules is configured to output a corresponding report including at least one of an estimated PRI, a pass/fail status, a correlation value, and pulses associated with the estimated PRI.

10. The device of claim 1 wherein the device is configured to receive a control signal including a mode select that causes the device to operate in one of a linear detection mode, a linear regression mode, or a dual vote mode.

11. The device of claim 1 wherein each of the linear detection and linear regression modules are both configured to output a corresponding report including a pass/fail status associated with the estimated PRI, thereby enabling the dual vote module to determine if the estimated PRIs both passed.

12. A multiple correlation processor device configured to estimate PRI associated with a received pulse train, the device comprising:

a first-type PRI detection module adapted to analyze a set of TOA data associated with the received pulse train, and to estimate a PRI associated with that set;

a second-type PRI detection module adapted to analyze the set of TOA data, and to estimate the PRI associated with that set; and

a multi-vote module adapted to determine if the estimated PRIs provided by the first-type and second-type detection modules are both passing with respect to predefined pass/fail thresholds.

13. The device of claim 12 wherein each of the modules is included in a correlator mask, and the device includes a number of such masks, each mask for analyzing a subset of pulses included in the pulse train, thereby allowing for parallel processing.

14. The device of claim 13 wherein PRI estimates output by the masks are collected at an output stage, and filtered, thereby separating PRIs identified as stable from uncorrelated PRI data.

15. The device of claim 14 wherein only the uncorrelated PRI data is provided for complex signal processing to identify other PRIs present in the pulse train.

16. The device of claim 14 wherein only the PRIs identified as stable are provided to a final analysis module adapted to perform one or more heuristic tests that assess the results provided by at least one module selected from the group consisting of:

the first-type PRI detection module, the second-type PRI detection module, and the multi-vote module.

17. The device of claim 16 wherein the heuristic tests performed by the final analysis module include at least one of a one signal present test, a one signal modulo test, a one signal remaining test, a two signals present test, and a two-phase stagger test.

18. The device of claim 16 wherein the final analysis module provides its output to a possible problem module adapted to perform a tie-breaker analysis when analysis performed by the final analysis module indicates a discrepancy.

19. The device of claim 12 wherein at least one of the first-type PRI detection module, second-type PRI detection module, and multi-vote module is configured to output a corresponding report including at least one of an estimated PRI, a pass/fail status, a correlation value, and pulses associated with the estimated PRI.

20. The device of claim 12 wherein the device is configured to receive a control signal including a mode select that causes the device to operate in one of a first-type PRI detection mode, a second-type PRI detection mode, and a multi-vote mode.