Unified Frequency Hopper Detection and Prosecution Methodology, 16-9544

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Principal Investigators
Matt B. Grantz
Glen W. Mabey
Joseph E. Porter

Inclusive Dates:  04/01/05 – 04/01/06

Background - Some SwRI clients of the Signal Exploitation and Geolocation Division have expressed interest in developing the ability to reliably detect and process Frequency Hopping (FH) signals. Existing SwRI capabilities are effective with some specific types of FH transmitters, but the current demand is for more general capabilities and for improvement of the reliability and accuracy of existing systems. This research effort aims to address these problems. We also aim to establish a rigorous foundation for testing, evaluating, and promoting capabilities against specified signals in light of basic system-level specifications.

Approach - The effort has three specific goals to achieve the aims listed above:

  1. Development of a test bench using generic scientific/data processing software tools. The test bench will a) display various measured parameters of FH data (simulated or actual) recorded in files, b) allow configuration of clustering algorithms and their associations, and c) run data files through configured clustering algorithms and collect accuracy statistics. This can be done manually or in batch over a list of files.
  2. Development and assessment of new techniques for prosecuting FH signals. Tests are implemented using generic scientific/data processing software tools.
  3. Limited software integration into running systems at the SwRI antenna test field. A single, basic implementation of the clusterer in C++ is essential for testing. This will be integrated into one system at the test field to collect data and assess performance. As time permits, we will integrate and test in as many available systems as possible.

Accomplishments - The project has accomplished the following objectives to date:

  1. Developed a basic clusterer in C++ for testing
  2. Discussed and designed approaches for handling and integrating multiple features during the clustering process
  3. Developed a basic test bench tool using generic scientific/data processing tools, including display capabilities
  4. Assessed channel models for simulating LOB measurements based on deployment scenarios

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