Data Compression Trade-offs for Tdoa/fdoa Geo-location Systems

The research results reported on here focus on new data compression methods that can enable Air Force systems to more rapidly and effectively share data for precision geolocation of RF emitters. The work was focused in four areas: (1) New Theoretical Results: We extend the previous rudimentary insight into how to use data compression to accomplish trade-offs between the sequence of tasks in a location processing scenario. In addition, data compression ideas were applied to the issue of how to select and configure a set of available sensors for location processing. This proved to be a challenging task. (2) Refine & Extend Previous Results: The short-time Fourier transform (STFT) was integrated into the data compression algorithm and was shown to properly operate. (3) Integrate Into a Matlab-based Test-Bed: Matlab routines for data compression were developed and integrated into a single Matlab application. (4) General Location Studies: In support of AFRL emitter location system development activities, this report provides important insight into the suitability of the use of previous results on emitter location. In particular, it was shown that there is a danger in using previous results that were developed explicitly for the sonar signal case when the signal was modeled as a wide-sense stationary Gaussian process. Results are provided for signal models suitable for the communication signal case.