Geolocation of RF Emitters
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500 West Cummings Park - Ste 3000, Woburn, MA, -
Senior Research Engineer
Senior Research Engineer
AbstractMeasurements made on RF signals from non-cooperative emitters provide situational awareness of threat locations for avoidance, countermeasures, and targeting. At present, the military uses multiple proprietary receiver systems for this task, which are not designed to interoperate, share data, or function across multiple platforms; thus they forego increased geolocation performance and accuracy that could result from rigorous data fusion. There is a clear opportunity for this, as well as reduced life-cycle operating costs, with a fleet-wide, integrated system. The Phase I effort was focused on developing new approaches based on Bayesian Sequential State Estimation (SSE) for passive emitter geolocation, on modeling many of the standard radar signal measurements for use in the estimator, on development of novel measurement types, and on simulation tradeoff studies. In Phase II, SSCI will extend the software to 1) handle a wider set of emitter signal and measurement types including communications signals; 2) support correlated radar/communications transmissions; 3) allow interoperability with heterogeneous receiver equipment and distributed operation across platforms. Software operation will be demonstrated and validated in the"Suppressor"Electronic Warfare simulation. SSCI will also further develop the sensor resource management aids from Phase I. Raytheon will provide technical and commercialization support. BENEFIT: The program will result in a system for geolocating emitters associated with RF radar and communications signals. The system will be easily adaptable to work with different receiver hardware, to operate on different platforms, and to participate in a wide array of mission configurations. This flexibility will ultimately result in a system that is easier for the Air Force to operate and maintain than current systems, and one that is more easily upgradeable for new receiver hardware and mission types, translating into lower life-cycle costs. In addition, as a result of being firmly grounded with a Bayesian sequential state estimation (SSE) engine, the SSCI system will produce more accurate estimates than existing approaches, given comparable equipment and available signal measurements. For instance, it will be able to make use of existing and planned radar warning receiver hardware and as such, incremental costs for functional implementations can be kept low, and there is a near-term path to transition validated technology into practice. The accurate and quantitative uncertainty tracking involved in SSE methods is an added benefit, providing more accurate situational information, and enabling development of analysis tools that can aid with data collection aspects of mission planning.
* information listed above is at the time of submission.