The ISR division of Etegent Technologies advances technology in the areas of machine learning, novel algorithm development, data analytics and visualization to create useful tools that benefit its customer base in the Department of Defense and the Intelligence Community.
We solve complex problems for intelligence groups involving signal processing, signature modeling, target detection and code optimization. The ISR division spans the spectrum of high-end academic research to end-user implementations; we have a demonstrated ability to operate on the cutting edge of research while also delivering pragmatic tools to improve end-user capabilities.
The Intelligence Tools team develops and delivers tools to aid analysts within the ISR community. Areas of particular note include the analysis of structured observation management (SOM) data in a spatio-temporal intensity map frame of reference, semi-automated processing of hyperspectral and infrared data sources, and tooling to support truthing and development of machine learning models. Tools are developed in a user-centric manner, with a focus on understanding the needs of the end user, providing responsive interfaces, and optimizing algorithm runtime to maximize the support provided to analysts.
Historically, sensor exploitation systems have been designed in isolation to support a specific range of operating conditions and predetermined sensor payload. As adversary countermeasures and capabilities evolve, this monolithic single sensor platform for a specific job is no longer tenable. Hence, future missions will utilize dynamic configurations of sensors – each with unique capabilities and associated cost. The DoD/IC community needs to develop the fundamental science required to address the additional complexity of re-configurable, re-taskable sensors to best utilize the available resources to enhance mission success. Some of the key developments necessary to support the new sensing paradigm are performance modeling, sensor fusion (decision/feature/handoff), sensor simulation, machine learning, and war gaming via system of system simulations. The performance modeling team leverages deep understanding of sensor phenomenology to train and characterize machine learner and statistical pattern recognition algorithms to provide tools to enable analysts, decision makers and warfighters to more effectively employ autonomy in realizing their mission goals.
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