|Electromagnetic Environment Situational Awareness for NATO|
|Information Systems Technology|
Big Data, Cognitive Radio & Networks, Data Fusion, DSA, EW, Spectrum Awareness & monitoring, Transmitter Localization
The Electromagnetic Environment Situational Awareness (EESA) under the Name of Radio Environmental Map (REM) has recently attracted a lot of attention in the wireless communications research community. The REM can be viewed as rich hierarchical databases containing various types of static and dynamic radio environment information e.g. sensing information from Radios or EW sensors, raw spectrum measurements, terrain models, building plans, fixed transmitters, statistical propagation models, estimations of located transmitters and their configurations, estimations of radio propagation models etc. Electromagnetic Environment Situational Awareness can be seen as a field of application of Big Data Analytics to the Spectrum Awareness on the battlefield.
REM is an enabler to enhance EM environment awareness on the Battlefield. It can be exploded to produce a multilayer (per frequency) geographical map of the usage of the spectrum.
1. Review the current state of the practice in managing the electromagnetic spectrum, particularly across NATO partners,
2. Establish and demonstrate the REM benefits for NATO C4ISR operations and systems,
3. Define a first model of REM,
4. Demonstrate the REM feasibility even if the REM model studied and demonstrated has not the objective to be fully complete,
5. Evaluate the gap between the existing legacy system and the future REM.
WP1: Study the added value and possible military applications of an EESA/REM for NATO:
WP2: Define the overall REM architecture, tools and associated Interfaces/APIs between Sensors/sources and REM, between REMs in an international deployment:
WP3: Develop a REM demonstrator (TRL tbd) based on a Technico-Operational simulation, data processing & HMI which will be shared between the countries involved in the RTG:
WP4: Define the futures works (NATO standardization):