Electromagnetic Propagation Characterization using Communication Networks

The proposed project provides a demonstration of the ability to retrieve refractivity profile information from ungroomed radio signals of opportunity, also known as refractivity from radios or RFR, in an operationally relevant environment using operational radio receiver systems. The overall concept of RFR as originally developed was to monitor friendly, ungroomed tactical radio links and continuously provide estimates of vertical profiles of refractivity that define radio frequency (RF) ducting conditions that impact RF sensors and communication systems. The specific software application which executes the RFR technique is called Radio Inversion. The output of the software application is a current estimate of the local modified refractivity profile, provided in a format that is suitable to be used in propagation prediction tools such as AREPS. The goal of this project is to further build on the validation process by increasing the breadth and number of signals-of-opportunity over which the RFR concept is validated, and to present validation results that demonstrate its value in operationally relevant conditions. A wider mix of cooperative and non-cooperative signals will be used. Data collection geometries will include both over water and over land transmission paths. Results will show the value of RFR to support critical tasks such as the placement of assets to provide more complete monitoring of emitters in support of C4I operational goals. Proper placement of surveillance assets can ensure more complete coverage for the surveillance function, can reduce the probability of detection for friendly assets, and can even lead to improved geolocation accuracy for hostile emitters. In the end, this project is designed to confirm that offshore sensors can be used to monitor a combination of cooperative and non-cooperative emitters, use this information to more accurately assess local ducting conditions, more accurately evaluate RF signal propagation, and more effectively place sensors to support surveillance operations while minimizing counterdetection.