Multi-hop processing for OTHR range extension (MOHAIR)

Over the Horizon Radar (OTHR) has been a deployed capability for over 3 decades and uses the ionosphere to reflect HF radar signals in order to illuminate objects (potential targets) beyond the horizon, giving it a potential effective range of several thousand kilometers. This range is impressive, but it assumes/takes advantage of only one bounce off of the ionosphere. The capability to take advantage of multiple bounces (hops) has the potential to greatly expand the detection and tracking range of an OTH radar. Indeed, the Earth-ionosphere waveguide supports HF propagation over transcontinental distances, so it is tempting to exploit this phenomenon to double or triple the range of the existing system. Expedition Technology, Inc. (EXP) is pleased present Multi-hop Over-the Horizon Artificially Intelligent Radar (MOHAIR). At a high level, this problem is a nonlinear, multidimensional estimation problem, with noisy and imperfect data, where Deep Learning (DL) approaches are often superior to alternative methods since they fundamentally operate in a non-linear multi-dimensional space. For the problem at hand, Deep Learning will make intelligent use of heterogeneous and disparate data from several sources to produce a solution. The DL approach is complemented by the development of a MIMO-inspired waveform.