Multi-resolution Swarm Detection, Identification, and Tracking (MSDIT)

Swarm UAS operations by sophisticated state and even non-state actors are a cause for concern to the U.S. Navy partly because the threat potential is not fully known. Some military theorists assert that “swarming” could be the Third Offset Strategy in military thinking and the basis for possible wide-scale impacts on military operations and tactics. Swarming is “a tactic that employs multiple UAV to overwhelm targets by using mass and attrition in combination with decentralized maneuvers or combined fires from multiple directions.” Swarms may be used to disrupt ship deck or aircraft flight operations, confuse the tactical picture and situational awareness, precipitate inefficient or pre-mature expenditure of defensive weapons, conduct reconnaissance and intelligence gathering, obscure or mask high-threat units, overwhelm defenses, or themselves deliver micro-munitions including chemical or biologic using coordinated ambush, circling, or multi-axis attacks. Detection, identification, and tracking of UAS swarms is challenging because of deformability, low sUAV Signal to Noise Ratio (SNR), large numbers of units, and elements of tactics such as ambush. Irregular grouping and ungrouping dynamics complicate the swarm picture, as the arrangement can change fluidly. Detection, identification, and tracking are functions of data fusion (DF). A specialized DF function is the identification (including classification) of hard to detect and recognize objects, e.g., swarms, for which Deep Learning (DL) has in recent years shown to be a good solution. We propose two innovations at the detection and identification DF level 0 working with another at the tracking DF level 1: Innovation # 1: For long to mid-range swarms, Detection and Identification (D&I) as an Unresolved Group Target (UGT) by radar intrapulse modulations using DL trained on synthetically superposed sUAV inverse backscattering and sUAV propeller Doppler signatures. Innovation # 2: For mid to short-range swarms, D&I as a Partially-resolved / Resolved Group Target (P/RGT) using a novel spectral frequency technique using DL trained on volumetric Fourier transforms of swarm formations. These two innovations provide a seamless solution to sensor target resolution wherein the UGT continuously give way to P/RGT detections as swarm range closes. Innovation # 3: Radar and IR sensing are made complimentary, as the signal and 3-D characteristics of the radar inform swarm detections and IR detections refine identification / classification. Both are used to form swarm tracks without ever having to track individual sUAVs. Associating and tracking at the swarm level allows low visible, dim, and weakly resolved image detections to be merged into the swarm track while discarding non-associated noise detections. This blend of sensors and swarm signature-based DL and DF has never been tried before but is well-founded and solves many of the long-standing issues with swarm tracking.