Collaborative Distributed Swarm Radar

TECHNICAL POINT OF CONTACT (TPOC)
Thomas Provencher
PROJECTED CMMC LEVEL REQUIREMENT
Level 2 (Self)
TECHNOLOGY AREAS
Electronics
|
Sensors
MODERNIZATION PRIORITIES
Integrated Sensing and Cyber
KEYWORDS
distributed radar, UAS swarm, information fusion
OBJECTIVE
Develop novel signal processing methods to combine information from multiple small radar sensors such as those on unmanned aerial systems (UAS) for potential signal processing performance improvement.
ITAR
The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 3.5 of the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.
DESCRIPTION
A network of radar-equipped UAS or sensors can be designed as a collaborative distributed radar team. Phase I is to study hardware architectures and develop algorithms to simulate networked sensor configurations to quantify anticipated performance gains with respect to ground or maritime target surveillance. Phase II will involve a small-scale swarm testbed, using three or more UAS surrogates each carrying a small radar module, to study newly proposed techniques and sensing paradigms. Phase III will evaluate new techniques for varying Service concepts of operation. Dual Use: Distributed radar has civilian potential in environmental monitoring such as swarms of gliders mapping terrain, surveillance, and emergency response.
PHASE I
Design sensor swarm geometries and data fusion schemes. Use modeling and simulation (M&S) to develop novel signal processing algorithms and to predict performance improvements with respect to ground or maritime surveillance, specifically target detection, track and/or identification. These performance analyses would compare the performance of the collaborative radar team vs. what a single radar in the team could achieve alone. Deliverables include a feasibility study, a proposed system design, details of the signal processing algorithm chosen/developed, and M&S showing the performance prediction using a radar teaming approach. The signal processing software/algorithm implementation, and any synthetic data generated, should also be delivered.
PHASE II
Build a prototype swarm of 3 or more sensors. Use hardware to study and test new techniques and sensing paradigms. Data will be collected and delivered at the end of Phase 2 along with the prototype hardware. This data will also be used in Phase 2 to evaluate the signal processing approach from Phase 1, and to analyze the anticipated performance gains with respect to target detection, track and/or identification using a radar teaming approach vs. a single radar system. Deliverables also include a commercialization analysis based on information learned from Phase 2. The signal processing software/algorithm implementation, and any measured/synthetic data generated/collected, should also be delivered.
PHASE III DUAL USE APPLICATIONS
Evaluate new techniques for varying Service concepts of operation. Civilian uses include cooperative UAS based sensing for mapping or wide area monitoring.
REFERENCES
C. Sch ler, M. Hoffmann, R. Ebelt, I. Weber and M. Vossiek, "Position and Velocity Fusion Using Multiple Monostatic Radar Sensors for Automotive Applications," 2021 IEEE Radar Conference (RadarConf21), Atlanta, GA, USA, 2021, pp. 1-6, doi: 10.1109/RadarConf2147009.2021.9455309.
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