Passive Acoustic Cued Electro-Optical (ACE-O) Detect and Avoid For sUAS

Detecting and Avoiding (DAA) manned aircraft from small Unmanned Aircraft Systems (sUAS) remains the unsolved problem for safe integration of sUAS into civil airspaces where Navy UAS must pay Due Regard to the laws of civil aviation. The difficulties are manifold. The solution requires both ultra-low SWaP sensors that track aircraft over long ranges, providing 360o field-of-regard (FOR), and often through difficult visibility conditions with potential for limited line-of-sight. Detect and Avoid is a system concept, depending on maneuver capability of the UAS to avoid collisions and navigation solutions for reliable evasion. SARA is teaming with the ACAS sXu team at John Hopkins Applied Physics Laboratory to combine ACAS sXu decision support and avoidance navigation support with fused data from SARA’s proven acoustic DAA sensor and a cued EO sensor. The result will be a complete and multi-modal DAA system requiring low SWaP. The result will be an advanced DAA system providing a Due Regard capability for the Navy. Solution to the challenge of DAA will unlock the commercial ‘drone economy’ by enabling safe Beyond Visual Line of Site (BVLOS) operations and autonomy as is necessary for drone services businesses in agriculture, linear inspection and package delivery.