SBIR-STTR Award

SSCI and RDR Tec propose to develop and implement an on-board Fast On-line pREdiCtion of Aircraft State Trajectories using Integrated Information (FORECAST II) system, as a part of a future comprehensive Integrated Collision Avoidance System (ICAS). The main feature of the FORECAST II system is that it will be based on quantification of uncertainty arising from the use of an on-board radar, and due to unanticipated motion of a threat aircraft. The proposed system will minimize false alarms and missed detections and facilitate timely decision-making regarding the implementation of avoidance maneuvers or deconfliction strategies. In Phase I the FORECAST II system will be tested on simplified dynamic models of an onboard radar and MQ-8B Firescout unmanned autonomous helicopter. In the base period of Phase I the focus will be on problem formulation, development of a state estimation and prediction models, FORECAST II design and implementation, and initial performance evaluation, while in the option period further performance testing will be carried out.

Benefit:
Immediate applications of the FORECAST II technology are in the area of collision detection for military aircraft, rotorcraft, and UAS, and in the National Airspace that will soon be shared by both manned and unmanned aerial vehicles. The FORECAST II technology will substantially contribute to improved flight safety. Other applications of the FORECAST II technology are envisioned in air traffic control, emergency route planing, and many applications of manned and unmanned aircraft and rotorcraft in law enforcement, surveillance and rescue missions which require an effective collision avoidance function to enhance mission safety.

Keywords:
Uncertainty Quantification, Uncertainty Quantification, collision avoidance, Intent estimation, Trajectory Prediction ,

The Optically-Aided Safety Enhancement System (OASES) project develops core technologies for an Optical Collision Detection/Operator Situational Awareness System applicable to the MQ-8C Fire Scout VTUAV and other Class 4 UAVs. OASES integrates a Wide-Field-of-View (WFOV) uncooled long-wave infra-red (LWIR) camera array for search-detect-track functionality with a micro-gimbal plus zoom Narrow-Field-of-View (NFOV) camera for collision threat interrogation / evaluation. A rugged embedded computer hosts the SAFESEE image processing software. Targets detected by the WFOV camera array are developed into tracks by the SAFESEE software. Each track is formatted as J-series messages (as defined in MIL-STD-6016 series) which can be passed to external systems, and can be internally interrogated for collision threat evaluation. The collision threat evaluation for each track is passed to external systems. The OASES project includes a data collection system that allows in-flight imagery of cooperative collision-target aircraft to be collected for a variety of potential near mid-air collision scenarios. The data collection system is integrated onto a commercial Robinson R44 helicopter and includes a high precision GPS/INS navigation system to record aircraft position, velocity, and attitude (PVA) for ground truth data. The in-flight data collected can be replayed through the rugged embedded computer to test the SAFESEE software.

Benefit:
The OASES project will develop optical collision detection technologies that will extend the capability of the INAV-SL optical back-up landing system (OBULS) currently under development for the MQ-8C Fire Scout VTUAV. The INAV-SL system includes a rugged embedded computer, cameras, and INAV-SL software to provide optical back-up landing capability for the MQ-8C, but is only used during approximately 2% of the flight profile. OASES adds additional lightweight cameras (WFOV camera array and micro-gimbal zoom NFOV camera) and SAFESEE software to provide optical collision detection/operator situational awareness capability for the remaining 98% of the MQ-8C mission. The optical collision detection/operator situational awareness capability provided by the OASES system is also potentially applicable to other Class 4 UAVs, such as RQ-2B Global Hawk, MQ-4C Triton, MQ-9 Reaper, MQ-25 Stingray, and others. Because the capability is optically-based, the SAFESEE image processing software is potentially applicable to commercial drone applications, such as package delivery being pursued by companies such as Amazon.

Keywords:
camera array, MQ-8C Fire Scout, Optical Collision Detection, sense and avoid (SAA), Narrow Field of View (NFOV), SAFESEE image processing software, Wide Field of View (WFOV)