The Department of Defense (DOD) is seeking proposals for the topic "Collaborative Airborne Sensor Fusion via Maximizing Information under Constraints" as part of the SBIR 24.1 BAA. The objective of this research is to develop algorithms that can determine the next optimal measurement or "look" on a set of targets to maximize correct identification/classification by munitions, while minimizing the total number of measurements/observations and collaborative communication required. The research will focus on both standalone munitions and swarming munitions, with the goal of increasing target identification accuracy, survivability, and battery usage efficiency.
Phase I of the project requires experience in developing autonomy algorithms for similar applications and simulating autonomy algorithms. Phase II involves simulating and demonstrating the concept of operations of maximal information measurement fusion, evaluating the algorithm's performance under various constraints, and generating simulation data. Phase III explores potential military applications, such as fusing automatic targeting information across other distributed airborne platforms, as well as commercial applications in autonomous aircraft and automobiles.
The research is restricted under the International Traffic in Arms Regulation (ITAR) and Export Administration Regulation (EAR) due to its sensitive technical data. The project duration is not specified, but the solicitation is closed. For more information, visit the DOD SBIR 24.1 BAA topic link: here.