Multi-Sensor Track Classification in Rotorcraft Pilot's Associate Data Fusion

The objective of the Rotorcraft Pilot's Associate (RPA) Advanced Technology Demonstration (ATD) is to apply artificial intelligence and state-of-the-art computing technologies to manage and integrate next generation mission equipment and battlefield information in order to enhance the lethality, survivability, and mission effectiveness of combat helicopters. Lockheed Martin Advanced Technology Laboratories is responsible for the real-time, computeintensive Data Fusion (DF) Subsystem that integrates inputs from large numbers of on-board and off-board sensors which describe ground and air targets as well as missiles. Mission scenarios are characterized by high target densities, rapid sensor update rates, and significant data uncertainties. DF furnishes to the Battlefield Assessment (BA) module uncluttered, fused target tracks with enhanced geospatial and classification accuracy. This paper describes fast and effective algorithms for comparison, derivation, and fusion of track classifications from multiple sensors. The contributions of these algorithms to the creation of a precise and uncluttered picture of the battlefield have been verified and quantified.