Testbed architecture for fusion of imaging and non-imaging airborne sensors

This paper describes an on-going effort to build an Adaptable Data Fusion Testbed (ADFT) based on a Knowledge-Based System (KBS) BlackBoard (BB) architecture to perform data fusion of imaging and nonimaging sensors present on-board the CP-140 Canadian maritime patrol aircraft. The algorithms incorporate state-of-the-art tracking in clutter and evidential reasoning for target identification. The end result offers the user a flexible and modular environment providing capability for: (a) addition of user defined sensor simulation models and fusion algorithms; (b) integration with existing models and algorithms; and (c) evaluation of performance to derive requirement specifications and help in the design phase towards fielding a real Data Fusion (DF) system