High-precision Infantry Training System (HITS)

2020 
Effective infantry training requires accurate pointing direction knowledge of soldier-carried weapons to determine hit or miss scores. Infantry training solutions, which transition seamlessly to operational use, enables soldiers to train with what they use in combat, thereby increasing training efficacy and soldier lethality. To meet these dual needs, BAE Systems is developing the High-precision Infantry Training System (HITS). HITS provides a day/night, weapon-mounted ballistics point-of-impact detection system, to be used for live force-on-force training at Combat Training Centers (CTCs). HITS is hardware agnostic, but presently leverages BAE Systems’ fielded FWSI (Family-of-Weapons Sights-Individual) IR camera optic system to provide a ruggedized, low-SWaP, weapon-mounted platform for high-precision gun barrel pointing angle determination. The magnetometer and Inertial Measurement Unit (IMU) sensors, housed in the FWS-I gunsight, provide approximate pointing direction information while the FWS-I IR camera produces IR imagery with a field-of-view centered on the pointing direction of the gun. HITS uses innovative computer-vision processing to calculate the gun’s correct pointing angles. HITS performs geometric alignment of the FWS-I acquired IR image to a reference image of the view. The reference image is created by projecting a pre-generated reference model of the training site, consisting of geo-located 3-D LIDAR point-cloud data, onto the image plane. Using the gunsight location information, obtained from a GPS-RTK, the correct pointing angles are calculated from the image alignment. The system has an initial pointing accuracy goal of two milliradians. In this paper, we provide an overview of the HITS algorithm components including reference image generation, image registration, and pointing angle determination.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    0
    References
    0
    Citations
    NaN
    KQI
    []