Abstract:
Closed-loop fire control systems greatly increase a weapon system's ability to success-
fully engage a target by measuring the trajectories of its outgoing projectiles. This has
been demonstrated with both line-of-sight and non-line-of-sight systems, but research in
autonomous Remote Weapon Stations (RWS's) currently lacks this capability. One of the
major challenges in bringing this capability to RWS's is that radar is not seen as an appro-
priate sensor due to its size, cost, and active nature.
The goal of this research was to determine if projectile trajectories could be accurately
measured with a camera. Algorithms were developed to detect small-caliber tracer rounds
in images and then combine those detections with a ballistic model to estimate trajectories.
These algorithms were successfully tested with live gunfire data, which showed that tracer
rounds were readily detectable and that estimated trajectories accurately predicted impact
points. Simulations also show that the algorithms can distinguish individual tracer trajec-
tories from machine gunfire and eliminate several types of outliers. These results open the
possibility of providing closed-loop fire-control to RWS's by using a camera as the main
sensor.
