Parallelized Particle Swarm Optimization on FPGA for Realtime Ballistic Target Tracking

Sensors (Basel). 2023 Oct 13;23(20):8456. doi: 10.3390/s23208456.

Abstract

This paper addresses the problem of tracking a high-speed ballistic target in real time. Particle swarm optimization (PSO) can be a solution to overcome the motion of the ballistic target and the nonlinearity of the measurement model. However, in general, particle swarm optimization requires a great deal of computation time, so it is difficult to apply to realtime systems. In this paper, we propose a parallelized particle swarm optimization technique using field-programmable gate array (FPGA) to be accelerated for realtime ballistic target tracking. The realtime performance of the proposed method has been tested and analyzed on a well-known heterogeneous processing system with a field-programmable gate array. The proposed parallelized particle swarm optimization was successfully conducted on the heterogeneous processing system and produced similar tracking results. Also, compared to conventional particle swarm optimization, which is based on the only central processing unit, the computation time is significantly reduced by up to 3.89×.

Keywords: ballistic target tracking; field-programmable gate array; particle swarm optimization; realtime system.

Grants and funding

This work was supported in part by Theatre Defense Research Center funded by Defense Acquisition Program Administration under Grant UD200043CD, and in part by the MSIT (Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program (IITP-2023-2020-0-01612) supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation).