On the FPGA implementation of tracking algorithms

This paper presents the FPGA (Field Programmable Gate Array) implementation of tracking algorithms based on the estimation of a moving target status in space. Two Bayesian estimators, Kalman Filter (KF) and Extended Kalman Filter (EKF), are used to track the targets with several interacting models. Hardware architectures have been proposed for different cases. The targeted circuit was an XC2v1000 FPGA embedded on the Celoxica RC200 board. A tool was designed with visual C++ to generate automatically FPGA configurations, through the use of Handel-C language. This work was completed with an experimental validation which consists in the real-time tracking of sinusoidal signal.