Kalman Filter Embedded in FPGA to Improve Tracking Performance in Ballistic Rockets

This research project deals with the application of dynamic modeling methods for prediction and correction (filtering) of state variables in the calculation of the position and speed training rockets launched at Alcantara Launch Center. Initially, an approach is made of the means involved in launching and tracking of rockets, with the purpose of obtaining an understanding of the acquisition of radar signals, which are input of the filter. Then it made an approach of mathematical treatment of the filter dynamic model to obtain the equations used in the prediction and filtering of the rocket trajectory. Finally is made the application of Kalman filter algorithm in LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) FPGA (Field Programmable Gate Array) to estimate the position and velocity of the rocket. The main contribution of this work is to obtain a gain in processing velocity of Kalman filtering using parallelism at the hardware level, implementing a reconfigurable FPGA architecture, ensuring a platform fast enough for radars with high precision and good tracking capability of rockets.