A study of Kalman´s filter in embedded controller for real-time quadrocopter roll and pitch measurement

Autonomous quadrocopter recently has shown a significant usages and potentials to be used widely in the commercial market. This caused the aircraft to become a well-liked subject among the researchers and research organizations. With good controllability and stability on its motions will make the usability of the quadrocopter to perform a task reliably. For this to happen, clean signals from accelerometer and gyroscope sensors appreciably play an essential role. However, the sensor´s signals are routinely encounter problems with noise and drift. Hence, a filter is required to correct this imperfectness. In this paper, a simplified algorithm for Kalman´s filter appropriates to be used by a low-cost microcontroller is presented. The research mainly focuses on filtering noisy outputs from the accelerometer so that the output is necessarily clean to be used for real-time quadrocopter pitch and roll angles estimation. Experimental results on assessment of the algorithm by varying the process and measurement noises are provided. The results reveal with correct tuning on the noise parameters; the filter algorithm is satisfying to give stable angles values with fine accuracy.