Improved Kalman Filter in Variometer

Differentiation of the measured value from altitude computed from actual static pressure or differentiation of the static pressure value and conversion into the altitude rate are the bases for measuring an altitude rate of an aircraft. Therefore, the differentiator is a crucial component of the measurement system. In this paper, a new method of differentiation is proposed, in which a Kalman filter with the process model of double integration is used. A modification has been introduced based on the estimation of the variance of the unknown input signal. This modification is a result of the analysis of the model of the dynamic process and the Kalman filter equations. The algorithm developed estimates the variance of the input signal using the measured altitude and the altitude being the output from the Kalman filter. This algorithm and two others have been tested using two types of signals, an artificial signal and recorded values of altitude obtained during in-flight experiments. The results obtained in both tests are consistent and confirm the predicted effects of the differentiator adaptation, which is manifested by a faster response in states with a high variation in altitude rate and also by an increased disturbance suppression in flight states with almost constant vertical speed compared to differentiators with constant parameters.