The Solution of the Dynamics Prediction of Aircraft State
Xiu Ying Zhao, Ji Cheng Quan, Jing Yuan Wei, Yu Liu, Ke Xiong Chen · Applied Mechanics and Materials · 2012
To monitor aircraft flight status, predict the position of aircraft is needed. By the research of the kalman filter, particle filter, and the best curve fitting method, use the last before time or several before moments‘s flight state data to predict the state of the aircraft, even forward time’s state, the dynamically weighted average of the multi-times data can get to the aircraft status data and subsequent flight status data, so the aircraft fly normally and smoothly with the predicted status data, that can get a good visual effect. The algorithm experiment is through the extraction data from the real aircraft data, the average relative error is 0.03%.