A dynamic model-aided sensor fusion approach to aircraft attitude estimation
Matthew B. Rhudy · 2017
Attitude is an important consideration for aircraft due to its necessity for control and other purposes such as remote sensing. Sensor fusion techniques are a popular approach to attitude estimation since low-cost and lightweight sensors such as inertial sensors can be utilized. However, an additional source of information that has been mostly overlooked is the control inputs. This information is typically known, and when coupled with an aircraft dynamic model, can predict the aircraft states. This information when fused with other sensor measurements through Kalman filtering techniques offers a reasonable method for using all available information to predict aircraft attitude. This work presents the procedure for implementing this sensor fusion idea with some simulation results from a known aircraft dynamic model.