This paper presents two ways to implement Extended Kalman Filter (EKF) algorithm for Inertial Navigation of a Micro Aerial Vehicle (MAV). The objective is to develop a fully integrated system using Micro electro mechanical systems (MEMS) inertial sensors combined with low-update rate Global positioning system (GPS) measurements. The approach uses three accelerometers, three gyroscopes and GPS measurements to aid the EKF algorithm. Two ways to implement EKF (15-state and splitarchitecture) are presented and observability issues are addressed in each case. EKF performance was evaluated by comparing the estimates with the simulated truth data.
"ADDRESSING ISSUES IN INERTIAL NAVIGATION OF MICRO AERIAL VEHICLES (MAV) VIA AN EXTENDED KALMAN FILTER WITH BIASED SENSORS,"
International Journal of Applied Research in Mechanical Engineering: Vol. 2
, Article 5.
Available at: https://www.interscience.in/ijarme/vol2/iss1/5