Location
Hill Aerospace Museum, Conference Room
Start Date
5-6-2014 3:12 PM
Description
This paper develops an algorithm to estimate motion using a radar and ground targets. It involves estimating motion using an Extended Kalman Filter (EKF) with an Inertial Measurement Unit (IMU) and a side-looking Synthetic Aperture Radar (SAR) carried on a fixed wing aircraft flying over unknown, flat terrain. The accuracy of the motion estimation is compared to dead reckoning using only the IMU, with truth data being provided by a standard IMU/GPS Kalman filter. Initial results show that over 4.5km of simulated flight, position drift of around 300m resulted, as compared to 2.5km using only the IMU.
Using Radar Odometry on Small Unmanned Aircraft
Hill Aerospace Museum, Conference Room
This paper develops an algorithm to estimate motion using a radar and ground targets. It involves estimating motion using an Extended Kalman Filter (EKF) with an Inertial Measurement Unit (IMU) and a side-looking Synthetic Aperture Radar (SAR) carried on a fixed wing aircraft flying over unknown, flat terrain. The accuracy of the motion estimation is compared to dead reckoning using only the IMU, with truth data being provided by a standard IMU/GPS Kalman filter. Initial results show that over 4.5km of simulated flight, position drift of around 300m resulted, as compared to 2.5km using only the IMU.