This thesis developed a Rudder Augmented Trajectory Correction (RATC) method for small unmanned aerial vehicles. The goal of this type of controller is to minimize the lateral image errors of body-fixed non-gimbaled cameras. This is achieved through both aggressive trajectory following and elimination of the roll angle present in current aileron only trajectory correction autopilots. The analytical derivation of the rudder augmented trajectory correction controller is presented. Using estimated aerodynamic derivatives of the Aerosonde UAV, RATC, produced a stable and controllable system. This control algorithm was integrated into the AggieAir Minion-class UAV using the Paparazzi open source autopilot. Flight results are presented that show significant reduction in the roll angle present during trajectory correction. This is shown using both inertial measurement nit sensor data as well as payload imagery collected over a selected region of interest. The conclusion of this thesis is that the RATC algorithm is a viable solution to minimize lateral image errors for body-fixed cameras in realm of aerial surveying.