This paper discusses optical flow-based vertical angular rate fault detection based-on real fight IMU data and camera image sequences. The fight test platform utilizes a gimbal stabilized downward looking camera that is why only the angular rate around the inertial vertical axis can be estimated. Improvements relative to the previous work of the authors are the application of forward-backward optical flow to filter outliers, the direct detection of angular rate faults without the need for Euler angles or GPS velocities and tuning and verification on real images and fight data. After presenting the optical flow equations and the method for image-based vertical angular rate estimation the fight test scenarios and video processing steps are introduced. Four different Artificial errors are added to the IMU measurements and the fault detection applies residual thresholding and up-down counters. Tuning is based on false alarm and missed detection rates and the application of receiver operating characteristics. Finally, the estimation results and possible further improvements are presented.