Motion Blur Modeling for Multi-rotor and Fixed Wing UAVs

A priori estimation of the expected achievable quality for an uncrewed aerial vehicle (UAV) based imaging system can help validate the choice of components for the system's implementation. For uncrewed airborne imaging systems coupling the sensor to the UAV platform is relatively simple. Quantifying the expected quality of collected data can, on the other hand, be less clear and often require trial and error. The central problem for these platforms is blur. The blur produced by the various rotational modalities of the aircraft can range from overwhelming to trivial but in most cases can be mitigated. This leaves the combination of the aircraft's linear motion, its altitude and the imaging device's instantaneous field of view (IFOV) and integration time as the determining factors for the blur produced in the image. In addition, there are significant differences in speeds obtainable between multi-rotor and fixed wing UAVs. In this paper we develop mathematical models for predicting blur based on these factors. We then compare these models with field data obtained from cameras mounted to fixed wing and multi-rotor UAVs. Conclusions regarding camera characteristics best suited for both types of UAV as well as the best image acquisition parameters such as altitude and speed, are discussed.