Linear motion blur of airborne thermal systems

As infrared (IR) sensors become increasingly deployed on aerial platforms, understanding the impact of motion blur on imaging performance is essential, particularly for thermal detectors, which are more susceptible to degradation due to their longer temporal response times. Unlike photon detectors, which respond with a shorter rectangular time response, thermal sensors such as microbolometers exhibit exponential responses defined with longer time constants, making them highly sensitive to motion blur introduced by platform movement. This paper investigates the modulation transfer function (MTF) degradation resulting from linear motion in airborne thermal systems. Using both theoretical modeling and field measurements, the study explores the influence of key parameters, including platform velocity, target range, sensor time constant, and instantaneous field of view (IFOV). Field experiments were conducted using LWIR sensors mounted on UAVs, comparing measured MTFs during static, hovering, and dynamic flight conditions. The results validate the theoretical model and highlight how motion blur can severely limit system performance in real-world scenarios. These findings provide a framework for optimizing sensor design and platform operation, offering guidance for minimizing blur and enhancing image quality. The work also establishes a baseline for post-processing corrections, enabling effective deblurring of thermal imagery captured under motion.