A System Detection Performance Evaluation Method Based on Temporal Clutter Model

In order to solve the problem that the influence factors of the temporal clutter model of staring infrared camera in geostationary orbit are complex and the accuracy needs to be improved, a temporal clutter model is established by considering the camera noise, the clutter caused by line-of-sight (LOS) dither, and the clutter caused by LOS drift. Based on the angular displacement sensor data of satellite vibration experiment, the LOS dither spectrum of camera is analyzed. Based on the interframe offset of the continuous observation image sequence under typical background, the LOS drift rate of the camera is calculated. Combined with the image sequence of staring infrared camera in geostationary orbit, the temporal clutter intensities are calculated and analyzed. The results show that the relative deviation between model calculation and statistical results is less than 15%. Based on the camera index parameters and background characteristic data, the camera noise and background clutter are discussed respectively. The detection performance of the system is quantitatively evaluated and the impact of various factors on detection performance is intuitively reflected. Thus, the detectability of the target can be quickly judged while the detection background, camera parameters, camera LOS movement characteristics and background suppression algorithm remain unchanged.