Analysis of the optimal detection spectrum of air targets based on MODIS data

In point target optical detection, the selection of the detection spectrum largely determines the upper limit of detection capability. In this paper, we analyze the main factors affecting point target detection and propose a spectral segment selection method for point target detection based on constant false alarm. The method uses the probability of detection as an evaluation index and considers the target and background radiation properties, atmospheric radiative transfer, background clutter and sensor noise levels. The method can calculate the optimal spectral band for its detection for different cases of target and background information. In this paper, we analyze the clutter levels of different surface types of background using MODIS data, and take typical airborne target detection as an example. We calculate the range of spectral bands whose detection probabilities meet the requirements under several conditions to verify its feasibility. The results show that the point target detection spectra satisfying the false alarm rate and detection probability requirements can be obtained by the method in this paper