Research on Inverse Recognition of Space Target Scattering Spectral Image

Because the space target is far away from the ground and the atmospheric medium strongly scatters the scattered light signal, it is difficult to get the accurate information of the target in ground-based measurement. In recent years, the rapid development of spectral observation technology has provided a new method for measuring space targets. However, it is difficult to distinguish the target directly from the spectral curve in the collected target spectral information because the target orbital height and material composition are mostly similar. Therefore, based on the bidirectional reflection distribution function (BRDF) scattering theory, the scattering spectral imaging model of space target is established. A group of geosynchronous(GEO) targets were experimentally measured by a 1. 2 m aperture ground-based observation platform and spectral video imaging system. The spectral range is 400 to 720 nm, and the spectral resolution is 2 nm. A radial basis neural network algorithm is used to unmix the BRDF in spectral data. The BRDF of six typical materials for space targets is measured experimentally. Because the target is relatively far away, it has exceeded the diffraction limit of the detection system so that the target can be regarded as a point target. However, in ground-based measurements, the atmosphere is an important barrier between the detection system and the target. The target light signal will be strongly scattered by the atmospheric medium when passing through the atmosphere. This scattering greatly attenuates the light signal, but at simultaneously the light signal is amplified according to its original structure. According to the optical memory effect, the structure of the target optical signal remains unchanged after passing through the uniform atmospheric medium. Based on the above analysis, the target spot image in measurement should retain the information of the target projection structure. Therefore, a method of segmentation inversion for the texture region of the target light spot image is used to divide the target light spot into 10 texture regions and extract the corresponding spectral data. Through the transfer function calibration and noise reduction processing of the detection system, the spectral curve of the space geometry angle of the orbiting target in the observation period is obtained. Then the typical material spectral database is used for fitting inversion. The results show that the material types in texture areas No. 2, No. 5 and No. 10 are different from other areas. At the same time, the material area ratio of each texture area is different. To further evaluate the fitting results, a non-singular matrix was used to evaluate the fitting effect, and the disturbance equation was analyzed. The highest fitting accuracy was 85. 283 3, and the lowest was 76. 982 7. It shows that the fitting results are relatively real. Target speckle image contains distinguishable target projection structure information. This study provides a new direction for detecting point target imaging and speckle image structure recognition.