The existence of diffraction limits forces optical remote sensing to develop towards a super-large aperture, but it is limited by the production process, manufacturing cost and carrying capacity. Although block expandable optical imaging technology, thin film diffraction imaging, optical synthetic aperture imaging and other technologies have been developed, these technologies have high requirements on process level and control accuracy, and are difficult to implement. Based on the Arago spot, this paper proposes a new ultra-high-resolution imaging technology suitable for space-based optical remote sensing, replacing the traditional optical system with a visor disk to achieve the lowest-cost high-resolution observation. Simulation results show that the visor disk with a diameter of 100 meters is deployed at the Lagrangian point 450,000 kilometers away from the Earth, with a resolution of 2.5 meters, which can achieve high-resolution observations of Earth-Moon space.
In order to improve the signal-to-noise ratio(SNR) of point target detection in the air, this paper takes two types of typical aircraft as targets, fully considers the various influencing factors on the detection link, establishes the SNR model, and optimizes the detection spectrum in the range of 2-12μm. The spectrum optimization method is to select the center wavelength and bandwidth with the SNR as the objective function. The first step is to calculate the SNR-central wavelength curve in the range of 2-12μm when Δλ=0.02μm to determine the center wavelength position of the peak SNR. The second step is to change the bandwidth and calculate the band with the largest SNR near the selected center wavelength. The optimal spectrum in a typical infrared point target detection scene is calculated through an example of spectrum selection, and the influence of target characteristics and background characteristics on the results of spectrum optimization is analyzed. Finally, the image of the point target in the air taken by the GF-5 full-spectrum spectral imager is used to verify the SNR model and the method of spectrum optimization. The results show that the model of the SNR and the method of spectrum optimization are effective.
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