Low light observation using an Intensified CCD (ICCD) camera as a photon detector can achieve intensity detection. However, the signals that the detection system receives are simultaneously impacted by noises such as stray light and its shot noise, shot noise of detected signal, photon intensify non-uniformity (PINU) error, photon response non-uniformity (PRNU) error, and readout noise. Through the establishment of the noise model, the impact of noise on the intensity of the detected target under various conditions are analyzed in this paper. Additionally, utilizing the differential intensities undulations of the target signal in multi-frame images and the differential centroid undulations, the study develops and simulates a method to reverse the target's actual target intensity. The method is proven through simulation. The results indicate that the methodology may be able to obtain a more accurate target intensity classification when stray light is present. This work has positive significance for enhancing the accuracy of data processing through low-light remote sensing
Numerous studies have demonstrated the importance of obtaining the vertical distribution of turbulence in a time efficient way for evaluating FSO systems and related laser applications, making it necessary to specify the profile of turbulence along the atmospheric propagation path. This paper presents a method for the rapid measurement of near ground turbulence profiles. This method is capable of providing a real-time evaluation of an optical propagation link, making it a useful tool for remote sensing of atmospheric turbulence. Based on this method, a turbulence profile LiDAR has been built in Hefei (31.8°N, 117.3°E) and long-term continuous measurements of the vertical distribution of turbulence were performed from October 2021 to November 2021. The retrieved results of turbulence profiles show that the LiDAR can describe spatiotemporal distributions of turbulence intensity along the measurement path corresponding to the weather and daily time changes.
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