Optimization Model of Signal-to-Noise Ratio for a Typical Polarization Multispectral Imaging Remote Sensor

The signal-to-noise ratio (SNR) is an important performance evaluation index of polarization spectral imaging remote sensors. The SNR-estimation method based on the existing remote sensor is not perfect. To improve the SNR of this model, a partial detector check slant direction is presented in this study, and a polarization extinction ratio related to the internal SNR model of a typical multispectral imaging remote sensor is combined with the vector radiative transfer model to construct the atmosphere 6SV–SNR coupling model. The new result is that the central wavelength of the detection spectrum, the observation zenith angle, and the extinction ratio all affect the SNR of the remote sensor, and the SNR increases with the increase in the central wavelength of the detection spectrum. It is proved that the model can comprehensively estimate the SNR of a typical polarization multispectral imaging remote sensor under different detection conditions, and it provides an important basis for the application evaluation of such remote sensors.