Analyzing the effect of synthetic scene resolution, sampling interval, and signal-to-noise ratio on hyperspectral imaging sensor simulations.

Sensor simulation modeling is an important tool for the design of new earth imaging systems. As the input of the model, the characteristics of the synthetic spectral scene image data cube (SSSIDC) play an important role in the accuracy of the simulation. Based on a general sensor simulation model, the effects of SSSIDC resolution, sampling interval (SI), and signal-to-noise ratio (SNR) on simulated data are analyzed. Analysis shows that the simulated data characteristics are a function of the model parameters and the SSSIDC characteristics. The results can be used for evaluating the errors of simulated data, giving criteria for scene image synthesis, and designing appropriate model parameters for expected simulation. Simulation experiments are included to demonstrate the discussed analysis, with the results showing that the analysis is valid.