FPGA technology has long been applied to on-board radiometric calibration data processing however the integration of
FPGA program is not good enough. For example, some sensors compressed remote sensing images and transferred to
ground station to calculate the calibration coefficients. It will affect the timeliness of on-board radiometric calibration.
This paper designs an integrated flow chart of on-board radiometric calibration. Building FPGA-based radiometric
calibration data processing modules uses system generator. Thesis focuses on analyzing the calculation accuracy of
FPGA-based two-point method and verifies the feasibility of this method. Calibration data was acquired by hardware
platform which was built using integrating sphere, CMOS camera (canon 60d), ASD spectrometers and light filter
(center wavelength: 690nm, bandwidth: 45nm). The platform can simulate single-band on-board radiometric calibration
data acquisition in visible/near infrared band. Making an experiment of calibration coefficients calculation uses obtained
data and FPGA modules. Experimental results show that: the camera linearity is above 99% meeting the experimental
requirement. Compares with MATLAB the calculation accuracy of two-point method by FPGA are as follows: the error
of gain value is 0.0053%; the error of offset value is 0.00038719%. Those results meet experimental accuracy
requirement.
This paper presents retrieving the ocean wave parameters in shallow water area of the South China Sea from ERS-2
imagery. Based on the MPI (Max-Planck Institute) algorithm, the proposed method uses the TMA (Texel-Marsen-Arsloe)
model, which used for description of the ocean wave spectra in shallow water, as the first-guess spectra to estimate the
ocean wave parameters. The model is extended and developed through adding the factor of water depth. The ERS-2
images in South China Sea are selected as the experimental data. The data of ECMWF is used to verify the peak
wavelength and SWH (significant wave height) retrieved by the proposed method. The results show the RMSE (Root
Mean Square Error) of peak wavelength and SWH are 14.19 m and 0.13 m, respectively; the mean bias of peak
wavelength and SWH are 11.30 m and 0.02 m, respectively. The analyzed results discover that the ocean wave spectrum
parameters retrieved by the proposed method are consistent with the corresponding parameters from ECMWF in shallow
water, and the developed model can effectively response the effects of coastal shoaling because of the varying
bathymetry to the surface wave propagation.
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