In order to ensure the radiometric imaging quality for the space-borne camera with super-wide field of view, we put forward a new method, with which the apparent spectral radiance for any field of view can be precisely calculated. Firstly, building the imaging model for the space-borne camera, and the parameters of the orbits and attitudes of satellite, the look direction for the given field of view, the characteristics of different ground objects, the state of the atmosphere, et al.. Secondly, calculating the geometrical observation parameters for the given look direction of the space-borne camera. Finally, using the radiative transfer model to calculate the value of the apparent spectral radiance. Then, we use this method to calculate the apparent spectral radiance for the space-borne camera with the FOV of 75°based on freeform mirror on a small remote sensing satellite. And the result shows that the relative non-consistency of the apparent spectral radiance can be 25.3%, when the satellite takes the imaging of the area of North Atlantic. And we should greatly consider the characteristic of the radiometric imaging quality for the space-borne camera with super-wide field of view.
Observation of meteorological parameters in coast and over sea surface layer will be conducive to understand the interaction between ocean and atmosphere, as well as the mechanism that ocean impacts on climate. Compared with the coast, it is more difficult to measure the atmospheric optical turbulence over sea, which includes measurement error caused by the instability of observation platform, instrument damage caused by poor environment and accuracy of measurement caused by the known and unknown factors, and so on. Conventional meteorological parameters and atmospheric optical turbulence in coast and over sea were observed by instruments equipped on the Marine Meteorological Science Experiment Base at Bohe and characteristics of atmospheric optical turbulence in this region were analyzed. By using temperature, humidity and wind speed, the atmospheric refractive-index structure constant in coast were estimated, and then compared with measured values, which verified the feasibility of this method.
The effects of non-uniform wind on the arrival angle temporal power spectrum of the spherical wave are numerically calculated and analyzed by using analytical formulae in Rytov approximation. The finite outer and inner scale is also included in the formulae by using modified Von-Karman spectrum of the turbulence. The results show that the non-uniform wind velocity through the propagation path will induce much change in line shape of the power spectrum. There are three scaling regions in arrival angle power spectrum of a spherical wave from Rayleigh star, which are proportional to f2/3, f5/3, f10/3 (or f11/3), respectively. In some conditions (small averaged wind velocity, relative larger random wind in horizontal propagation path near the ground), the power spectrum of spherical-wave is approximately proportional to f-8/3 in much wider frequency region, rather than f-11/3 as in uniform wind condition.
The use of neural networks are investigated for 2-D range Doppler microwave imaging. The range resolution of the microwave image is obtained by transmitting a wideband signal and the cross-range resolution is achieved by the Doppler frequency gradient in the same range bin. Hopfield neural networks are used to estimate the Doppler spectrum to enhance the cross- range resolution and reduce the processing time. There is a large number of neurons needed for the high cross-range resolution. In order to cut down the number of neurons, the reflectivities are replaced with their minimum norm estimates. The original Hopfield networks converge often to a local minina instead of the global minima. Simulated annealing is applied to control the gain of Hopfield networks to yield better convergence to the global minima. Results of imaging a model airplane from real microwave data are presented.