GF-7 IMAGING SIMULATION AND DSM ACCURACY ESTIMATE

Abstract

Abstract. GF-7 satellite is a two-line-array stereo imaging satellite for surveying and mapping which will be launched in 2018. Its resolution is about 0.8 meter at subastral point corresponding to a 20 km width of cloth, and the viewing angle of its forward and backward cameras are 5 and 26 degrees. This paper proposed the imaging simulation method of GF-7 stereo images. WorldView-2 stereo images were used as basic data for simulation. That is, we didn’t use DSM and DOM as basic data (we call it “ortho-to-stereo” method) but used a “stereo-to-stereo” method, which will be better to reflect the difference of geometry and radiation in different looking angle. The shortage is that geometric error will be caused by two factors, one is different looking angles between basic image and simulated image, another is not very accurate or no ground reference data. We generated DSM by WorldView-2 stereo images. The WorldView-2 DSM was not only used as reference DSM to estimate the accuracy of DSM generated by simulated GF-7 stereo images, but also used as “ground truth” to establish the relationship between WorldView-2 image point and simulated image point. Static MTF was simulated on the instantaneous focal plane “image” by filtering. SNR was simulated in the electronic sense, that is, digital value of WorldView-2 image point was converted to radiation brightness and used as radiation brightness of simulated GF-7 camera. This radiation brightness will be converted to electronic number n according to physical parameters of GF-7 camera. The noise electronic number n1 will be a random number between -√n and √n. The overall electronic number obtained by TDI CCD will add and converted to digital value of simulated GF-7 image. Sinusoidal curves with different amplitude, frequency and initial phase were used as attitude curves. Geometric installation errors of CCD tiles were also simulated considering the rotation and translation factors. An accuracy estimate was made for DSM generated from simulated images.