Space Solar Telescope Image Stabilization System Image

The Space Solar Telescope (SST), proposed by Chinese scientists independently, is described as "the ambitious big plan" by the overseas media. Its main objective is to study the sun using five payloads, which will be helpful in researching the small-scale solar magnetic field, and hope to achieve a breakthrough.On the one hand, we need to increase the integration time to improve the signal to noise ratio (SNR) of the CCD image. On the other hand, the satellite platform of SST can only provide±6" pointing accuracy and 3"/s attitude stability. So the Main Optical Telescope (MOT) can not realize its 0.1" resolution without help. Under this circumstance, it is necessary to use a correlation tracker (CT) to stabilze the image.In this paper, considering the low contrast and irregularity of solar granulation, we use the correlation algorithm to detect the image movement, which is widely adopted by both foreign and domestic scientists. The correlation algorithm can be calculated by three steps. Firstly, the integral offset between the reference image and the live image can be found by getting the coordinates of the peak of correlation matrix. Secondly, sub-pixel offset can be determined by fitting the 5 by 5 matrix around the peak of correlation matrix with a parabolic surface. Finally, the total offset can be calculated by adding the integral offset to sub-pixel offset. After a large number of simulation experiments, we find that adding two parameters, obtained by statistical method, at the final step can reduce the error in image offset detection.It is a pure time delay system characteristic that its bandwidth is inverse proportion to the delay time. So, to realize the correlation algorithm as far as possible is one of the correlation tracker's key tasks. By full utilizing the characteristics of FPGA, we realize the design of correlation tracker's calculation unit and short the calculation time in great degree by modular design and pipeline organization.The 18-bit floating-point data structure can not only satisfy the restriction of XCV800 FPGA resource, but also ensure no overflow occurs during the caluculation. Through many tests, the relative error of correlation matrix between the results of our design and MATLAB program is better than 6‰.From theoretical analysis, simulated waveform, and oscilloscope's measurement, we can draw the conclusion that the correlation calculation time of our design is about 240us, which is great shorter than other designs.Above all, we improve the accuracy of image offset detection by using the modified fitting algorithm, and reduce the correlation calculation time by combining the parallel algorithm and the characteristics of FPGA. The solution we provided can not only meet the needs of correlation tracker, but also provide a reference to other similar applications.