Application of Compressive Sensing Technology and Image Processing in Space Exploration

Abstract

With the efforts of Terence Tao, David Donoho and many other scientists, using the prior knowledge of signal sparsity to obtain and reconstruct compressible signals has brought new vitality to information acquisition technology. The main advantage of compressive sensing technology over traditional Nyquist sampling law is that it can recover the original signal from fewer measurements. Naturally, compressive sensing technology can be innovatively used in a wide range of fields with its own advantages, such as space exploration, which is concerned in this paper: the measurement environment is more stringent, the original signal to noise ratio is lower, and the self-weight of detection equipment is more demanding. This paper will focus on the theory of compressive sensing, and discuss its application conditions and limitations. Finally, based on the theory, its application in multi-star imaging is discussed.