Abstract
The emerging optical imager can greatly reduce system weight and size compared to conventional telescopes. The compressive sensing (CS) theory demonstrates that incomplete and noisy measurements may actually suffice for accurate reconstruction of compressible or sparse signals. In this paper, we propose an optimized design of the emerging optical imager based on compressive sensing theory. It simplifies data acquisition structure and reduces data transmission burden. moreover, the system robustness is improved.
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Acknowledgements
This work is supported by China Lunar Exploration Project (CLEP) and Youth Innovation Promotion Association, CAS.
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Liu, G., Wen, D., Song, Z., Li, Z., Zhang, W., Wei, X. (2020). Compressive Sensing-Based Optimal Design of an Emerging Optical Imager. In: Lu, H. (eds) Cognitive Internet of Things: Frameworks, Tools and Applications. ISAIR 2018. Studies in Computational Intelligence, vol 810. Springer, Cham. https://doi.org/10.1007/978-3-030-04946-1_8
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