The concept of quantum remote sensing and the differences between quantum remote sensing and remote sensing is introduced, an experiment about the uses of mid and thermal infrared in quantum remote sensing is described and results are analyzed.
The background, quantum remote sensing needs and the current status of the development of quantum information technology are studied. The needs of practical applications development is the most pressing needs of quantum remote sensing. Basic concepts of quantum remote sensing are presented. Quantum remote sensing is the theory and methods reflected in the quantum level remote sensing of movement and the law theory reflected in remote sensing micro particles campaign. The counterpart relations and the differences between quantum remote sensing and remote sensing are presented. Information mechanism of quantum remote sensing is studied. Planck law is the basis in remote sensing physics and in accordance with the material reality of the world. For quantum remote sensing, quantum mechanics is the foundation for the next step needs to choose a practical application of the quantum of electromagnetic radiation field to study and deduct the formulas.
In recent years, deep learning algorithms have shown promising results for different image analyzing tasks, particularly in remote sensing image processing. Inspired by the success of remote sensing sensors in geo-located imagery, many studies have been carried out on remote sensing sensors for image processing, which brings a new approach into intelligent remote sensing and photogrammetric computer vision. At the same time, algorithms for quantum processors have been shown to efficiently solve some issues that are intractable on conventional, classical processors. This study summarizes the novel techniques of deep learning and quantum deep learning and its research progress and real-world applications in remote sensing image processing, introduces the current main challenges in processing and its development of geo-located datasets, focuses on the analysis and elaboration of the research status of quantum deep learning in sensing and imaging, and on this basis, summarizes the intelligent remote sensing applications and their application effects in scene understanding.
This work presents a study on quantum remote sensing applied to national defense using RADAR (Radio Detection and Ranging) and LIDAR (Light Detection and Ranging) technologies, which can be adopted in metrology and remote sensing processes, capable of detecting and intercepting targets in a given coverage area. In this context, the work presents a bibliographic research addressing concepts, principles of quantum mechanics, basic configurations, methods of photon entanglement, projects, experiments, and potential applications of RADAR and LIDAR systems, highlighting advantages and aspects, such as speed, greater precision, lower cost, greater security guarantee, higher sensitivity, and resolution of quantum remote sensing operation, as well as associated challenges: photon loss, technical difficulties, the phenomenon of decoherence, sensitivity to noise, and the need for integration of quantum remote sensing systems with quantum error correction modules.
In the last years, the Mid Infrared (MIR) spectral region has attracted the attention of many areas of science and technology, opening the way to important applications, such as molecular imaging, remote sensing, free- space communication and environmental monitoring. However, the development of new sources of light, such as quantum cascade laser, was not followed by an adequate improvement in the MIR detection system, able to exceed the current challenges. Here we demonstrate the single-photon counting capability of a new detection system, based on efficient up-converter modules, by proving the correlated nature of twin photons pairs at about 3.1μm, opening the way to the extension of quantum optics experiments in the MIR.