We use quantum computing for processing and optimization tasks in radar remote sensing.
Quantum computing is used for processing and optimisation tasks in radar remote sensing. With the QUA-SAR project, we are combining the classical research field of radar remote sensing – particularly synthetic aperture radar (SAR) – with innovative quantum technologies. To this end, we have identified six main application areas. Firstly, we will improve the performance of the radar sensors themselves. This includes optimising the radar antenna, the design of the transmitted signal and the suppression of ambiguities. We are also striving for more efficient processing of large volumes of radar data. To this end, we are researching quantum algorithms that will increase the performance of future radar sensors and accelerate radar data processing.
Quantum technologies are an innovative and dynamic field of research with applications in radar remote sensing. Both the radar hardware and the radar signal processing are being developed in a fundamental way. In the QUA-SAR project, we are looking to explore and take advantage the possibilities afforded by quantum computers for solving complex processing and optimisation tasks in radar remote sensing. In the foreseeable future, quantum computing will allow us to solve certain computationally intensive tasks exponentially faster than classical computers. This opens up many new possible solutions for processing demanding and highly complex radar signals and evaluating radar data.
Modern radar remote sensing, such as that used for Earth observation from space, is playing an increasingly important role in answering essential questions about climate dynamics. Previous space-based radar sensors were able to image Earth’s surface twice a year. Future radar observatories, on the other hand, will provide images of Earth’s entire surface up to twice a week – an incredibly valuable contribution to climate research! But this also means that we need ever more powerful radar sensors for Earth observation. The primary challenges here are the speed and quality with which radar data can be acquired. For this purpose, we are developing innovative quantum algorithms that accelerate the design process of such systems or even make them possible in the first place. The second main application of novel quantum computation routines and methods is in the field of radar data processing. This ranges from the sharpening of raw SAR data to SAR interferometry and the scientific evaluation of SAR images. Here, too, we expect the use of quantum computers to offer unprecedented performance improvements