AI Research
Researchers develop AI-powered radar technique for high-resolution 3D urban mapping
A research team from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences has developed a novel method to generate highly detailed three-dimensional (3D) city models using radar data, addressing long-standing challenges in urban mapping.
By merging artificial intelligence (AI) with architectural geometry, the new technique—dubbed Geo-SETRA—produces clearer, more comprehensive images of urban landscapes. This study was published in the Journal of Remote Sensing.
Traditional technology, known as Tomographic Synthetic Aperture Radar (TomoSAR), uses radar signals to reconstruct 3D environments; however, it has historically faced challenges in urban areas. Complex structures, such as skyscrapers and narrow alleys, often disrupt radar signals, leading to blurry or incomplete images.
To address this issue, Geo-SETRA utilizes the inherent shapes and patterns of buildings—such as rooftops, walls, and windows—as navigational cues. It incorporates these visual semantics into its algorithm, enabling the system to “fill in gaps” and enhance details by using architectural features to guide the interpretation of radar signals.
“Our approach creates a new synergy between geometric modeling and radar imaging,” said Dr. Wang Chunyi, the study’s lead author. “By letting visual semantics steer radar-based reconstruction, we boost detail and completeness without sacrificing efficiency.”
Unlike conventional SAR processing, which relies on extensive post-editing, Geo-SETRA uses a multi-stage pipeline: it starts with a rough 3D map, refines it via computer vision to identify key architectural features, and then employs these features as statistical “priors” in a Bayesian model to guide precise reconstruction.
Testing on simulated and drone-collected radar data from Suzhou, an eastern Chinese city, demonstrated notable results. The algorithm achieved sub-meter elevation accuracy, capturing fine details often missed by other techniques—such as window frames and rooftop edges. It outperformed existing methods in low-signal environments, generated denser point clouds, and retained more than 80% of critical data points.
“Our findings prove that decoding the ‘language’ of city architecture can enhance radar imaging,” Dr. Wang noted. “This could transform how we deploy airborne or spaceborne systems for smart city development, infrastructure monitoring, and disaster response.”
This study opens new doors for high-fidelity urban mapping, bridging the gap between radar capabilities and the complex demands of modern city management.
More information:
Chunyi Wang et al, A Geometric Semantic Enhanced TomoSAR Reconstruction Algorithm in an Urban Area: Analysis and Application, Journal of Remote Sensing (2025). DOI: 10.34133/remotesensing.0583. spj.science.org/doi/10.34133/remotesensing.0583
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Researchers develop AI-powered radar technique for high-resolution 3D urban mapping (2025, July 9)
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In an interview with the Post, founder and president Ronald Sun expressed confidence that IntelliGen AI could soon compete globally with Isomorphic Labs, a spin-off of DeepMind, in leveraging AI for drug screening and design.
“For generative science, new breakthroughs and application opportunities are global in nature,” Sun said. “Within 12 to 18 months, we aim to land major, high-value clients on a par with Isomorphic.”
The term “generative science”, although not widely recognised yet, refers to the use of AI to model the natural world and facilitate scientific discovery.
The company’s ambitious plan follows the launch of its IntFold foundational model, which is designed to predict the three-dimensional structures of biomolecules, including proteins. The model’s accuracy levels were comparable to DeepMind’s AlphaFold 3, according to IntelliGen AI.
In an interview with the Post, founder and president Ronald Sun expressed confidence that IntelliGen AI could soon compete globally with Isomorphic Labs, a spin-off of DeepMind, in leveraging AI for drug screening and design.
“For generative science, new breakthroughs and application opportunities are global in nature,” Sun said. “Within 12 to 18 months, we aim to land major, high-value clients on a par with Isomorphic.”
The term “generative science”, although not widely recognised yet, refers to the use of AI to model the natural world and facilitate scientific discovery.
The company’s ambitious plan follows the launch of its IntFold foundational model, which is designed to predict the three-dimensional structures of biomolecules, including proteins. The model’s accuracy levels were comparable to DeepMind’s AlphaFold 3, according to IntelliGen AI.
A new and unique supercomputing collaboration between the UK and France was announced at the UK-France Summit today (10 July).
As two of the most advanced countries in the development and use of AI for science, industry and public services, this partnership will significantly strengthen both countries’ national AI ecosystems and the wider European AI ecosystem.
The Bristol Centre for Supercomputing (BriCS) based at the University of Bristol and the Grand équipement national de calcul intensif (GENCI) will work on building and establishing a collaboration on supercomputing for the benefit of their respective communities and the broader European research ecosystem.
This joint initiative will foster bilateral scientific collaborations in the field of AI-specialisation across materials science, life sciences and medical, cybersecurity, AI security and safety, energy, and engineering, and more globally in AI for science.
The collaboration will ensure sharing of best practice on industrial involvement as well as establishing joint training and education tracks, exchange of students and researchers, hackathons, and the organisation of joint scientific seminars.
Both parties will collaborate in assessing new scientific and technical approaches including federated/distributed learning, agentic and frugal (cost efficient) AI, as well as jointly developed gathering and analysing information about advancements and trends in AI hardware and software.
Professor Simon McIntosh-Smith, Director of the Bristol Centre for Supercomputing, said: “We are delighted to work alongside GENCI to deliver an innovative and productive European supercomputing ecosystem. Our AI supercomputer, Isambard-AI, is the 11th fastest and 4th greenest supercomputer in the world and having delivered on this project successfully and at pace, the BriCS team is perfectly positioned to co-lead this with the GENCI team.”
Professor Evelyn Welch, Vice-Chancellor and President of the University of Bristol, said: “The University of Bristol is proud to have forged this pioneering new European partnership that will enable unique collaboration with our French colleagues. We will continue to develop and grow the UK’s AI and supercomputing strategy alongside the Government, accelerating critical research and supporting industry innovations at home and internationally.”
A Letter of intention between BriCS and GENCI (PDF, 309kB) provides further information on the ambitions of the partnership.
Further information
About Isambard-AI
Isambard-AI is set to become the UK’s fastest and most powerful supercomputer, purpose-built for AI research following build completion in Summer 2025. Designed to provide open-source intelligence, it will transform research and drive AI-led breakthroughs in critical areas like automated drug discovery and climate research.
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