Radar-vision multimodal fusion for dynamic target trajectory prediction and threat assessment in power transmission corridors

Jun Zhang, Zhiwei Zhang, Xiao Tan, Jin Ling, Qing Jie Deng · 2026

Read Radar-vision multimodal fusion for dynamic target trajectory prediction and threat assessment in power transmission corridors by Jun Zhang, Zhiwei Zhang, Xiao Tan, Jin Ling, Qing Jie Deng (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13338033.txt.

Description

Jun Zhang and co-authors fuse radar and cameras to guard power line corridors in a 2026 study. Drones, cranes, and wind blown debris threaten lines, yet single sensors watch under a fifth of corridor length. Their system joins the two sensor types into one pipeline built for this setting.

A learned weighting scheme trusts whichever sensor is healthier moment to moment, based on signal and weather cues. Radar motion queries attend to camera details to enrich tracking. A threat scorer blends distance, speed, and path trend into five severity grades. On six months of field data, position errors fell forty three percent versus radar alone, and threat grading scored near ninety percent accuracy.

Catalog record

CREATORJun Zhang, Zhiwei Zhang, Xiao Tan, Jin Ling, Qing Jie Deng
YEAR2026
COLLECTIONPAPERS
FORMATTXT
FILE SIZE84 KB
VERSION1.0
LICENSECC BY 4.0
RIGHTSCC BY
SOURCEEurope PMC

Source: https://europepmc.org/articles/PMC13338033

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