Environment-Aware GNSS for UAS and Autonomous Driving

This program develops environment-aware GNSS positioning for autonomous platforms — autonomous vehicles, unmanned aerial systems, and robotic platforms where the onboard sensor budget can include LiDAR, multi-camera perception, fish-eye sky imaging, dedicated compute, and real-time multi-sensor fusion. Rich environmental sensing turns the surrounding world into measurement-prior information for GNSS reliability assessment and integrity-aware positioning at the constraints — and at the safety bar — of autonomous operation.

Why it matters. Where smartphone-grade 3DMA GNSS works within tight compute and power budgets, AV and drone platforms can carry rich sensors and afford harder integrity guarantees. AV safety needs trustworthy positioning, not just accurate positioning — and rich environmental sensing is the lever that gives the integrity layer enough information to be confident.

Funding.

• RGC CRF Co-PI — Enhancing the Safety of AVs via Cross-Layer Security Hardening, HK$7M total (HK$0.6M share)
• Google Research Award — US$40k, 2024, 3DMA GNSS Precise Positioning for Vehicular Applications (PI)

Industry partners. SAIC Motor Corporation (integrity-for-AV consultancy).

Recognition.

• TechConnect 2021 Innovation Award — 3D LiDAR Aided GNSS for L4 AV
• US12123961B2 patent — 3D LiDAR Aided GNSS NLOS Detection and Correction (Hsu, Wen, granted 2024)

Representative publications. 3D Vision Aided GNSS RTK for Autonomous Systems in Urban Canyons (Wen, Bai, Hsu, NAVIGATION 2023); Safety-Quantifiable Planar-Feature LiDAR Localization for Intelligent Vehicles (Zhang et al., IEEE TIV 2024); Outlier-aware GNSS/INS/Visual Integrated Navigation in Urban Canyons (Bai et al., related publications).

Related projects. Smartphone-grade companion: 3D Map-Aided GNSS (3DMA) for Smartphone and IoT — same intellectual foundation, different platform constraints.