As automated driving systems demand ever higher levels of positioning accuracy and resilience, GNSS architectures are evolving beyond standalone receivers.
Integrating positioning chips, cloud correction services and antennas into a unified ecosystem offers new opportunities to improve reliability, reduce costs and strengthen protection against interference. We spoke with Dr. Hongyang Zhang, Product Manager at BDStar, about the advantages of cloud-chip co-design, the positioning challenges that remain, and how engineers can validate robust, global positioning performance for next-generation vehicles.
1. What are the key benefits of co-designing receivers and correction services?
This Cloud-Chip integrated architecture unifies data cloud service, positioning chip modules and receiving antennas under one integrated design, supply and support system. The cloud and chips work in synergy to suppress ionospheric scintillation, deliver stable low-traffic correction transmission, and continuously upgrade positioning performance with full data security compliance. Meanwhile, chips are fully adapted to antennas via optimized system layout, matched signal bandwidth and RF links, enabling joint anti-interference capability against urban multipath and malicious spoofing/jamming. The all-in-one solution brings clear benefits: lower overall costs, reliable positioning security, single-point accountability and rapid fault diagnosis for global automotive mass production.
2. Which positioning failure modes remain most difficult to solve?
Multipath in dense urban canyons, where worst-case errors can evade standard RAIM checks;
Ionospheric scintillation degrades GNSS observation quality and increases the probability of cycle slips and signal loss-of-lock, thereby impairing GNSS positioning performance;
Jamming and Spoofing:Jamming disables positioning functionality mainly through signal suppression, while spoofing manipulates positioning results into errors by transmitting counterfeit navigation signals.
3. How important is cloud connectivity to future positioning architectures?
Cloud service has evolved from a convenience to a structural requirement. It aggregates data from dozens of regional reference stations, models atmospheric and orbital errors, and distributes real-time corrections to vehicles. This enables centimeter-level positioning with instant convergence across city-scale coverage, breaking the distance limits of single-base-station RTK.
Alongside NRTK, the cloud supports scalable SSR correction distribution for PPP-RTK, ionospheric quality monitoring,integrity monitoring, and over-the-air updates.
4. How should engineers validate positioning robustness across global markets?
Engineers should validate global positioning robustness through lab simulation, multi-terrain road testing, and long-term performance iteration.
Use signal simulators to carry out signal simulation verification for different global regions and scenarios, as well as playback verification of actual collected data.
Real-road tests span all target geographic zones to measure positioning continuity, ambiguity resolution performance and anti-interference stability under local environmental features.
Continuously iterate and optimize performance based on mass production field performance.
Don’t miss Dr. Hongyang Zhang’s presentation ‘Chip-Cloud Integration: How Co-Designed GNSS Receivers and Correction Services Enable Robust Vehicle Positioning‘ at AutoSens Europe this year!
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