Standard GPS systems struggle in cities because tall buildings reflect, block, or distort satellite signals, creating erratic jumps in positioning known as urban-canyon errors, reports this article on ScienceDaily. The reflections delay the satellite signal’s travel time, undermining distance calculations and thus accuracy. According to NTNU’s doctoral fellow Ardeshir Mohamadi, “cities are brutal for satellite navigation.”
To solve this, the NTNU team developed SmartNav, a system that layers three key technologies:
- Carrier-phase-only positioning: instead of relying on standard code signals (which are vulnerable to reflection errors), SmartNav uses the radio-wave carrier’s phase to achieve much finer precision.
- Precise Point Positioning-Real Time Kinematic (PPP-RTK): this provides global correction data without needing dense local ground stations, lowering cost and enabling wide deployment.
- 3D building-model awareness: by integrating 3D urban maps (e.g., from Google), the system predicts how satellite signals bounce around architecture and filters out paths that produce errors (wrong-side-of-street problem).
Testing in Trondheim’s streets showed SmartNav delivering accuracy better than 10 cm in 90% of cases. That level of precision enables reliable navigation for autonomous vehicles, urban drones, delivery robots, and any system that needs accurate location in dense build-up zones.
Positioning systems for cities now require more than just stronger signals; they need smarter algorithms, city-aware mapping, wave analysis, and integrated correction services. SmartNav represents a shift from “good enough GPS” to high-confidence urban localization. The takeaway for engineers building autonomous infrastructure in cities is: accurate positioning is achievable but only when navigation systems account for the built environment, not ignore it.