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Samsung · AI / ML · Filed Sep 4, 2025 · USPTO published Jun 18, 2026 · Jun 18 release

Samsung's New Patent Stops GPS from Going Haywire Inside Tunnels

GPS loses its mind the moment you enter a tunnel — and Samsung is filing patents to fix that with an AI system that detects the moment you go underground and compensates before your map goes haywire.

By · Updated · 3 min read

Samsung Patent: AI Tunnel Detection for GPS Navigation, figure from US 2026/0169173 A1
Figure from the official USPTO publication.
Publication number
US 2026/0169173 A1(US20260169173A1)
Applicant
Samsung Electronics Co., Ltd.
Filed · Published
Sep 4, 2025 · Jun 18, 2026
Inventors
Changwei Chen, Jong Ki Lee, Suk Hwan Lim
Status when we published
Waiting for an examiner
Document
20 claims
US classification
342/357.31
Parent application
Claims priority from a provisional application 63733925 (filed Dec 13, 2024)
AI vision

What Samsung's tunnel-detection GPS fix actually does

Imagine you're driving through a city and you enter a tunnel. Your phone's GPS signal drops out, your navigation app freezes or puts you in the wrong lane, and by the time you emerge on the other side, the map is scrambling to catch up. It's a frustratingly common problem.

Samsung's patent describes an AI system built into your phone that watches the quality of incoming GPS signals and uses that pattern to figure out — on its own — when you've entered a tunnel. Once it detects you're underground, it can switch the phone into a mode that doesn't rely on satellite signals that are no longer arriving cleanly.

The clever part is a self-checking mechanism: the AI compares its own tunnel verdict against a separate calculation from the raw signal data. If the two agree, the AI stays active. If they diverge, the system can dial the AI back down — so a one-off bad signal in an open field doesn't fool your phone into thinking you've gone underground.

How the AI model checks and adjusts its own confidence

The patent describes a method running on a phone (called a UE, or user equipment in wireless standards language) that continuously monitors incoming GNSS signals — the satellite broadcasts that GPS is built on.

When a satellite signal arrives, an AI model analyzes its characteristics to produce a tunnel detection result: essentially a judgment call about whether the phone is currently inside a tunnel. That result is then compared against a separate value calculated directly from the raw signal — acting as a sanity check on the AI's conclusion.

Based on how well those two outputs agree, the system decides whether to keep using the AI model for the next incoming signal or to disable it temporarily. This feedback loop is designed to prevent the AI from confidently reaching wrong conclusions in edge cases — like signal interference in a parking garage or a dense urban canyon.

  • Receives satellite signal tied to the phone's current position
  • Runs AI model to decide if a tunnel is present
  • Cross-checks that AI output against a signal-based calculation
  • Enables or disables the AI for the next signal cycle accordingly
  • Feeds the tunnel detection result into position estimation

What this means for navigation in cities and underground

GPS dead zones in tunnels are one of the most persistent navigation headaches on Android phones, and Samsung is the world's largest Android phone maker. A system like this, baked directly into the phone's signal-processing layer, could meaningfully reduce the lag and location errors that drivers and transit riders experience every day going underground.

The self-correcting confidence check is the detail worth watching. Many tunnel-detection approaches exist, but ones that can turn themselves off when uncertain are less common — and that matters in real-world city environments where signals are messy even above ground. If this ends up in Samsung's Galaxy navigation stack, it's the kind of quiet improvement that users notice without ever knowing what fixed it.

Source: US 2026/0169173 A1 at the USPTO (PDF). Full patent text and figures are in the official publication.

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