Automatic Detection of Indoor and Outdoor Scenarios using NMEA Message Data from GPS Receivers

TL;DR

This paper proposes an automatic method to distinguish indoor from outdoor environments using NMEA data from GPS receivers, leveraging metrics like satellite count and signal quality for scenario detection.

Contribution

It introduces a novel approach utilizing GPS NMEA data metrics to accurately classify indoor and outdoor scenarios, validated through static testing and parameter verification.

Findings

Metrics like satellite count and signal quality differ significantly between indoor and outdoor scenarios.

The proposed method effectively classifies environments with high accuracy.

Validation confirms the reliability of the identified parameters for scenario detection.

Abstract

Detection of indoor and outdoor scenarios is an important resource for many types of activities such as multisensor navigation and location-based services. This research presents the use of NMEA data provided by GPS receivers to characterize different types of scenarios automatically. A set of static tests was performed to evaluate metrics such as number of satellites, positioning solution geometry and carrier-to-receiver noise-density ratio values to detect possible patterns to determine indoor and outdoor scenarios. Subsequently, validation tests are applied to verify that parameters obtained are adequate.