ArticleSensors (Basel, Switzerland)2023
GNSS Observation Generation from Smartphone Android Location API: Performance of Existing Apps, Issues and Improvement.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A Multi-Modal Dataset for Automated Phenological Stage Mapping in Actinidia chinensis.Scientific data · 2026Article
- RAIM and Failure Mode Slope: Effects of Increased Number of Measurements and Number of Faults.Sensors (Basel, Switzerland) · 2023Article
- Stochastic Modeling of Smartphones GNSS Observations Using LS-VCE and Application to Samsung S20.Sensors (Basel, Switzerland) · 2023Article
- Static Positioning under Tree Canopy Using Low-Cost GNSS Receivers and Adapted RTKLIB Software.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
3 authors.
Funding
Abstract
Precise position information available from smartphones can play an important role in developing new location-based service (LBS) applications. Starting from 2016, and after the release of Nougat version (Version 7) by Google, developers have had access to the GNSS raw measurements through the new application programming interface (API), namely android.location (API level 24). However, the new API does not provide the typical GNSS observations directly (e.g., pseudorange, carrier-phase and Doppler observations) which have to be generated by the users themselves. Although several Apps have been developed for the GNSS observations generation, various data analyses indicate quality concerns, from biases to observation inconsistency in the generated GNSS observations output from those Apps. The quality concerns would subsequently affect GNSS data processing such as cycle slip detection, code smoothing and ultimately positioning performance. In this study, we first investigate algorithms for GNSS observations generation from the android.location API output. We then evaluate the performances of two widely used Apps (Geo++RINEX logger and GnssLogger Apps), as well as our newly developed one (namely UofC CSV2RINEX tool) which converts the CSV file to a Receiver INdependent Exchange (RINEX) file. Positioning performance analysis is also provided which indicates improved positioning accuracy using our newly developed tool. Future work finding out the potential reasons for the identified misbehavior in the generated GNSS observations is recommended; it will require a joint effort with the App developers.
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