# Single-Baseline RTK Positioning Using Dual-Frequency GNSS Receivers Inside Smartphones
###### Abstract
For example, reference [2] deviates the analog signal acquired by the inner smartphone antenna directly to an external radio frequency front-end and GNSS receiver. This approach enabled them to apply a well-defined signal processing algorithm, avoiding the limitation of the internal chipset [3]. This test revealed the antenna gain to be the primary impediment to reliable positioning solution with a decrease of 11 dB in the carrier to noise ratio (C/N\({}_{0}\)) with respect to a survey-grade antenna. [PERSON] et al. [4] gave more details on the performances of smartphones for cm-accurate positioning. Firstly, they were able to extract raw GNSS observables thanks to a Broadcom customized software implemented in an Android test phone. Having access to both pseudorange and carrier-phase measurements, the authors performed a differential GNSS processing in a zero-baseline configuration. The observations acquired by a survey-grade antenna and re-irradiated to a smartphone within a RF enclosure allowed them to directly test the single frequency GNSS chipset in a single point positioning mode. The results showed an accuracy of less than 5 meters horizontally, a result coherent with the expected deviation of a survey-grade receiver [4]. Again, the multipath-induced phase errors from the antenna remained the main challenge for accurate smartphone positioning. A fundamental push for mobile positioning research came in May 2016, when, during the I/O conference, Google announced the release of a new Android operating system (OS), the Nougat 7.0. In this new implementation, accompanied by the Application Programming Interface level 24, Google gave the ability to developers and researchers to directly access the GNSS measures without having to use custom smartphones and external devices [5]. Today this feature still provides great interest for developers and researchers, as it gives them the opportunity to develop advanced processing algorithms using pseudoranges, Doppler shifts, and carrier-phase observations. Initially, the first empirical tests on these measurements were focused on the raw observables data evaluation. [PERSON] et al. [6] acquired raw static measurements with a Nexus 9 tablet in order to characterize the errors with respect to a reference solution performing the single difference approach considering only pseudoranges. They observed an error of around \(\pm\) 20 meters, a pseudorange rate noise within \(\pm\) 10 m/s, and a C/N\({}_{0}\) average value of approximately 10 dB-Hz lower than the geodetic receiver used as the reference solution [6]. In the same configuration the carrier-phase rate and Doppler data have also been characterized with a value within \(\pm\) 0.2 m/s. In [PERSON] et al. [7], the zero-baseline approach has been applied for the noise characteristics of the GNSS observation of a smartphone. At the same time, advanced post-processing algorithms have been applied with the aim of achieving centimeter positioning with smartphones [8; 9]. To do this, the first step was the development of parsers capable of extracting the raw measurements in a format more suited to geodetic post-processing. Some developers have created converters that can produce a Radio Technical Commission for Maritime Services (RTCM) or Receiver-Independent Exchange (RINEX) formats files that are useful for use in complex software (GEO++ RINEX logger and rinexON). Thanks to these applications, numerous research has been made to increment the positioning performances exploiting multi-constellation observations, real-time, and post-processing estimation procedures and signal processing. In reference [10], the authors were able to reach sub-meter accuracies with an on-board Doppler filtering algorithm and while considering the Satellite-based Augmentation Systems (SBAS).