With the release of Android N, Google announced the availability of GNSS Raw data from the mobile phone. This opens a broader perspective for research, analysis, and enhancement of the positioning quality in mobile phones. With increasing applications based upon augmented reality, e-banking, e-health, etc., there is a rapid increase in the demand for precise positioning using the existing architecture of mobile devices. On one hand, error sources such as ionospheric error and multipath mitigation tend to degrade the quality of precise positioning in mobile phones. On the other hand, cycle slip introduced due to weaker carrier-phase signal makes the positioning in mobile phone code-phase dependent only. Now with the availability of GNSS raw data, researchers are getting the opportunity to analyze and develop new concepts to enhance the carrier-phase positioning into a mobile phone. The approach presented in this paper is to emulate the smartphone and understand the effect of inducing noise in Pseudorange and Carrier phase artificially. The GNSS data recorded from smartphone directly cannot be manipulated to analyze the role of e.g. cycle slip in positioning accuracy quantitatively. Secondly, due to the hardware limitation, tracking inside the smartphone cannot be controlled which makes it difficult for researchers to play round with the GNSS data. Based upon the statistical analysis performed on the code and carrier residual from the smartphone, a high quality GNSS data was degraded. Results presented in the paper clearly indicates that the degradation of positioning accuracy due to the presence of noise introduced in the Carrier phase and Pseudorange. The first section gives user an understanding with state of the art positioning technique which is currently used in smartphones. Section 2 will give detailed description about data logging setup and techniques for inducing artifacts for emulating smartphone. In the following section results and analysis with different scenarios are discussed. In the final section paper will conclude the future possibilities and the extension of the work.    «

With the release of Android N, Google announced the availability of GNSS Raw data from the mobile phone. This opens a broader perspective for research, analysis, and enhancement of the positioning quality in mobile phones. With increasing applications based upon augmented reality, e-banking, e-health, etc., there is a rapid increase in the demand for precise positioning using the existing architecture of mobile devices. On one hand, error sources such as ionospheric error and multipath mitigatio...    »