GNSS smartphones positioning: advances, challenges, opportunities, and future perspectives

Starting from 2016,the raw Global Navigation Satellite System(GNSS)measurements can be extracted from the Android Nougat(or later)operating systems.Since then,GNSS smartphone positioning has been given much attention.A high number of related publications indicates the importance of the research in this field,as it has been doing in recent years.Due to the cost-effectiveness of the GNSS smartphones,they can be employed in a wide variety of applications such as cadastral surveys,mapping surveying applications,vehicle and pedestrian navigation and etc.However,there are still some challenges regarding the noisy smartphone GNSS observations,the environment effect and smartphone holding modes and the algorithm development part which restrict the users to achieve high-precision smartphone positioning.In this review paper,we overview the research works carried out in this field with a focus on the following aspects:first,to provide a review of fundamental work on raw smartphone observations and quality assessment of GNSS observations from major smart devices including Google Pixel 4,Google Pixel 5,Xiaomi Mi 8 and Samsung Ultra S20 in terms of their signal strengths and carrier-phase continuities,second,to describe the current state of smartphone positioning research field until most recently in 2021 and,last,to summarize major challenges and opportunities in this filed.Finally,the paper is concluded with some remarks as well as future research perspectives.

A method of improving ambiguity fixing rate for post-processing kinematic GNSS data

Global Navigation Satellite System precise positioning using carrier phase measurements requires reliable ambiguity resolution.It is challenging to obtain continuous precise positions with a high ambiguity fixing rate under a wide range of dynamic scenes with a single base station,thus the positioning accuracy will be degraded seriously.The Forward-Backward Combination(FBC),a common post-processing smoothing method,is simply the weighted average of the positions of forward and backward filtering.When the ambiguity fixing rate of the one-way(forward or backward)filter is low,the FBC method usually cannot provide accurate and reliable positioning results.Consequently,this paper proposed a method to improve the accuracy of positions by integrating forward and backward AR,which combines the forward and backward ambiguities instead of positions-referred to as ambiguity domain-based integration(ADBI).The purpose of ADBI is to find a reliable correct integer ambiguities by making full use of the integer nature of ambiguities and integrating the ambiguities from the forward and backward filters.Once the integer ambiguities are determined correctly and reliably with ADBI,then the positions are updated with the fixing ambiguities constrained,in which more accurate positions with high confidence can be achieved.The effectiveness of the proposed approach is validated with airborne and car-borne dynamic experiments.The experimental results demonstrated that much better accuracy of position and higher ambiguity-fixed success rate can be achieved than the traditional post-processing method.