Yong Chien Zheng, Harima Ken, Rubinov Eldar, McClusky Simon, Odolinski Robert
National School of Surveying, University of Otago, 310 Castle Street, Dunedin 9016, New Zealand.
Geomatic Innovation Research Group, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia.
Sensors (Basel). 2022 May 16;22(10):3772. doi: 10.3390/s22103772.
High-precision global navigation satellite system (GNSS) positioning and navigation can be achieved with carrier-phase ambiguity resolution when the integer least squares (ILS) success rate (SR) is high. The users typically prefer the float solution under the scenario of having a low SR, and the ILS solution when the SR is high. The best integer equivariant (BIE) estimator is an alternative solution since it minimizes the mean squared errors (MSEs); hence, it will always be superior to both its float and ILS counterparts. There has been a recent development of GNSSs consisting of the Global Positioning System (GPS), Galileo, Quasi-Zenith Satellite System (QZSS), and the BeiDou Navigation Satellite System (BDS), which has made precise positioning with Android smartphones possible. Since smartphone tracking of GNSS signals is generally of poorer quality than with geodetic grade receivers and antennas, the ILS SR is typically less than one, resulting in the BIE estimator being the preferred carrier phase ambiguity resolution option. Therefore, in this contribution, we compare, for the first time, the BIE estimator to the ILS and float contenders while using GNSS data collected by Google Pixel 4 (GP4) smartphones for short-baseline real-time kinematic (RTK) positioning. It is demonstrated that the BIE estimator will always give a better RTK positioning performance than that of the ILS and float solutions while using both single- and dual-frequency smartphone GNSS observations. Lastly, with the same smartphone data, we show that BIE will always be superior to the float and ILS solutions in terms of the MSEs, regardless of whether the SR is at high, medium, or low levels.
当整数最小二乘(ILS)成功率(SR)较高时,通过载波相位模糊度解算可实现高精度全球导航卫星系统(GNSS)定位与导航。在SR较低的情况下,用户通常更喜欢浮点解;而在SR较高时,则更喜欢ILS解。最佳整数同变(BIE)估计器是一种替代解决方案,因为它能使均方误差(MSE)最小化;因此,它总是优于其浮点和ILS对应方案。近年来,由全球定位系统(GPS)、伽利略系统、准天顶卫星系统(QZSS)和北斗导航卫星系统(BDS)组成的GNSS有了新发展,这使得使用安卓智能手机进行精确定位成为可能。由于智能手机对GNSS信号的跟踪质量通常比大地测量级接收机和天线要差,ILS SR通常小于1,这使得BIE估计器成为首选的载波相位模糊度解算选项。因此,在本论文中,我们首次将BIE估计器与ILS和浮点竞争者进行比较,同时使用谷歌像素4(GP4)智能手机收集的GNSS数据进行短基线实时动态(RTK)定位。结果表明,在使用单频和双频智能手机GNSS观测数据时,BIE估计器的RTK定位性能总是优于ILS和浮点解。最后,利用相同的智能手机数据,我们表明,无论SR处于高、中还是低水平,就MSE而言,BIE总是优于浮点和ILS解。