An improved wide-lane ambiguity resolution method for kinematic smartphone positioning

Yan Zhang, Yang Jiang, Yuting Gao, Shuai Guo, Yang Gao
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Abstract

The release of GNSS raw data on Android smartphones provides the potential for high-precision smartphone positioning using multi-constellation and multi-frequency signals. However, severe multipath and low observation quality in kinematic environments make double-differenced uncombined ambiguities difficult to resolve reliably. To address this, the paper proposes an improved wide-lane (WL) integer ambiguity resolution (IAR) method that combines integer rounding and the Least-Square AMBiguity Decorrelation Adjustment (LAMBDA) methods. The proposed method achieved fix rates of 57% to 70% in challenging environments, with an average improvement of 7 · 7% in horizontal positioning accuracy compared to the float solution. The traditional partial integer rounding method only improved accuracy by 1 · 1%.
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用于智能手机运动定位的改进型宽线性模糊解决方法
安卓智能手机上发布的全球导航卫星系统原始数据为利用多星座和多频率信号进行高精度智能手机定位提供了可能。然而,运动环境中严重的多径和较低的观测质量使得双差分非组合歧义难以可靠地解决。为解决这一问题,本文提出了一种改进的宽线(WL)整数模糊解决(IAR)方法,该方法结合了整数四舍五入和最小平方模糊解相关调整(LAMBDA)方法。在具有挑战性的环境中,所提出的方法实现了 57% 至 70% 的固定率,与浮动解决方案相比,水平定位精度平均提高了 7 - 7%。而传统的部分整数舍入法仅提高了 1 - 1% 的精度。
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