In this paper, a new motion-based approach for Global Positioning System (GPS) integer ambiguity resolution is derived. The approach first represents the GPS sightline vectors in the body frame or the baseline vectors in the reference frame. The solution to this problem is always available as long as at least three non-coplanar baseline or sightline vectors exist. The body-frame sightline or reference-frame baseline observations are the sum of two vectors, one depending on the phase measurements and the other on the unknown integers. The vector containing the integer phases is then converted into an attitude independent observation using scalar checking, which leads to a problem that treats the integers as to-be-determined biases. The bias estimation problem is typically solved by using a batch process. In this paper, simple real time algorithms are developed based on both the extended Kalman filter and Unscented filter. Simulation results indicate that both algorithms provide accurate integer resolution in real time, but the Unscented filter is more robust to large initial condition errors and slow vehicle motions than the extended Kalman filter.

中文翻译：

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实时姿态独立GPS整数模糊度解析

本文提出了一种新的基于运动的全球定位系统（GPS）整数歧义分辨率解决方案。该方法首先在身体框架中表示GPS视线矢量，或者在参考框架中表示基线矢量。只要存在至少三个非共面基线或视线矢量，就始终可以使用此问题的解决方案。身体框架视线或参考框架基线观测值是两个向量的总和，一个向量取决于相位测量，另一个向量取决于未知整数。然后，使用标量检查将包含整数相位的向量转换为与姿态无关的观察，这会导致将整数视为待确定偏差的问题。偏差估计问题通常通过使用批处理来解决。在本文中，基于扩展卡尔曼滤波器和无味滤波器开发了简单的实时算法。仿真结果表明，这两种算法都可以实时提供准确的整数分辨率，但是Unscented滤波器比扩展的Kalman滤波器对较大的初始条件误差和缓慢的车辆运动更为鲁棒。