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A motion-based integer ambiguity resolution method for attitude determination using the global positioning system (GPS)

机译:基于运动的整数模糊度解析方法,用于使用全球定位系统(GPS)进行姿态确定

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摘要

Loss of the satellite signal and noise disturbance will cause cycle slips to occur in the carrier phase observation of the attitude determination system using the global positioning system (GPS), especially in the dynamic situation. Therefore, in order to reject the error by cycle slips, the integer ambiguity should be re-computed. A motion model-based Kalman predictor is used for the ambiguity re-computation in dynamic applications. This method utilizes the correct observation of the last step to predict the current ambiguities. With the baseline length as a constraint to reject invalid values, we can solve the current integer ambiguity and the attitude angles, by substituting the obtained ambiguities into the constrained LAMBDA method. Experimental results demonstrate that the proposed method is more efficient in the dynamic situation, which takes less time to obtain new fixed ambiguities with a higher mean success rate.
机译:卫星信号的丢失和噪声干扰将导致在使用全球定位系统(GPS)的姿态确定系统的载波相位观测中出现周跳,特别是在动态情况下。因此,为了通过周跳消除误差,应该重新计算整数歧义。基于运动模型的卡尔曼预测器用于动态应用中的歧义重新计算。该方法利用对最后一步的正确观察来预测当前的歧义。以基线长度为拒绝无效值的约束,我们可以通过将获得的模糊度代入约束的LAMBDA方法来解决当前整数模糊度和姿态角。实验结果表明,该方法在动态情况下更有效,花费更少的时间获得具有较高平均成功率的新的固定歧义。

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