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A Performance Improvement Method for Low-Cost Land Vehicle GPS/MEMS-INS Attitude Determination

机译:低成本陆地车辆GPS / MEMS-INS姿态确定的性能改进方法

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摘要

Global positioning system (GPS) technology is well suited for attitude determination. However, in land vehicle application, low-cost single frequency GPS receivers which have low measurement quality are often used, and external factors such as multipath and low satellite visibility in the densely built-up urban environment further degrade the quality of the GPS measurements. Due to the low-quality receivers used and the challenging urban environment, the success rate of the single epoch ambiguity resolution for dynamic attitude determination is usually quite low. In this paper, a micro-electro-mechanical system (MEMS)—inertial navigation system (INS)-aided ambiguity resolution method is proposed to improve the GPS attitude determination performance, which is particularly suitable for land vehicle attitude determination. First, the INS calculated baseline vector is augmented with the GPS carrier phase and code measurements. This improves the ambiguity dilution of precision (ADOP), resulting in better quality of the unconstrained float solution. Second, the undesirable float solutions caused by large measurement errors are further filtered and replaced using the INS-aided ambiguity function method (AFM). The fixed solutions are then obtained by the constrained least squares ambiguity decorrelation (CLAMBDA) algorithm. Finally, the GPS/MEMS-INS integration is realized by the use of a Kalman filter. Theoretical analysis of the ADOP is given and experimental results demonstrate that our proposed method can significantly improve the quality of the float ambiguity solution, leading to high success rate and better accuracy of attitude determination.
机译:全球定位系统(GPS)技术非常适合用于姿态确定。然而,在陆地车辆应用中,经常使用具有低测量质量的低成本单频GPS接收机,并且在人口密集的城市环境中,诸如多径和卫星可见度低的外部因素进一步降低了GPS测量的质量。由于所使用的接收器质量低下以及充满挑战的城市环境,用于动态姿态确定的单个历时歧义分辨率的成功率通常很低。提出了一种微机电系统(惯性导航系统)辅助的模糊度解算方法,以提高GPS姿态确定性能,特别适用于陆地车辆姿态确定。首先,用GPS载波相位和代码测量值来增加INS计算的基线向量。这改善了精确度的歧义稀释度(ADOP),从而提高了无约束浮动解决方案的质量。其次,使用INS辅助歧义函数方法(AFM)进一步过滤和替换由大的测量误差引起的不希望的浮动解。然后通过约束最小二乘模糊解相关(CLAMBDA)算法获得固定解。最后,通过使用卡尔曼滤波器实现GPS / MEMS-INS集成。给出了ADOP的理论分析,实验结果表明,本文提出的方法可以显着提高浮点模糊解的质量,从而提高了成功率,提高了姿态确定的准确性。

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