GNSS/INS Integration with Partial-ZUPT for Land Vehicle Navigation

Jingxuan Su, Zheng Yao, Mingquan Lu
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Abstract

GNSS has important applications in land vehicle positioning services. However, in special harsh scenarios such as urban canyon with strong occlusion, the stability of the GNSS signal will be significantly reduced, and the positioning result usually has a lower update rate, such as 1HZ. Therefore, GNSS can be combined with the inertial navigation system (INS) to achieve higher update rate and more stable positioning. GNSS and INS can complement each other in signal frequency and positioning accuracy, so well-positioned results can be obtained even with less expensive devices. An integration positioning algorithm that can suppress the accumulation of positioning errors in the case of GNSS outage is proposed in this paper. The algorithm is based on a technique called Partial-ZUPT and a sliding window polynomial predictor. Traditional loosely coupled integration is used in the algorithm. The experimental results show that the quadratic positional error growth can be suppressed to the first-order growth by applying the algorithm when the GNSS positioning information is invalid. In terms of positioning accuracy, the integration algorithm only shows a cumulative position error of 0.5m after about 5 seconds of the GNSS outage, which is a significant improvement compared with the RMS error of about 1.5m in the traditional loosely coupled integration algorithm.
部分zupt集成GNSS/INS用于陆地车辆导航
GNSS在陆地车辆定位服务中有着重要的应用。但在城市峡谷强遮挡等特殊恶劣场景下,GNSS信号的稳定性会明显降低,定位结果通常更新率较低,如1HZ。因此,GNSS可以与惯性导航系统(INS)相结合,实现更高的更新速率和更稳定的定位。GNSS和INS在信号频率和定位精度上可以互补,因此即使使用较便宜的设备也可以获得较好的定位结果。提出了一种抑制GNSS中断情况下定位误差累积的集成定位算法。该算法基于一种称为Partial-ZUPT的技术和滑动窗口多项式预测器。算法采用传统的松耦合积分。实验结果表明,在GNSS定位信息无效的情况下,应用该算法可以将二次型位置误差增长抑制到一阶增长。在定位精度方面,积分算法在GNSS中断约5秒后的累计位置误差仅为0.5m,与传统松耦合积分算法的均方根误差约为1.5m相比,有了显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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