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A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation

机译:用于车辆导航的多传感器紧密融合方法

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摘要

Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in their costs, the positioning performance of GNSS is expected to be significantly improved by fusing multi-sensors. In order to improve the continuity and reliability of the vehicle navigation system, we proposed a multi-sensor tight fusion (MTF) method by combining the inertial navigation system (INS), odometer, and barometric altimeter with the GNSS technique. Different fusion strategies were presented in the open-sky, insufficient satellite, and satellite outage environments to check the performance improvement of the proposed method. The simulation and real-device tests demonstrate that in the open-sky context, the error of sensors can be estimated correctly. This is useful for sensor noise compensation and position accuracy improvement, when GNSS is unavailable. In the insufficient satellite context (6 min), with the help of the barometric altimeter and a clock model, the accuracy of the method can be close to that in the open-sky context. In the satellite outage context, the error divergence of the MTF is obviously slower than the traditional GNSS/INS tightly coupled integration, as seen by odometer and barometric altimeter assisting.
机译:使用全球导航卫星系统(GNSS),由于GNSS信号的自然脆弱性,很难为复杂城市环境中的车辆导航提供连续和可靠的定位服务。随着传感器技术的飞速发展和成本的降低,通过融合多传感器,有望显着提高GNSS的定位性能。为了提高车辆导航系统的连续性和可靠性,我们提出了一种将惯性导航系统(INS),里程表和气压高度计与GNSS技术相结合的多传感器紧密融合(MTF)方法。在露天,卫星不足和卫星停电的环境中提出了不同的融合策略,以检查所提出方法的性能改进。仿真和实际设备测试表明,在开阔的天空环境下,传感器的误差可以正确估计。当GNSS不可用时,这对于传感器噪声补偿和位置精度改善很有用。在卫星不足的情况下(6分钟),借助气压高度计和时钟模型,该方法的准确性可以接近露天环境。在里程表和气压高度计辅助下,在卫星停运的情况下,MTF的误差发散明显比传统的GNSS / INS紧密耦合的集成要慢。

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