关键词: ANFIS GNSS INS INS/GNSS integration MEMS-IMU RISS autonomous vehicle navigation machine learning

来  源:   DOI:10.3390/s24061985   PDF(Pubmed)

Abstract:
Autonomous vehicles (AVs) require accurate navigation, but the reliability of Global Navigation Satellite Systems (GNSS) can be degraded by signal blockage and multipath interference in urban areas. Therefore, a navigation system that integrates a calibrated Reduced Inertial Sensors System (RISS) with GNSS is proposed. The system employs a machine-learning-based Adaptive Neuro-Fuzzy Inference System (ANFIS) as a novel calibration technique to improve the accuracy and reliability of the RISS. The ANFIS-based RISS/GNSS integration provides a more precise navigation solution in such environments. The effectiveness of the proposed integration scheme was validated by conducting tests using real road trajectory and simulated GNSS outages ranging from 50 to 150 s. The results demonstrate a significant improvement in 2D position Root Mean Square Error (RMSE) of 43.8% and 28% compared to the traditional RISS/GNSS and the frequency modulated continuous wave (FMCW) Radar (Rad)/RISS/GNSS integrated navigation systems, respectively. Moreover, an improvement of 47.5% and 23.4% in 2D position maximum errors is achieved compared to the RISS/GNSS and the Rad/RISS/GNSS integrated navigation systems, respectively. These results reveal significant improvements in positioning accuracy, which is essential for safe and efficient navigation. The long-term stability of the proposed system makes it suitable for various navigation applications, particularly those requiring continuous and precise positioning information. The ANFIS-based approach used in the proposed system is extendable to other low-end IMUs, making it an attractive option for a wide range of applications.
摘要:
自动驾驶汽车(AV)需要精确的导航,但是,全球导航卫星系统(GNSS)的可靠性可能会因城市地区的信号阻塞和多径干扰而降低。因此,提出了一种将校准的低惯性传感器系统(RISS)与GNSS集成在一起的导航系统。该系统采用基于机器学习的自适应神经模糊推理系统(ANFIS)作为一种新颖的校准技术,以提高RISS的准确性和可靠性。基于ANFIS的RISS/GNSS集成在此类环境中提供了更精确的导航解决方案。通过使用50至150s的实际道路轨迹和模拟GNSS中断进行测试,验证了所提出的集成方案的有效性。结果表明,与传统的RISS/GNSS和调频连续波(FMCW)雷达(Rad)/RISS/GNSS组合导航系统相比,2D位置均方根误差(RMSE)显着提高了43.8%和28%。分别。此外,与RISS/GNSS和Rad/RISS/GNSS组合导航系统相比,2D位置最大误差分别提高了47.5%和23.4%,分别。这些结果揭示了定位精度的显著提高,这对于安全高效的导航至关重要。所提出的系统的长期稳定性使其适用于各种导航应用,特别是那些需要连续和精确的定位信息。所提出的系统中使用的基于ANFIS的方法可扩展到其他低端IMU,使其成为一个广泛的应用有吸引力的选择。
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