The combined navigation system consisting of Global Positioning System (GPS) and Inertial Navigation System in a complementary mode assures an accurate, reliable, and continuous positioning capability in the navigation system. Because of problems such as dealing with a low-cost MEMS-based inertial sensors having a high level of uncertainty and imprecision, stochastic noise, a high-speed vehicle, high noisy real data, and long-term GPS signal outage during the real-time flight test, the advantage is taken for some approaches in different steps: (1) utilizing discrete wavelet transform technique to enhance the signal-to-noise ratio in raw and noisy inertial sensor signals and attenuate high-frequency noise as a preprocessing phase to prepare more accurate data for the proposed model and (2) employing adaptive neural subtractive clustering fuzzy inference system (ANSCFIS) which combines and extracts the best feature of adaptive neuro-fuzzy inference system (ANFIS), and the subtractive clustering algorithm with fewer rules than the ANFIS method, aiming to improve a more efficient, accurate, and especially a faster method which enhances the prediction accuracy and speeds up the positioning system. The achieved accuracies for the proposed model are discussed and compared with the extended Kalman filter (EKF), ANFIS, and ANSCFIS which are implemented and tested experimentally using a high-speed vehicle in three GPS blockages. The proposed model shows considerable improvements in high-speed navigation using low-cost MEMS-based inertial sensors in case of long-term GPS blockage.

中文翻译：

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小波自适应神经减法聚类模糊推理系统，增强低成本，高速INS / GPS导航系统

以互补模式由全球定位系统（GPS）和惯性导航系统组成的组合导航系统可确保导航系统中的准确，可靠和连续的定位能力。由于存在一些问题，例如处理具有高不确定性和不精确性的低成本，基于MEMS的惯性传感器，随机噪声，高速车辆，高噪声真实数据以及实时过程中长期GPS信号中断等问题，定时飞行测试，在不同步骤中采用了某些方法：（1）利用离散小波变换技术来增强原始和有噪声的惯性传感器信号中的信噪比，并衰减高频噪声作为预处理阶段，以为提出的模型准备更准确的数据；（2）采用自适应神经网络减法聚类模糊推理系统（ANSCFIS）结合并提取自适应神经模糊推理系统（ANFIS）的最佳特征，以及与ANFIS方法相比规则更少的减法聚类算法，旨在提高效率，准确性，特别是一种更快的方法，可以提高预测精度并加快定位系统的速度。讨论了所提出模型的精度，并与扩展卡尔曼滤波器（EKF），ANFIS，和ANSCFIS，它们是通过高速车辆在三个GPS障碍物中进行实验性实施和测试的。所提出的模型在长期GPS阻塞的情况下，使用低成本的基于MEMS的惯性传感器显示出高速导航方面的显着改进。