Land vehicle navigation based on inertial navigation system (INS) and odometers is a classical autonomous navigation application and has been extensively studied over the past several decades. In this work, we seriously analyze the error characteristics of the odometer (OD) pulses and investigate three types of odometer measurement models in the INS/OD integrated system. Specifically, in the pulse velocity model, a preliminary Kalman filter is designed to obtain accurate vehicle velocity from the accumulated pulses; the pulse increment model is accordingly obtained by integrating the pulse velocity; a new pulse accumulation model is proposed by augmenting the travelled distance into the system state. The three types of measurements, along with the nonhonolomic constraint (NHC), are implemented in the standard extended Kalman filter. In view of the motion-related pulse error characteristics, the multiple model adaptive estimation (MMAE) approach is exploited to further enhance the performance. Simulations and long-distance experiments are conducted to verify the feasibility and effectiveness of the proposed methods. It is shown that the standard pulse velocity measurement achieves the superior performance, whereas the accumulated pulse measurement is most favorable with the MMAE enhancement.

中文翻译：

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通过精确测量建模和多模型自适应估计的 INS/里程表陆地导航

基于惯性导航系统（INS）和里程表的陆地车辆导航是一种经典的自主导航应用，在过去的几十年中得到了广泛的研究。在这项工作中，我们认真分析了里程计（OD）脉冲的误差特性，并研究了 INS/OD 集成系统中的三种里程计测量模型。具体来说，在脉冲速度模型中，设计了一个初步的卡尔曼滤波器，以从累积的脉冲中获得准确的车辆速度；通过对脉冲速度进行积分，从而得到脉冲增量模型；通过将行进距离增加到系统状态，提出了一种新的脉冲累积模型。在标准扩展卡尔曼滤波器中实现了三种类型的测量以及非完整约束 (NHC)。针对运动相关的脉冲误差特性，采用多模型自适应估计（MMAE）方法进一步提升性能。进行仿真和长距离实验以验证所提出方法的可行性和有效性。结果表明，标准脉搏速度测量实现了优越的性能，而累积脉搏测量最有利于 MMAE 增强。