drive_ros_localize_inertial_navigation_system：仅基于IMU数据的惯性导航系统。 通过IMU数据集成创建里程表

这是韩国学生的一篇硕士论文 业内评价很高。论文研究了低成本IMU的检校、INS的初始对准方法、GPS/INS组合解算模型的公式推导等。对做惯导和组合导航的算法设计很有帮助

Principles of GNSS, Inertial, and Multi-Sensor Integrated Navigation Systems Principles of GNSS, Inertial, and Multi-Sensor Integrated Navigation Systems

In this tutorial, we provide principled methods to quantitatively evaluate the quality of an estimated trajectory from visual(-inertial) odometry (VO/VIO), which is the foundation of benchmarking the accuracy of different algorithms. First, we show how to determine the transformation type to use in trajectory alignment based on the specific sensing modality (i.e., monocular, stereo and visual-inertial). Second, we describe commonly used error metrics (i.e., the absolute trajectory error and the relative error) and their strengths and weaknesses. To make the methodology presented for VO/VIO applicable to other setups, we also generalize our formulation to any given sensing modality. To facilitate the reproducibility of related research, we publicly release our implementation of the methods described in this tutorial.

In this paper, we focus on the problem of motion tracking in unknown environments using visual and inertial sensors.We term this estimation task visual-inertial odometry (VIO), in analogy to the well-known visual-odometry problem. We present a detailed study of EKF-based VIO algorithms, by comparing both their theoretical properties and empirical performance. We show that an EKF formulation where the state vector comprises a sliding window of poses (the MSCKF algorithm) attains better accuracy, consistency, and computational efficiency than the SLAM formulation of the EKF, in which the state vector contains the current pose and the features seen by the camera. Moreover, we prove that both types of EKF approaches are inconsistent, due to the way in which Jacobians are computed. Specifically, we show that the observability properties of the EKF’s linearized system models do not match those of the underlying system, which causes the filters to underestimate the uncertainty in the state estimates. Based on our analysis, we propose a novel, real-time EKF-based VIO algorithm, which achieves consistent estimation by (i) ensuring the correct observability properties of its linearized system model, and (ii) performing online estimation of the camera-to-IMU calibration parameters. This algorithm, which we term MSCKF 2.0, is shown to achieve accuracy and consistency higher than even an iterative, sliding-window fixed-lag smoother, in both Monte-Carlo simulations and real-world testing. I

Global Navigation Satellite Systems, Inertial Navigation, and Integration, 3 edition English | 2013 | ISBN: 111844700X | ISBN-13: 9781118447000 | 608 pages | PDF | 20,3 MB An updated guide to GNSS, and INS, and solutions to real-world GNSS/INS problems with Kalman filtering Written by recognized authorities in the field, this third edition of a landmark work provides engineers, computer scientists, and others with a working familiarity of the theory and contemporary applications of Global Navigation Satellite Systems (GNSS), Inertial Navigational Systems, and Kalman filters. This book is intended for people who need a working knowledge of global navigation satellite systems (GNSSs), inertial navigation systems (INSs), and the Kalman filtering models and methods used in their integration. The book is designed to provide a usable, working familiarity with both the theoretical and practical aspects of these subjects. For that purpose, we include “realworld”problems from practice as illustrative examples. We also cover the more practical aspects of implementation: how to represent problems in a mathematical model, analyze performance as a function of model parameters, implement the mechanization equations in numerically stable algorithms, assess the computational requirements, test the validity of results, and monitor performance in operation with sensor data from Global Positioning System (GPS) and INS. These important attributes, often overlooked in theoretical treatments, are essential for effective application of theory to real-world problems.

Global Navigation Satellite Systems, Inertial Navigation, and Integration

GNSS与惯性及多传感器组合导航系统原理(第二版)英文原版pdf

惯导的同志们必备款，器件测试，西工大严恭敏老师的书电子版，严老师很严谨很可爱

由Volker Kempe所著的《Inertial MEMS Principles and Practice》的中英文版PDF文档。中文版名为《惯性MEMS器件原理与实践》。 中文版为扫描版，文字还算清晰；英文版为高清版，文字可拷。欢迎感兴趣的朋友下载。