1. Course Introduction
Navigation technology is widely deployed on various land, sea, air and space unmanned platforms, and has seen rapid expansion from high-end national defense equipment to civilian sectors. Inertial and integrated navigation algorithms are among the core enabling technologies in this field.
Supported by typical cases and navigation program demonstrations, this course illustrates the fundamental algorithms and underlying principles of inertial and integrated navigation. Simulation and field data are adopted to reinforce learners’ comprehension of relevant algorithms. It enables participants to proficiently grasp the basic theories and application approaches of inertial and integrated navigation algorithms in an efficient manner, bridging theory and practice and allowing learners to experience the value of advanced algorithm development and hands-on implementation.
The course centers on two major technical modules:
1.1 Inertial Navigation Algorithms
This module consists of fundamentals and performance analysis of inertial navigation algorithms.
(1) Fundamentals of Inertial Navigation Algorithms
It elaborates mathematical representations of carrier attitudes and corresponding conversion algorithms and programs, covering Euler angles, direction cosine matrices, quaternions and equivalent rotation vectors, and derives the differential equations of carrier attitudes. Taking dead reckoning navigation of underwater vehicles as a typical case, this section conducts simulation analysis based on carrier attitude and velocity data, and explains algorithms and programs related to commonly used navigation coordinate systems, representation of latitude, longitude and altitude, as well as position updating.
(2) Analysis of Inertial Navigation Algorithms
Combined with practical cases, this part presents the differential equations of attitude, velocity and position for inertial navigation in the inertial frame, Earth frame and local navigation frame. It also introduces numerical integration algorithms and program implementation for inertial navigation differential equations, along with algorithm simulation and analysis. Both simulation and field data are used to deepen the understanding of inertial navigation algorithms.
1.2 Multi-source Integrated Navigation Algorithms
This module includes fundamentals and engineering applications of inertial-based integrated navigation.
(1) Fundamentals of Inertial-based Integrated Navigation Algorithms
This section clarifies the concept of integrated navigation, the necessity of integrated navigation for various moving platforms, and the implementation tools. It also expounds the establishment of inertial navigation error models in integrated navigation systems, including differential equations for attitude errors, velocity errors, position errors and sensor errors.
(2) Applications of Inertial-based Integrated Navigation Algorithms
Targeting various land, sea and air moving carriers, this section conducts in-depth interpretation and hands-on practice of diverse integrated navigation algorithms. Based on inertial navigation error models, the state equations for integrated navigation filtering are established, and the observation equations are constructed using multi-source navigation information. The influence of state transformation on filtering performance of integrated navigation is analyzed.
The content covers key technologies and applications such as fine alignment of strapdown inertial navigation in integrated navigation, transfer alignment for precision airdrop platforms, loose and tight integrated navigation for UAV inertial/satellite systems, vehicle inertial/odometer integrated navigation, multi-sensor integrated navigation for unmanned underwater vehicles, and inertial/visual integrated navigation for unmanned platforms. Characteristics of integrated navigation filtering algorithms in different application scenarios are also summarized.
2. Course Features
Integration of Research and Teaching: The state transformation Kalman filter, an original research achievement of the research group, runs through all chapters. Comparative analysis is provided to demonstrate its technical advantages.
Combination of Theory and Practice: Open-source data and codes are provided for inertial navigation, fine alignment, transfer alignment, inertial/satellite integrated navigation, inertial/odometer integrated navigation, underwater inertial/Doppler integrated navigation and inertial/visual integrated navigation for unmanned platforms. Online programming exercises and virtual simulation training help learners integrate theoretical knowledge with practical skills.
Cross-domain Adaptability: Focusing on application scenarios of land, sea, air and space platforms, the course analyzes the cross-domain adaptability of initial alignment, inertial navigation and integrated navigation algorithms, so as to enhance learners’ capability of technology migration and complex problem solving.
Academic Globalization: Bilingual teaching in Chinese and English is adopted to broaden learners’ international academic horizons and facilitate academic exchanges and cooperation.
3. Target Audience and Course Objectives
This course is designed for science and engineering students, engineering technicians and interdisciplinary researchers. Through full-process training covering navigation system error analysis, algorithm optimization and programming practice, it helps learners connect theories with engineering applications and cultivate the capability to independently design algorithms for multi-source navigation systems.
4. Navigation as the Key, Exploring the Frontier of Intelligence
From theoretical formulas in laboratories to large-scale industrial applications, navigation technology has always been a cornerstone of the intelligent era. Join us for in-depth technical exploration. With codes as tools and innovation as the mission, let us jointly define the core orientation of next-generation positioning technology. Hand in hand, we will forge ahead and embark on a new chapter of the intelligent era.
