Research On Ship Indoor Navigation Algorithms Based On MEMS Inertial Sensors

With the rapid development of shipping industry, ships are becoming large-scale. Large cruises and offshore passenger ships are described as "floating cities", which are characterized by internal complicated structures and multi-decks. Complex inner structures have an effect on routine work and emergency response, such as fire fighting, life-saving, oil spill response, etc. Especially the darkness, smoke, fire, power outages triggered by fire disaster pose a great threat to firefighters. Based on MEMS (Micro-Electronic-Mechanical System) inertial sensors, this thesis endeavors to design the SINS (Ship Indoor Navigation System) and related algorithms in line with the ship characteristics to help achieve ship indoor navigation.To begin with, the features of PNS (Pedestrian Navigation System) are analyzed. Aiming at the pedestrian walking characteristics, the paper simplifies INS (Inertial Navigation System), and analyzes the error transfer characteristics of inertial sensors as well. The variation of the parameters during walking motion is revealed through the walking experiments. Moreover, the features of SINS are analyzed theoretically and experimentally. A method for ship attitude measurement that adopting MEMS AHRS (Attitude and Heading Reference System) is proposed, and a3D visualization system of ship attitude is developed as well. The effects of ship motion on indoor navigation are analyzed with regards to the differences between indoor environment on board and land, and also the SINS technology strategy is proposed. In addition, the technical architectures of SINS are designed out and the navigation algorithms are developed. A precise zero-velocity detection algorithm based on three axes angular velocity and sliding window is put forward to solve the error-updating problem of traditional algorithm. A gait recognition algorithm on the basis of dynamic time warping is brought out to solve the problem of the traditional algorithm on the insufficiency of gait recognition. The author also brings out the altitude error correction algorithm, and utilizes gait and map information to reduce the altitude error by95%on the centimeter-level, which occurs in the navigation with multi-decks on board. Finally, the SINS software named by "SmartWalking" is developed based on the research results. After the experiments on Yukun Ship belonging to Dalian Maritime University, the performance of navigation algorithms is testified.The study extends the application field of indoor navigation system. In addition, SINS not only enhances the capabilities of emergency response, but also realizes the crew’s autonomous navigation, monitoring and LBS (Local Based Service) on board.