| Abstract |
Indoor navigation and positioning, as an important cornerstone and one of the key technologies of urban digital transformation, plays a crucial role in the development and construction of smart cities. However, due to the complex and ever-changing indoor environment, spatial structure layout, indoor pedestrian activities, etc., achieving accurate, reliable and universal indoor positioning to meet the needs of mass positioning and effectively promote the development of smart cities still faces great challenges. With the advantages of the dead reckoning positioning method based on micro-inertial measurement units (MIMU), including small size, low cost, strong autonomy and high real-time performance, as well as the widespread coverage of existing Wi-Fi signals that do not require additional equipment deployment, indoor positioning technology based on MIMU and Wi-Fi has gained significant attention for its extensive research value and significance. The indoor positioning methods based on MIMU and Wi-Fi are mainly reviewed. Firstly, the principle of MIMU-based indoor positioning methods is classified and explained, and the problems and research status of MIMU- based indoor positioning are summarized. Secondly, the limitations and challenges of Wi-Fi-based indoor positioning methods are analyzed, with a focus on summarizing the current research status of machine-learning-based Wi-Fi fingerprint indoor positioning methods. Thirdly, the existing fusion positioning methods based on MIMU and Wi-Fi are systematically compared and analyzed by considering their advantages, disadvantages, and applications respectively. Finally, the future development trends of MIMU and Wi-Fi based positioning methods are prospected. © 2024 China Astronautic Publishing House Co Ltd. All rights reserved. |
