Recent Advance of Auto Navigation in Indoor Scenarios

Dear Colleagues,

Location-based services (LBS) play a crucial role in supporting people's work, travel, factory production, and other social activities, becoming an indispensable part of transportation, the economy, and society. Central to LBS is positioning, a fundamental technology that underpins its functionality. In recent years, the Global Navigation Satellite System (GNSS) has matured significantly, offering reliable meter-level or even centimeter-level location services around the clock in open outdoor environments. However, GNSS is unsuitable for shielded environments such as tunnels and indoor spaces. To complement GNSS, indoor positioning technologies have rapidly developed, including UWB, Wi-Fi, BLE, visible light, vision, magnetic field, inertial navigation, etc. Despite these advancements, GNSS-denied environments present challenges due to the complex and diverse indoor space structures, where a single indoor positioning technology may struggle with issues such as low availability, poor accuracy, high system costs, and limited coverage. Consequently, achieving wide-area, high-precision indoor positioning at a low cost has become a prominent and urgent research focus in the field of navigation and positioning.

This Special Issue aims to introduce the latest breakthroughs in the theoretical research, technological innovation, and practical application of autonomous navigation in indoor scenarios and its future development prospects. Topics of interest include, but are not limited to, the following:

• Inertial navigation;
• Pedestrian, vehicle, bicycle, and drone dead reckoning;
• UWB, ultrasound, Wi-Fi, BLE, LED, visual, and magnetic positioning;
• Attitude and heading reference system;
• Gyroscope, accelerometer, and magnetometer calibration;
• Data-driven positioning method;
• Simultaneous localization and mapping (SLAM);
• Crowdsourcing-based mapping;
• Optimal estimation methods such as Kalman filtering and graph optimization.

Dr. Wenchao Zhang
Dr. Jian Kuang
Guest Editors

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• indoor positioning
• auto navigation
• dead reckoning
• matching positioning
• multi-source fusion