Dead Reckoning

Dead reckoning (DR) is a method for estimating position and orientation using only sensor data from the moving object, primarily inertial measurement units (IMUs). Current research focuses on mitigating DR's inherent drift through sensor fusion techniques, incorporating data from sources like cameras, radar, and other positioning systems (e.g., UWB, BLE, WiFi) within frameworks such as Kalman filters, factor graph optimization, and deep learning models (e.g., Res2Net, LSTM). These advancements are crucial for improving the accuracy and reliability of positioning in various applications, including pedestrian navigation, robotics, and autonomous vehicle localization, particularly in GPS-denied environments.