the ZUPT‐aided pedestrian inertial navigation, and methods have been proposed and demonstrated to be able to reduce the majority part of the errors caused by the ZUPTs. Chapter discusses efforts in improving the adaptivity of the pedestrian inertial navigation algorithm. Approaches including ML and Multiple‐Model (MM) methods are introduced. Chapter discusses other popular self‐contained aiding techniques, such as magnetometry, barometry, computer vision, and ranging techniques. Different ranging types, mechanisms, and implementations are covered in this chapter. Finally, in Chapter , the book concludes with a technological perspective on self‐contained pedestrian inertial navigation with an outlook for development of the Ultimate Navigation Chip (uNavChip).
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