Sensors have always been the core of any system used in positioning, navigation, and mapping. Mobile sensing in particular is the main component for such systems in land, airborne, and marine applications. In recent decades, it has become a standard tool in those mobile systems to integrate different sensors that complement each other, hence adding more capabilities to the used system. These sensors include GNSS, inertial sensors (accelerometers and gyroscopes), magnetometers, compasses, odometers, vision-based sensors, LiDAR, scanners, etc. Although sensor integration has been implemented to improve overall system performance, it has introduced lots of challenges due to the added system complexities. This has led researchers to investigate several aspects such as sensor synchronization, data fusion, signal processing, sensor error models, integration schemes, and optimal estimation techniques. Moreover, with the advances in sensor technology, sensors costs are lower, and their sizes are smaller. This has come with the price of large sensor errors, which again has motivated researchers to investigate more approaches to overcome this issue.