Array-based Hybrid RF-Acoustic High Precision High Reliability Indoor 3D Positioning for Energy-neutral Devices

Highly accurate and reliable indoor 3D positioning of low power or even energy-neutral devices is becoming increasingly important in new Internet-of-Things (IoT) related applications for the future digital society. For example, consider a warehouse where automated drones have to collect certain objects. To make this technology work properly, high precision and high reliability 3D positioning is needed over the entire indoor space for both the drones and the static objects. The drones must be able to navigate themselves even when they are in full motion. Moreover, the localisation must be done in the lowest power possible way to achieve longer flight times and to deal with the energy restriction of energy-neutral tags for the objects where it is impossible to add a battery for cost, form factor and sustainability reasons. In addition to these extreme energy limitations, accurate and reliable localisation of objects in dense environments such as a stacked pallet must be provided. Current technologies have good accuracy characteristics, but show a large variance and many outliers while there is not enough reliability across the entire 3D space. Therefore, this PhD focusses on reliable indoor positioning for energy-neutral devices by advancing and combining two very promising concepts, hybrid-signals (i.c. RF and acoustic) and scattered arrays, and by using a large amount of beacon nodes to locate many passive devices and moving objects.