Uncrewed flying drones have extensively used light-based queues for navigation, such as the ones obtained from color cameras and depth sensors. However, there are scenarios where vision modalities are limited, such as night-time, foggy skies, or heavy smoke. In these scenarios, audio can be employed instead: the drone itself constantly emits propeller noise that echolocation techniques can use to map the surrounding area and avoid obstacles. In this chapter, we present the state of the art of audio-based self-localization techniques employed for autonomous drone navigation. Additionally, several insights are provided in terms of what has been accomplished, current challenges, as well as some proposed next steps to be tackled in future work.