Networks of UAVs of Low Complexity for Time-Critical Localization

Future networks of unmanned aerial vehicles (UAVs) will be tasked to carry out ever-increasing complex operations that are time-critical and that require accurate localization performance, such as tracking the position of a malicious user. Since there is the need to preserve low UAV complexity while tackling the challenging goals of missions in effective ways, one key aspect is the UAV intelligence (UAV-I). The UAV's intelligence includes the UAV's capability to process information and make decisions, e.g., to decide where to sense and whether to delegate some tasks to other network entities. This paper overviews some existing signal processing techniques for distributed estimation and autonomous navigation of UAVs of low complexity. To this end, we show some of the needs of the UAVs for running efficient localization operations for time-limited missions, performed either as a team or individually. Further, we focus on different network configurations, which possibly include assistance with edge computing. We also discuss open problems and future perspectives for these settings.