As the density of wireless, resource-constrained sensors grows, so does the need to choreograph their actions across both time and space. Recent advances in ultra-wideband RF communication have enabled accurate packet timestamping, which can be used to precisely synchronize time. Location may be further estimated by timing signal propagation, but this requires additional communication overhead to mitigate the effect of relative clock drift. This additional communication lowers overall channel efficiency and increases energy consumption. This article describes a novel approach to simultaneously localizing and time synchronizing networked mobile devices. An Extended Kalman Filter is used to estimate all devices' positions and clock errors, and packet timestamps serve as measurements that constrain time and overall network geometry. By inspection of the uncertainty in our state estimate, we can adapt the number of messages sent in each communication round to balance accuracy with communication cost. This reduces communication overhead, which decreases channel congestion and power consumption compared to traditional time of arrival and time difference of arrival localization techniques. We demonstrate the performance and efficiency of our approach using a real network of custom RF devices and mobile quadrotors.