In wireless networks, the position information of the individual devices has great value. For example, scientists often attach wireless tags on wild animals to study their population, migration and living habits. In deep forests, the GPS signal is generally too weak, and we will need to find another way to track the real-time positions of these animals. Another example is the localization in the cellular networks. Whenever people call 911, they need to report their location. However, it can be quite difficult to accomplish this trivial task in emergency. Imagine a person who just had an heart attack, dialed 911, and then passed out. In these cases, if the base station can localize the caller automatically, we will have larger chances to save more lives. There are various techniques that can be used to localize wireless devices. Taking the wireless sensor networks (WSNs) as an example, a small number of location-aware nodes are generally deployed, serving as reference nodes. The other nodes in the network can localize themselves by receiving the beacon signals from the reference nodes. This framework based on fixed reference nodes have two major defects. First, the localization accuracy is low due to the sparsity of reference nodes. Second, for large-scale WSNs, a huge number of reference nodes should be deployed to guarantee the coverage, which is uneconomic and lacks flexibility. An intuitive idea is to replace the fixed nodes with a small number of mobile ones, who can move on predefined trajectory and broadcast beacon signals periodically. These mobile nodes can be drones or automous underwater vehiculs, depending on our needs. Such a system can provide much better coverage at significantly reduced cost. In this presentation, Dr. Zijun Gong will talk about the system design, performance analysis, simulations and experiments for various application scenarios, including the drone-assisted localization in terrestrial WSNs, and the automous underwater vehicle-assisted time synchronization and localization in underwater acoustic networks.