| Wireless sensor networks (WSN) have been considered as promising tools for many location-dependent applications such as area surveillance, search and rescue, mobile tracking and navigation, etc. In addition, the geographic information of sensor nodes can be critical for improving network management, topology planning, packet routing and security. Although localization plays an important role in all those systems, itself is a challenging problem due to extremely limited resources available at each low-cost sensor node.;Previous research generally divides into two groups: range-based and range-free. Range-based methods are accurate but costly for requiring per-node ranging hardware, careful system calibration, or extensive environment profiling. Range-free approaches feature reduced overhead at the resource constrained sensor node side, nevertheless, with less accuracy depending on anchor density, network connectivity, event distribution, etc.;This thesis offers novel solutions to bridge the gap between low cost and high accuracy for range-free localization. In the first part, we explore uncontrolled event-driven localization that advances the state-of-the-art an important step towards a usable system. As the first to apply the concept of sequence to localize nodes, our designs significantly improve system flexibility by providing a trade-off between physical cost (anchors) and soft cost (events), a useful layer of abstraction that adopts different sensing modalities, and a potential option of achieving node positioning via natural ambient events.;In the second part, we focus on the challenging problem of localization with merely range-free sensing results. Different from binary proximity, we invent the signature distance as a metric that, for the first time, enables quantifying distance relationships among neighboring nodes with sub-hop resolution in a range-free manner. With little overhead, this metric can be conveniently applied for enhanced system accuracy. We further extend the discovery to mobile target tracking. By converting the tracking problem from sequential localization to a maximum likelihood shortest path searching in a graph, we demonstrate robust tracking under unreliable sensing and without complex movement modeling.;By investigating into two important branches of range-free localization - event-driven localization, and localization with local sensing - the research presented in this thesis aims at promoting the use of low-cost range-free solutions in real world applications. |
