Dissertation: The benefits of adaptive techniques in sensor network localization – aid for localization challenges in varying outdoor conditions
In his dissertation, Jari Luomala explored the challenges in localization in outdoor WSNs and ways to overcome these challenges. In WSNs, the accurate and robust localization of sensor nodes is fundamental to system performance and many sensor network applications. However, locating low-cost and resource-constrained sensor nodes is challenging outdoors.
“The research explored the effects of various factors on localization and aimed to find ways to mitigate these effects. The aim is to improve localization accuracy, considering the cost-effectiveness of solutions”, Luomala says.
The commonly used GNSS-based localization is not a cost-effective solution for locating sensor nodes on a large scale. Its energy consumption and costs are too high for resource-constrained sensor nodes that often need to operate battery-powered for a long time.
“Therefore, we must develop localization algorithms and techniques that are suitable for nodes with limited energy, computational power, and memory”, Luomala says.
Varying weather and environmental conditions a key challenge
Many WSNs operate outdoors and are exposed to varying weather and environmental conditions. They may introduce errors in range estimates and reference node locations, which are the key elements in anchor- and range-based localization. RSSI-based localization, that is based on radio signal strength, is a cost-effective technique for locating sensor nodes. However, it is sensitive to varying conditions.
“Various environmental factors and weather conditions affect node hardware and radio signal propagation. Unless their effects are considered, ranging and localization accuracy vary with conditions. For example, temperature variation may have a significant effect”, Luomala explains.
The reference node locations that are utilized in localization are often based on the GNSS. They are prone to the effects of conditions, which adds to the inaccuracy of locations. This reduces localization accuracy further.
Adaptive techniques to aid in localization challenges
The dissertation research proposed adaptive techniques for improving RSSI-based ranging and GNSS-based reference localization. However, the errors due to weather and environmental conditions cannot be completely removed. Therefore, we developed adaptive localization algorithms and techniques, which adapt to changing conditions and are robust to ranging errors and factors related to network topology.
“Localization error is largely determined by the joint effect of distance estimation error and localization geometry. As they both depend on the reference nodes used, special attention needs to be paid to reference node selection”, Luomala says.
The solutions proposed in the dissertation are adaptive, robust, and cost-effective. They improve the localization accuracy of resource-constrained sensor nodes in outdoor WSNs.
More information
MSc Jari Luomala defends his doctoral dissertation “Adaptive Anchor- and Range-Based Localization for Outdoor Wireless Sensor Networks” on Friday, 19 September 2025 at 12 o’clock at the Kokkola University Consortium Chydenius. The opponent is Professor Riku Jäntti (Aalto University) and the custos is Professor Ismo Hakala (University of Jyväskylä).
The dissertation “”Adaptive Anchor- and Range-Based Localization for Outdoor Wireless Sensor Networks” is available in the JYX publication archive.
