Projects: FuzLoc - Localization in Harsh Environments

This project aims to develop a system for localizing mobile resource contrained nodes in radio-challenged environments. The key idea is that fuzzy logic is used to encode the inherent errors in ranging, to produce the location as a pair of fuzzy numbers (which denote an area). Ranging is a widely used technique where the distance between two nodes is inferred from the RF signal strength between them. However, the relationship between RSS and distance is highly random in such environments as indoor urban office building, places with a lot of concrete or metallic objects etc. In order to overcome these drawbacks, we propose FuzLoc, an anchor based range based algorithm suitable for mobile nodes in such environments. "Bins" are created in order to hold the gathered RSS and distance values. These bins are used to construct "rules", which are a common tool in fuzzy logic.

Anchors create these rules and nodes use these rules to localize themselves. Multilateration is performed in the fuzzy logic domain using a fuzzy variant of the popular Newton-Rhapson method. Since this procedure requires atleast 2 anchors (which is a luxury when the percentage of anchors deployed is low), we propose the theoretical construct of "virtual anchors" which are nothing but fixed and virtual anchors situated at the center of a cell - the deployment area is assumed to be divided into many cells in the form of a grid.

Extensive evaluation and simulation (using the DoI model to simulate challenging environments) proves that FuzLoc outperforms previous Monte Carlo based methods such as MCL and MSL.



  • H. Chenji, R. Stoleru, "Towards Accurate Mobile Sensor Network Localization in Noisy Environments," major review IEEE Transactions on Mobile Computing (TMC), 2011.
  • H. Chenji, R. Stoleru, "Mobile Sensor Network Localization in Harsh Environments," Proceedings of IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), 2010.

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