Hamed Bastani

• Euclidean distance ratios between networked nodes can be represented by the weight values of a subset of multidimensional graph edges. Through acquiring the real world data measures, our approach aims to accurately realize the spatial relationship of such layout elements. In particular, this solution is tremendously useful for mobile robotics relative localization, geo-location dynamic data management platforms, wireless sensor networking, smart routing, and so forth. In this research, we employ chirp spread spectrum modulation enabled radio transceivers for proximity measurement of the network nodes as the bidirectional weight information of the graph edges. Physical link experiments confirm that this recent technology is adequately reliable against environmental distortions when employed for asynchronous round trip time of flight measurements. In order to achieve the best affordable accuracy and reach a high level of robustness against the estimation noise, the multidimensional scaling method is utilized. Implementation phase's outcome is a cooperative and proprioceptive self-constructive infrastructure, for a flexible any-time localization application.