N
Neal Patwari
Researcher at Washington University in St. Louis
Publications - 199
Citations - 15339
Neal Patwari is an academic researcher from Washington University in St. Louis. The author has contributed to research in topics: Wireless sensor network & Wireless network. The author has an hindex of 46, co-authored 191 publications receiving 14263 citations. Previous affiliations of Neal Patwari include Google & Aalto University.
Papers
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Journal ArticleDOI
Locating the nodes: cooperative localization in wireless sensor networks
Neal Patwari,Joshua N. Ash,Spyros Kyperountas,Alfred O. Hero,Randolph L. Moses,Neiyer S. Correal,Neiyer S. Correal +6 more
TL;DR: Using the models, the authors have shown the calculation of a Cramer-Rao bound (CRB) on the location estimation precision possible for a given set of measurements in wireless sensor networks.
Journal ArticleDOI
Relative location estimation in wireless sensor networks
TL;DR: This work derives CRBs and maximum-likelihood estimators (MLEs) under Gaussian and log-normal models for the TOA and RSS measurements, respectively for sensor location estimation when sensors measure received signal strength or time-of-arrival between themselves and neighboring sensors.
Journal ArticleDOI
Radio Tomographic Imaging with Wireless Networks
Joey Wilson,Neal Patwari +1 more
TL;DR: A linear model for using received signal strength (RSS) measurements to obtain images of moving objects and mean-squared error bounds on image accuracy are derived, which are used to calculate the accuracy of an RTI system for a given node geometry.
Journal ArticleDOI
Distributed weighted-multidimensional scaling for node localization in sensor networks
TL;DR: A scalable, distributed weighted-multidimensional scaling (dwMDS) algorithm that adaptively emphasizes the most accurate range measurements and naturally accounts for communication constraints within the sensor network is introduced.
Proceedings ArticleDOI
On the effectiveness of secret key extraction from wireless signal strength in real environments
Suman Jana,Sriram Nandha Premnath,Michael R. Clark,Sneha Kumar Kasera,Neal Patwari,Srikanth V. Krishnamurthy +5 more
TL;DR: An environment adaptive secret key generation scheme that uses an adaptive lossy quantizer in conjunction with Cascade-based information reconciliation and privacy amplification is developed, which shows that the scheme performs the best in terms of generating high entropy bits at a high bit rate.