LSRR-LA: AN ANISOTROPY-TOLERANT LOCALIZATION ALGORITHM BASED ON LEAST SQUARE REGULARIZED REGRESSION FOR MULTI-HOP WIRELESS SENSOR NETWORKS

LSRR-LA: An Anisotropy-Tolerant Localization Algorithm Based on Least Square Regularized Regression for Multi-Hop Wireless Sensor Networks

As is well known, multi-hop range-free localization algorithms demonstrate pretty good performance in isotropic networks in which sensor nodes Lunch Bag distribute evenly and densely.However, these algorithms are easily affected by network topology, causing a significant decrease in positioning accuracy.To improve the localization performance in an

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