Incremental Localization Algorithm Based on Regularized Iteratively Reweighted Least Square - Yan Xiaoyong; Yang Zhong; Liu Yu; Xu Xiaoduo; Li Huijun (Foundations of Computing and Decision Sciences, 2016)
Incremental localization algorithm is a distributed localization method with excellent characteristics for wireless network. However, its estimated result is generally influenced by the heteroscedasticity arising from cumulative errors and the collineation among anchor nodes. We have proposed a novel incremental localization algorithm with consideration to cumulative errors and collinearity among anchors. Using iteratively reweighted and regularized method, the algorithm reduces the influences of errors accumulation and avoids collinearity problem between anchors. Simulation experiment results show that compared with the previous incremental localization algorithms, the proposed algorithm obtains a localization solution which not only has high accuracy but also high stability. Therefore, the proposed algorithm is suitable for different deployment environments and has high adaptability.