Incremental Localization Algorithm Based on Regularized Iteratively Reweighted Least Square

Considering that incremental localization is influenced by the heteroscedasticity problem caused by cumulative errors and the collinearity problem among nodes, this paper has proposed an incremental localization algorithm with consideration to cumulative error and collinearity problem. Using iteratively reweighted method, the algorithm reduces the influences of error accumulation and avoids collinearity problem between nodes with a regularized method. Simulation experiment results show that compared with the previous incremental localization algorithms the proposed algorithm can not only solve the problem of heteroscedasticity, but also obtain a localization solution with high accuracy. In addition, the method also takes into account the influence of collinearity on localization calculation in the process of locating, thus the method is suitable for different monitoring areas and has high adaptability.