Distributed robust RLS estimation algorithm over sensor networks - Kaikai KANG; Zhaoting LIU; Yingbiao YAO (Dianxin kexue)
In the parameter estimation of the sensor network, there may be impact noise or pulse interference in the measurement environment, which leads to the outliers that greatly deviate from the actual range, so that the effective parameter estimation problem can't be obtained. A distributed RLS estimation algorithm based on node cooperation and robustness was proposed. The characteristic of interference or attack on a node is usually sporadic (ie, sparse) for a period of time was utilized, ℓ1norm was introduced to cost function. The outliers which may exist in the measurement data were identified and eliminated, and the interaction between the nodes of the network was utilized to further improve the performance of the parameter estimation. The computer simulation experiments show that the algorithm has good estimation performance.