A Robust Diffusion Estimation Algorithm with Self-Adjusting Step-Size in WSNs

作者：Shao, Xiaodan; Chen, Feng^*; Ye, Qing; Duan, Shukai

来源：Sensors (Switzerland), 2017, 17(4): 824.

DOI：10.3390/s17040824

• robust diffusion estimation
• self-adjusting step-size
• non-Gaussian noise
• wireless sensor networks

In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in a distributed manner. This paper proposed a robust diffusion estimation algorithm based on a minimum error entropy criterion with a self-adjusting step-size, which are referred to as the diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has a fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS algorithm with the diffusion minimum error entropy (DMEE) algorithm, an Improving DMEE-SAS algorithm is proposed for a non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.

• 出版日期2017-4
• 单位西南大学