Survey Of Wireless Sensor Networks Estimation Problem Based On Consensus-based Kalman Filtering Algorithm

Wireless sensor networks (WSN) is currently a top research field with a wide range of applications. Since the limitations of single sensor's energy, storage and processing bring challenging issues including low stability, poor reliability and precision, information fusion technology can be an effective approach to address these problems and has caused great concern of scholars. Information fusion technology is a highly integrated multi-disciplinary research field and in this paper, for the characteristics of wireless sensor networks, we study the Kalman filter fusion algorithm based on consensus by combining wireless sensor networks with information fusion algorithm.In the first place, this paper introduces a consensus-based distributed filtering algorithm. Aiming to the problem of network packet-dropping in the practical application, we focus on the distributed filtering algorithm with packet-dropping. By the theoretical analysis, we give a sufficient condition for the convergence of the estimation error system. We compare our algorithm with a classical filtering one by some simulations in ideal and packet-dropping cases, respectively. The results show that our algorithm does better filtering in the packet-dropping case. In response to this problem, three schemes of improvement are presented and simulation results show the effectiveness. Secondly, in order to reduce the network energy consumption under the circumstances of maintaining certain precision, the proposed algorithm is introduced into contain network structure. Two contain strategies are put forward, containing big degree nodes and random node. Their tracking precision and network synchronization are compared through simulation. Finally, a consensus-based UKF algorithm applying in nonlinear system is introduced. The result of comparing traditional EKF and UKF with our algorithm indicates the latter has good effect.