Distributed Fusion Estimation Based on Robust Kalman Filtering for 3D Spatial Positioning System

Because of the requirements of growing measurement scale, the issue of the networked high-precision positioning has been developed rapidly, and this paper designs a 3D spatial positioning system. With the aid of the spatial positioning principle, the 3D spatial positioning system is used to enlarge communication constraint and increase signal coordination processing. A information fusion estimation method is presented for the distributed networked systems with data transmission delays. The proposed distributed fusion estimation scheme employs the transformation of measurement and the weighted fusion of innovation sequence. To reduce the communication burden and computational cost with transmission delays, a re-optimal weighted fusion estimator is designed. Moreover, the proposed method reduces the information redundancy and maintains the higher measurement accuracy. An illustrative example obtained from the 3D spatial positioning system is given to validate the effectiveness of the proposed method.

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