A Decentralized Parallel Kalman Filter in Multi-sensor System for Data Verification

  • Guoping LiEmail author
  • Shiqiang Wang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 890)


In order to ensure the successful completion of the tasks of a system, the accuracy of data is the foundation and indemnification. To complete the data verification on the decentralized computing platform, a decentralized Kalman filter with state constraints is presented in this paper. The decentralized sensing architecture takes the form of a network of transputer-based sensor nodes, each with its own processing system. So it does not require any central processor or common clock. Based on that, this new algorithm can allow fully decentralization of the multisensory Kalman filter equations with state equality constraints among a number of sensing nodes to verify the data. The algorithm is developed from a centralized method named projection method to minimized the communication among nodes and can take place without any prior synchronization between nodes. Theoretical derivation is provided to the decentralized algorithm. Finally, the case study of the secondary chilled water pump system illustrates the effectiveness of the proposed method.


Decentralized computing platform Decentralized Kalman filter Data verification State equality constraints Projection estimation 



This work is supported by National Key Research and Development Project of China No. 2017YFC0704100 (entitled New generation Intelligent building platform techniques)


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.College of Defense Engineering, Army Engineering University of PLANanjingChina

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