Distributed Kalman estimation with decoupled local filters
نویسندگان
چکیده
We study a distributed Kalman filtering problem in which number of nodes cooperate without central coordination to estimate common state based on local measurements and data received from neighbors. This is typically done by running filter at each node using information obtained through some procedure for fusing across the network. A with existing methods that outcome filters time step depends fused previous step. propose an alternative approach eliminate this error propagation. The proposed are guaranteed be stable under mild conditions certain global structural data, their fusion yields centralized estimate. main feature new errors introduced given do not carry over subsequent steps. offers advantages many situations including when only needed rate slower than or there network interruptions. If can correctly asymptotically, stability equivalent filter. Otherwise, we provide guarantee bound resulting estimation error. Numerical experiments show advantage our method other alternatives.
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ژورنال
عنوان ژورنال: Automatica
سال: 2021
ISSN: ['1873-2836', '0005-1098']
DOI: https://doi.org/10.1016/j.automatica.2021.109724