Improved Kalman Filtering for Systems with Randomly Delayed and Lost Measurements
作者： H. Rezaei , R. Mahboobi Esfanjani , M. H. Sedaaghi
DOI: 10.1007/S00034-014-9740-6
关键词:
摘要: In this paper, a novel Kalman filter is developed for discrete-time linear systems with intermittent observations. The measurement data latency and dropout in transmission from the sensor to modeled by group of Bernoulli distributed random variables. minimum variance designed when packets are/are not time stamped reorganized innovation approach. Moreover, steady-state behavior proposed investigated. Finally, simulation results are presented illustrate that suggested estimator leads remarkably improved performance compared previously approaches.
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sci-hub.se 参考文章(21)
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