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http://dx.doi.org/10.11003/JPNT.2020.9.2.99

Kalman Filter-based Navigation Algorithm for Multi-Radio Integrated Navigation System  

Son, Jae Hoon (Department of Electronics Engineering, Chungnam National University)
Oh, Sang Heon (Navcours Co., Ltd)
Hwang, Dong-Hwan (Department of Electronics Engineering, Chungnam National University)
Publication Information
Journal of Positioning, Navigation, and Timing / v.9, no.2, 2020 , pp. 99-115 More about this Journal
Abstract
Since GNSS is easily affected by jamming and/or spoofing, alternative navigation systems can be operated as backup system to prepare for outage of GNSS. Alternative navigation systems are being researched over the world, and a multi-radio integrated navigation system using alternative navigation systems such as KNSS, eLoran, Loran-C, DME, VOR has been researched in Korea. Least Square or Kalman filter can be used to estimate navigation parameters in the navigation system. A large number of measurements of the Kalman filter may lead to heavy computational load. The decentralized Kalman filter and the federated Kalman filter were proposed to handle this problem. In this paper, the decentralized Kalman filter and the federated Kalman filter are designed for the multi-radio integrated navigation system and the performance evaluation result are presented. The decentralized Kalman filter and the federated Kalman filter consists of local filters and a master filter. The navigation parameter is estimated by local filters and master filter compensates navigation parameter from the local filters. Characteristics of three Kalman filters for a linear system and nonlinear system are investigated, and the performance evaluation results of the three Kalman filters for multi-radio integrated navigation system are compared.
Keywords
Kalman filter; decentralized Kalman filter; federated Kalman filter; integrated navigation system;
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Times Cited By KSCI : 2  (Citation Analysis)
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