Estimation fusion of nonlinear cost functions with application to multisensory Kalman filtering |
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| Authors: | Il Young Song Vladimir Shin Seokhyoung Lee Won Choi |
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| Institution: | 1. Department of Sensor Systems, Hanwha Corporation R&D Center, 52-1 Oesam-dong, Yuseong-gu, Daejeon 305-106, Republic of Korea;2. Department of Information and Statistics, Research Institute of Natural Science, Gyeongsang National University, 501 Jinjudaero, Jinju, Gyeongsangnam-do 660-701, Republic of Korea;3. Department of Automation & Control Research, Hyundai Industrial Research Institute, 1000 Bangeojinsunhwan-doro, Dong-gu, Ulsan 682-792, Republic of Korea;4. Department of Mathematics, University of Incheon, 119 Academy-ro, Yeonsu-gu, Incheon 402-749, Republic of Korea |
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| Abstract: | This paper focuses on four fusion algorithms for the estimation of nonlinear cost function (NCF) in a multisensory environment. In multisensory filtering and control problems, NCF represents a nonlinear multivariate functional of state variables, which can indicate useful information of the target systems for automatic control. To estimate the NCF using multisensory information, we propose one centralized and three decentralized estimation fusion algorithms. For multivariate polynomial NCFs, we propose a simple closed-form computation procedure. For general NCFs, the most popular procedure for the evaluation of their estimates is based on the unscented transformation. The effectiveness and estimation accuracy of the proposed fusion algorithms are demonstrated with theoretical and numerical examples. |
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