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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhansheng Duan Li, X.R. Jilkov, V.P. |
| Copyright Year | 2010 |
| Description | Author affiliation: Dept. of Electr. Eng., Univ. of New Orleans, New Orleans, LA, USA (Zhansheng Duan; Li, X.R.; Jilkov, V.P.) |
| Abstract | Numerous state estimation problems (e.g., under linear or nonlinear inequality constraints, with quantized measurements) can be formulated as those with point and set measurements. Inspired by the estimation with quantized measurements developed by Curry, under a Gaussian assumption, the minimum mean-squared error (MMSE) filtering with point measurements and set measurements of any shape is proposed by discretizing continuous set measurements. Possible ways to relax the Gaussian assumption and to discretize the involved Gaussian and truncated Gaussian distributions are discussed. Through an inequality constrained state estimation example, it is shown that under a certain condition, the update by inequality constraints as set measurements is redundant, otherwise the update is necessary and helpful. Supporting numerical examples are provided. |
| Sponsorship | ISIF |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 298937 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9780982443811 |
| DOI | 10.1109/ICIF.2010.5712087 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-07-26 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Gaussian distribution Shape measurement Approximation methods State estimation Shape Atmospheric measurements nonlinear filtering point measurement set measurement inequality constraint quantized measurement |
| Content Type | Text |
| Resource Type | Article |
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