Improving bearings-only target state estimation tracking problem by using adaptive and nonlinear kalman algorithms
Finding the best estimate of the process state from noisy data is the main problem in tracking systems, many efforts and researches have been done to remove this noise. More useful information about the target's state can be extracted from observations by using a more appropriate model for the...
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Main Authors: | , , |
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Format: | EJournal Article |
Published: |
Institute of Advanced Engineering and Science,
2019-07-01.
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Online Access: | Get fulltext |
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Call Number: |
A1234.567 |
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Copy 1 | Available |