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Evaluation of Data Fusion Methods Using Kalman Filtering and TBM
This presentation will probably involve audience discussion, which will create action items. Use PowerPoint to keep track of these action items during your presentation In Slide Show, click on the right mouse button Select “Meeting Minder” Select the “Action Items” tab Type in action items as they come up Click OK to dismiss this box This will automatically create an Action Item slide at the end of your presentation with your points entered. Evaluation of Data Fusion Methods Using Kalman Filtering and TBM Sergiy Nazarko 21/11/2018 Cheese Factory project meeting
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Area of Interest Data fusion algorithms which can be used for target tracking and identification Kalman Filtering TBM 21/11/2018 Cheese Factory project meeting
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”Eye Of Ra” User Interface Kalman Filter part TBM part 21/11/2018 Cheese Factory project meeting
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UI of TBM part 21/11/2018 Cheese Factory project meeting
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Results Within TBM Applying Disjunctive Rule of Combination
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Results within TBM applying Generalized Bayesian theorem
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UI of Kalman Filtering part
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Structure of Kalman Filter
True Trajectory Noise Estimation (Kalman Filter) Estimated trajectory Sensor measurement + 21/11/2018 Cheese Factory project meeting
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Results Within Kalman Filter
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More Results Within KF 21/11/2018 Cheese Factory project meeting
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Separated representation of tracking
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Conclusion Evaluation successful Kalman filter works as it should Results achieved during TBM evaluation were checked with Matlab sources 21/11/2018 Cheese Factory project meeting
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Future Work Fusion of TBM and Kalman filter Designing totally distributed tracking system Integration into Cheddar 21/11/2018 Cheese Factory project meeting
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Thank You! 21/11/2018 Cheese Factory project meeting
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