Extended Kalman Filter Tracking Object in 3-D
Assume that we want to track an object moving in 3-D space with constant velocity. Our instruments observe bearing, range and high(cylindrical coordinates). However, of an interest are rectangular coordinates. Since transformation is non-linear this requires use of extended Kalman filter.
Because transformation is non-linear between X,Y and Range,Bearing and linear between Z and high(Z is height), this problems serves as a good comparason of how well extended Kalman filter can perform. By comparing its linear estimation error in Z to non-linear estimations in X and Y, we can judge how non-familiarities effect estimation.
Cite As
Alex Dytso (2024). Extended Kalman Filter Tracking Object in 3-D (https://www.mathworks.com/matlabcentral/fileexchange/36301-extended-kalman-filter-tracking-object-in-3-d), MATLAB Central File Exchange. Retrieved .
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- Image Processing and Computer Vision > Computer Vision Toolbox > Tracking and Motion Estimation > Motion Detection >
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