Object Tracking with Kalman Filter

Added on 2020-05-16

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Running head: PROGRAMMING AND OTHERS 0PROGRAMMING AND OTHERSName of StudentInstitution Affiliation

PROGRAMMING AND OTHERS 2For tracking, we adopt EKF over linear Kalman filtering because most of the times the state variables and measurements are not linear combination of state variables, inputs to the system and noise. The key variables used in EKF were state estimate (k x ˆ) and measurement (k z ) whose relation can be depicted in the figure below . This is the advance research of our previous work so comprehensive explanation of EKF can be seen below And from the above illustration diagram we can come up with algorithms to help come up with the matlab codes (Corke, 2011).Algorithm 1

PROGRAMMING AND OTHERS 3Algorithm 2Algorithm 3

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