MATLAB KALMAN FILTER CODING EXAMPLE

Target is moving on 2D space. Initial position of the target is x=[5000m 250 m/s 25000m 0m/s]^T

Target starts to move with the position provided.

Target moves for 50 seconds within the effect of White Noise Acceleration model with mean of zero and covariance of:

And then after this 50 seconds, target makes coordinated turn for 50 seconds with constant angular velocity of 6 degrees/seconds.

After this turning process target continues to move for 50 more seconds within the effect of White Noise Acceleration model and completes its movement.

A sensor which is located at (0m, 0m) position makes measurement in each second of the target info given above. Sensor measures the targets location [x y]T with cumulative sum of zero within the presence of White Gaussian noise with covariance of:

Plot and provide MATLAB code for the movement of target and measurements in same figure with T=1 second sampling.

Implement a Kalman Filter and plot the movement of target with T=1 second sampling.

Use the model of White Noise Acceleration. Use 3 different process noise (low, medium, high). Make 100 Monte Carlo runs.

[1(m/sn?) 0 II 2 0 1(m/sn) 2500m2 b 0 2500m? 0 [1(m/sn?) 0 II 2 0 1(m/sn) 2500m2 b 0 2500m? 0