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:
- Matlab Kalman Filter Coding Example Target Is Moving On 2d Space Initial Position Of The Target Is X 5000m 250 M S 250 1 (3.13 KiB) Viewed 21 times
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
target’s location [x y]T with cumulative sum of zero within the
presence of White Gaussian noise with covariance of:
- Matlab Kalman Filter Coding Example Target Is Moving On 2d Space Initial Position Of The Target Is X 5000m 250 M S 250 2 (2.31 KiB) Viewed 21 times
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