Target Tracking Performance Evaluation A General Software Environment for Filtering. Rickard Karlsson Gustaf Hendeby Automatic Control Linköping University, SWEDEN. [email protected] Motivating Example. Range-Only Measurements. Two Sensors with range uncertainties. Performance?
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Two Sensors with range uncertainties
STATE SPACE MODEL
Extended Kalman Filter
Mean square error (MSE)
Compare the true trajectory with the estimated!!!
What can we do instead?
Kullback Divergence (KD)
Compare the true PDF with the estimated PDF.
Generalized Gaussion Distribution
Probability Density Function
KD for one realization
comparing PF and EKF
RMSE for 400 MC simulations
KD Indicates a Difference!
Probability for target within
the circle with radius R
F++: Fairly easy to use
Just provide models f(x), h(x), etc
EKF, PF, IMM, UKF
OOP & Design Patterns
Open Source code available www.control.isy.liu.se/resources/f++
“Design patterns are general, programming language independent, conceptual high level solutions to common problems”
Ex: Linear Gaussian system with KF and MATLAB support
Ex: Non-Linear Gaussian system with PF and MATLAB support
Estimator Time Update Meas. Update Estimate
This works for any estimator!
for any Model