Evaluating Model Fit for Sea Clutter Returns
Author Information
Author(s): Bojan Vondra
Primary Institution: University of Zagreb
Hypothesis
Can a semi-empirical method effectively evaluate the goodness of fit for models of sea clutter data?
Conclusion
The proposed semi-empirical method for evaluating model fit shows promise in accurately assessing the goodness of fit for various models to sea clutter data.
Supporting Evidence
- The proposed method converges almost surely, demonstrating its effectiveness.
- Numerical examples indicate that a sample size greater than 1000 is sufficient for convergence.
- The method achieves lower mean square error compared to empirical counterparts.
Takeaway
This study created a new way to check if models of sea clutter data are accurate, which is important for tracking boats in the sea.
Methodology
The study proposes a semi-empirical method using Kullback–Leibler divergence and Squared Hellinger distance based on empirical cumulative distribution functions.
Limitations
The method may require very large sample sizes for convergence in certain scenarios, particularly when the supports of the sample and model distributions differ.
Digital Object Identifier (DOI)
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