Abstract
Mahalanobis and log-likelihood estimates are used extensively in tracking systems, but are affected by residual bias and by uncertainty in covariance matrices. This paper provides a formal framework that, to some extent, justifies covariance inflation techniques and allows existing fudge factor thresholds to be interpreted in terms of residual bias covariance matrices and covariance matrix uncertainty.
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