Multiscale analysis of univariate time series has appeared in the literature at an ever increasing rate. Here we introduce the multiscale analysis of covariance between two time series using the discrete wavelet transform. The wavelet covariance and wavelet correlation are deened and applied to this problem as an alternative to traditional cross-spectrum analysis. The wavelet covariance is show...

A new covariance matrix estimator useful for designing classifiers with limited training data is developed. In experiments, this estimator achieved higher classification accuracy than the sample covariance matrix and common covariance matrix estimates. In about half of the experiments, it achieved higher accuracy than regularized discriminant analysis, but required much less computation.

In this report we describe our analysis of the influence of sea clutter non stationarity on the clutter covariance matrix estimation and its impact on the CFAR property of the normalized adaptive matched filter (NAMF). Three estimators have been considered in the analysis, i.e. the sample covariance matrix (SCM), the normalized sample covariance matrix (NSCM), and the fixed point (PF) estimator...