Abstract-We consider the adaptive radar problem where the properties of the (nonstationary) clutter signals can be estimated using multiple observations of radar returns from a number of sufficiently homogeneous range/azimuth resolution cells. We derive a method for approximating an arbitrary Hermitian covariance matrix by a time-varying autoregressive model of order , TVAR( ), that is based on the Dym-Gohberg band-matrix extension technique which gives the unique TVAR( ) model for any nondegenerate covariance matrix. We demonstrate that the Dym-Gohberg transformation of the sample covariance matrix gives the maximum-likelihood (ML) estimate of the TVAR( ) covariance matrix. We introduce an example of TVAR( ) clutter modeling for high-frequency over-the-horizon radar that demonstrates its practical importance.

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Absfracf-The performance of an HF Doppler radar is degraded by signal corruption due to impulsive interferers such as atmospherics and meteor train echoes. These interterm raise the Doppler spectrum hackground noise level, thereby reducing large1 to noise power ratios. In lhis paper, we make modifications lo a known linear prediction missing data technique, and show that this technique is eNeciive against HF radar impulsive interference. Radar 2003

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