Abstract
This paper addresses the problem of robust linear estimations of systems perturbed by noise with a wide sense stationary (WSS) process, with its spectral density known only to be in a neighborhood of some specified spectral density. The asymptotic efficiency of the least-square (LS) estimator relative to the best linear unbiased estimator (BLUE) is known to depend upon the degree of the variance of the spread of the noise spectral density at the frequencies where the spectral mass of the system's impulse response function is concentrated. A signal estimator in the frequency domain is considered and it is demonstrated that where the Fourier transform is applied to the observed data, robust estimation occurs.
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