Subspace-based frequency estimation of sinusoidal signals in alpha-stable noise
Signal Processing - Signal processing with heavy-tailed models
Estimation of the parameters of sinusoidal signals in non-Gaussian noise
IEEE Transactions on Signal Processing
α-stable interference modeling and cauchy receiver for an IR-UWB ad hoc network
IEEE Transactions on Communications
LFM signal detection using LPP-Hough transform
Signal Processing
Impulsive noise cancelation with simplified Cauchy-based p-norm filter
Signal Processing
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This paper presents a robust class of estimators for the parameters of a deterministic signal in impulsive noise. The proposed technique has the structure of the maximum likelihood estimator (MLE) but has an extra degree of freedom: the choice of a nonlinear function (which is different from the score function suggested by the MLE) that can be adjusted to improve robustness. The effect of this nonlinear function is studied analytically via an asymptotic performance analysis. We investigate the covariance of the estimates and the loss of efficiency induced by nonoptimal choices of the nonlinear function, giving special attention to the case of α-stable noise. Finally, we apply the theoretical results to the problem of estimating the parameters of a sinusoidal signal in impulsive noise