Time delay estimation of vibroseis chirp signal in urban noise using higher order statistics

One of the primary applications of higher order statistics (HOS) has been for detection and estimation of nonGaussian signals in Gaussian noise of unknown covariance. This is motivated by the fact that higher order cumulants of Gaussian processes vanish. In the present work we study the opposite problem, namely, detection and estimation in nonGaussian noise. We estimate cumulants of nonGaussian processes in the presence of unknown deterministic and/or Gaussion signals. Our approach is to augment existing second-order estimation methods using cumulants. Finally, we illustrate the hybrid strategy using field real data examples. The consistency of the results is very encouraging because the improved cumulant matching strategy we describe can be effectively used with a limited amount of data.