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Signal parameter estimation of complex exponentials using fourth order statistics: additive Gaussian noise
Pradip Sircar1, Mukesh K Dutta1, Sudipta Mukhopadhyay2
1Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, UP 208016 India.
Abstract:
A novel approach based on fourth order statistics is presented for estimating the parameters of the complex exponential signal model in additive colored Gaussian noise whose autocorrelation function is not known. Monte Carlo simulations demonstrate that the proposed method performs better than an existing method which also utilizes fourth order statistics under the similar noise condition. To deal with the non-stationarity of the modeled signal, various concepts are introduced while extending the estimation technique based on linear prediction to the higher order statistics domain. It is illustrated that the accuracy of parameter estimation in this case improves due to better handling of signal non-stationarity. While forming the fourth order moment/ cumulant of a signal, the choice of the lag-parameters is crucial. It has been demonstrated that the symmetric fourth order moment/ cumulant as defined in this paper will have many desirable properties.
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