COMPLEX AMBIGUITY FUNCTIONS USING NONSTATIONARY HIGHER-ORDER CUMULANTESTIMATES

The complex ambiguity function based on secondorder statistics (CAF-SO S) has been used to simultaneously estimate the frequency-delay of arr ival (FDOA) and time-delay of arrival (TDOA) between two signal measur ements; its performance, however, is sensitive to the correlation betw een two additive noise sources, When the noise sources are assumed to be Gaussian, we develop a new complex ambiguity function based on high er order statistics (CAF-HOS) that reduces the unknown noise-correlati on effect. The new CAF-HOS algorithm utilizes nonstationary higher ord er cross-cumulant estimates and their Fourier transform. In fact, we s uggest a nonstationary estimate of fourth-order cross-cumulants and ob tain the analytical expressions for its mean value and variance. We co mpare the analytical expressions with results obtained by Monte Carlo runs. Also, we compare the performance of the new complex ambiguity fu nction based on fourth-order statistics (CAF-FOS) against the CAF-SOS algorithm using different Gaussian noise sources, different signals of interest, different signal-to-noise ratios, and different lengths of data.