Signal-to-noise ratio estimation using higher-order moments
Signal Processing
H∞ filtering with stochastic sampling
Signal Processing
Identifiability and aliasing in polynomial-phase signals
IEEE Transactions on Signal Processing
A new parameter estimation method of linear frequency modulation signal
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
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Estimating the parameters of a cisoid with an unknown amplitude and polynomial phase using uniformly spaced samples can result in ambiguous estimates due to Nyquist sampling limitations. It has been shown previously that nonuniform sampling has the advantage of unambiguous estimates beyond the Nyquist frequency; however, the effect of sampling on the Cramer-Rao bounds is not well known. This paper first derives the maximum likelihood estimators and Cramer-Rao bounds for the parameters with known, arbitrary sampling times. It then outlines two methods for incorporating random sampling times into the lower variance bounds, describing one in detail. It is then shown that for a signal with additive white Gaussian noise the bounds for the estimation with nonuniform sampling tend toward those of uniform sampling. Thus, nonuniform sampling overcomes the ambiguity problems of uniform sampling without incurring the penalty of an increased variance in parameter estimation