Abstract

In this work, we consider the joint estimation of time delay, Doppler velocity and Doppler rate of unknown wideband signals, in the sense that the time delay migration over time and Doppler shift migration over signal frequency are non-ignorable. By partitioning the received signals into short-time segments, a novel wideband signal model is presented and the maximum likelihood (ML) estimator is derived. With better compensation of parameter migrations, higher estimation accuracy might be achieved through the derived ML estimator. The signal-specific Cramer–Rao lower bound analysis for the wideband cases is also presented. To avoid the multidimensional search of the ML estimator, a fast estimation algorithm based on the time-reverse transform and the second-order Keystone transform is proposed. In this fast estimation algorithm, these parameters could be estimated through successive one-dimensional searches. Simulation results show that the fast estimation algorithm could achieve comparable performance with the ML estimator with a much lower computational complexity.

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