Abstract

This paper introduces two matching cumulative estimators designed for achieving gridless time difference of arrival (TDOA) estimation for linear frequency modulated (LFM) signals with limited samples. A designed matching basis function, customized to the source signal waveform, is employed to calculate with the received data. Time delay matching is then utilized to formulate a monotonic objective function related to the estimated TDOA, enabling gridless estimation. To enhance robustness, especially in scenarios characterized by small samples and low signal to noise ratios (SNRs), a nonlinear cumulative transformation, comprised of a series of strongly convex operations, is incorporated to mitigate the impact of noise on the peak calculation of the objective function. Simulation results validate the efficacy of the two proposed TDOA estimators, particularly under challenging conditions involving small samples and low SNRs.

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