LAUSR

Time delay estimation (TDE) is of great importance in reconnaissance and passive localization. Though TDE could leverage compressive sensing (CS) kernel to enjoy the advantage of sub-Nyquist samples, the estimation accuracy and robustness are inclined to be reduced by jamming or noise. To address the issue, this letter proposes a scheme of defensive compressive time delay estimation (DCTDE) with a novel sensing kernel optimization method and a defense augmentation strategy for the kernel. Inspired by the information bottleneck (IB) theory, we deduce a new analytic principle to enhance the estimation capability of the kernel, which focuses on the fidelity to the non-compressive scheme and the relevant information provided for TDE task. The strategy adopts an adversarial idea for the anti-spoofing design of kernel. Via simulations, the proposed scheme shows promising estimation accuracy, robustness, and high adaptability in both Gaussian noise and jamming environments, and more competitiveness than the Nyquist scheme.