Abstract
Accurate time delay estimation is critical for a wide range of remote sensing applications. We propose a technique that exploits the redundancy between absolute and relative time delays in transducer arrays as a means to reduce the level of noise present in the measurements. We formalize the problem of interest and present two different strategies to solve it. The first strategy is optimal in the mean square sense but requires a quadratic programming solver. The second approach is based on a sub-optimal iterative denoising technique. The effectiveness of our approach is demonstrated in the context of travel time tomographic imaging using numerical and physical breast mimicking phantoms as well as patient data.
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