Time-domain multiscale shape identification in electro-sensing

TL;DR

This paper introduces a novel time-domain multi-scale shape identification method for electro-sensing that uses pulse signals and transform-invariant descriptors, demonstrating high noise robustness and potential for pulsed imaging applications.

Contribution

The paper develops a new multi-scale shape identification approach in the time domain using polarization tensors, enhancing noise robustness and applicability in limited-view electro-sensing scenarios.

Findings

Robust shape identification with pulse signals

Effective at limited angles and noisy conditions

Applicable to pulsed echolocation and induction imaging

Abstract

This paper presents premier and innovative time-domain multi-scale method for shape identification in electro-sensing using pulse-type signals. The method is based on transform-invariant shape descriptors computed from filtered polarization tensors at multi-scales. The proposed algorithm enjoys a remarkable noise robustness even with far-field measurements at very limited angle of view. It opens a door for pulsed imaging using echolocation and induction data.