Time-domain multiscale shape identification in electro-sensing
This work addresses shape identification problems in electro-sensing for applications like pulsed imaging using echolocation and induction data, representing a novel method rather than an incremental improvement.
The paper tackles shape identification in electro-sensing by developing a time-domain multi-scale method using pulse-type signals and transform-invariant shape descriptors, achieving remarkable noise robustness with far-field measurements at very limited angles of view.
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.