The paper aims at proposing the first shape identification and classification algorithm in echolocation. The approach is based on first extracting geometric features from the reflected waves and then matching them with precomputed ones associated with a dictionary of targets. The construction of such frequency-dependent shape descriptors is based on some important properties of the scattering coefficients and new invariants. The stability and resolution of the proposed identification algorithm with respect to measurement noise and the limited-view aspect are analytically and numerically quantified.
@article{arxiv.1308.5625,
title = {Shape identification and classification in echolocation},
author = {Habib Ammari and Minh Phuong Tran and Han Wang},
journal= {arXiv preprint arXiv:1308.5625},
year = {2013}
}