  Echolocating bats locate the targets by echolocation. Many theoretical
frameworks have been suggested the abilities of bats are related to the shapes
of bats ears, but few artificial bat-like ears have been made to mimic the
abilities, the difficulty of which lies in the determination of the elevation
angle of the target. In this study, we present a device with artificial bat
pinnae modeling by the ears of brown long-eared bat (Plecotus auritus) which
can accurately estimate the elevation angle of the aerial target by virtue of
active sonar. An artificial neural-network with the labeled data obtained from
echoes as the trained and tested data is used and optimized by a tenfold
cross-validation technique. A decision method we named sliding window averaging
algorithm is designed for getting the estimation results of elevation. At last,
a right-angle pinnae construction is designed for determining direction of the
target. The results show a higher accuracy for the direction determination of
the single target. The results also demonstrate that for the Plecotus auritus
bat, not only the binaural shapes, but the binaural relative orientations also
play important roles in the target localization.
