In recent years, with the development of high-range resolution radars, the desire to identify targets under all weather and clutter conditions has become of great importance. This is an activity carried out with great success by echo-locating mammals such as nectar feeding bats that are able to detect and select flowers of bat-pollinated plants, even in a dense clutter environment. Herein, data consisting of acoustically-generated high-range resolution profiles of four bat-pollinated flower heads are analysed. Multi-perspective classification performance is assessed and compared with the radar case. There are close parallels that suggest lessons can be learnt from nature.
No takes yet. Share an insight, caveat, or question.
Balleri et al. (2009) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: