Abstract:Some mammals use sound signals for communications and navigation in the air (bats) or underwater (dolphins). Recent biological discovery shows that blind mole rat is capable of detecting and avoiding underground obstacles using reflection from seismic signals. Such a remarkable capacity relies on the ability to localize the source of the reflection with high accuracy and in very low Signal to Noise Ratio (SNR) conditions. The standard methods for source localization are usually based on Time of Arrival (ToA) estimation obtained by the correlation of received signal with a matched filter. This approach suffers from rapid deterioration in the accuracy as SNR level falls below certain threshold value: the phenomenon known in the Radar Theory as a "threshold effect". In this paper we describe biosonar-inspired method for ToA estimation and 2D source localization based on the fusion of the measurements from biased estimators which are obtained using a family of unmatched filters. Suboptimal but not perfectly correlated estimators are combined together to produce a robust estimator for ToA and 2D source position which outperforms standard matched filter-based estimator in high noise. The proposed method can be applied for mapping of underground instalments using low power infrasound pulses.