A comprehensive computational model of animal biosonar signal processing.

Chen Ming,James A Simmons,Stephanie Haro,Andrea Megela Simmons,Lyle J Graham

doi:10.1371/journal.pcbi.1008677

Abstract

Computational models of animal biosonar seek to identify critical aspects of echo processing responsible for the superior, real-time performance of echolocating bats and dolphins in target tracking and clutter rejection. The Spectrogram Correlation and Transformation (SCAT) model replicates aspects of biosonar imaging in both species by processing wideband biosonar sounds and echoes with auditory mechanisms identified from experiments with bats. The model acquires broadband biosonar broadcasts and echoes, represents them as time-frequency spectrograms using parallel bandpass filters, translates the filtered signals into ten parallel amplitude threshold levels, and then operates on the resulting time-of-occurrence values at each frequency to estimate overall echo range delay. It uses the structure of the echo spectrum by depicting it as a series of local frequency nulls arranged regularly along the frequency axis of the spectrograms after dechirping them relative to the broadcast. Computations take place entirely on the timing of threshold-crossing events for each echo relative to threshold-events for the broadcast. Threshold-crossing times take into account amplitude-latency trading, a physiological feature absent from conventional digital signal processing. Amplitude-latency trading transposes the profile of amplitudes across frequencies into a profile of time-registrations across frequencies. Target shape is extracted from the spacing of the object’s individual acoustic reflecting points, or glints, using the mutual interference pattern of peaks and nulls in the echo spectrum. These are merged with the overall range-delay estimate to produce a delay-based reconstruction of the object’s distance as well as its glints. Clutter echoes indiscriminately activate multiple parts in the null-detecting system, which then produces the equivalent glint-delay spacings in images, thus blurring the overall echo-delay estimates by adding spurious glint delays to the image. Blurring acts as an anticorrelation process that rejects clutter intrusion into perceptions.

Highlights

Echolocation is a real-time active acoustic sense used by bats and cetaceans for spatial orientation and perceptual imaging [1,2,3]
We use the term “image”, which is appropriate for describing the model’s output in this composite format because it is literally just a picture that shows the estimates of range delay (t) and glint delay (Δt)
The arrangement of the X, Y, and Z axes is interlocking; it illustrates the magnifying effect of the spectrogram transformation from spectral ripples into the glint delay estimate alongside the range delay estimate derived from spectrogram correlation

Summary

Introduction

Echolocation is a real-time active acoustic sense used by bats and cetaceans for spatial orientation and perceptual imaging [1,2,3]. The design of the broadcast signals, the sense of hearing, and the neural mechanisms of the auditory system are harnessed into a single cohesive biosonar system [4,5,6]. Orchestration of these components is a product of evolution rather than engineering design [7]. The strong underpinnings for radar and sonar in applied math and engineering can reflect back to improve our understanding of the biological system as if it were a product of design [9,10]. We describe a sufficiently detailed computational model of biosonar that it can contribute to both directions of inspiration [11,12]

Methods

Results

Conclusion