Bio‐inspired processing of radar target echoes

Abstract

Echolocating bats have evolved the ability to detect, resolve and discriminate targets in highly challenging environments using biological sonar. The way bats process signals in the receiving auditory system is not the same as that of radar and sonar and hence investigating differences and similarities might provide useful lessons to improve synthetic sensors. The Spectrogram Correlation And Transformation receiver (SCAT) is an existing model of the bat auditory system that takes into account the physiology and the neural organisation of bats that emit broadband signals. In this paper, we present a baseband receiver equivalent to the SCAT that allows an analysis of target echoes at baseband. The Baseband SCAT (BSCT) is used to investigate the output of the bat-auditory model for two closely spaced scatterers and to carry out an analysis of range resolution performance and a comparison with the conventional matched filter. Results firstly show that the BSCT provides improved resolution performance. It is then demonstrated that the output of the BSCT can be obtained with an equivalent matched-filter based receiver. The results are verified with a set of laboratory experiments at radio frequencies in high Signal to Noise Ratio (SNR).

A comprehensive computational model of animal biosonar signal processing

“…The first component was Spectrogram Correlation—a system for forming pulse and echo spectrograms and then determining echo delay from the time that elapses between the broadcast and the echo at each frequency. The utility of spectrogram correlation for determining echo delay has been demonstrated in a number of different implementations of the model [ 23 , 101 – 104 ]. Simulations of delay estimation show that its accuracy is comparable to matched filtering [ 24 ].…”

“…These side peaks mark the glint delays themselves. Subsequent iterations of the model adopted several alternative methods for reading the glint interference pattern out of the spectrograms to estimate the glint delay spacing underlying the interference pattern [ 101 – 104 ]. Subsequent behavioral and neurophysiological research has refined our understanding of auditory mechanisms in bats, focusing attention particularly on how peaks and nulls in the echo spectrogram are encoded in neural responses [ 106 – 108 ].…”

How frequency hopping suppresses pulse-echo ambiguity in bat biosonar

“…The direct approach to time–frequency processing is to generate the frequency axis “up front,” using a bank of band-pass filters at the moment signals are received. To mimic the inner ear’s receptors, the spectrogram correlation and transformation (SCAT) model of biosonar ( 13 ) and its relatives ( 54 – 60 ) receive FM broadcasts and their echoes through parallel band-pass filters tuned to different frequencies in the bat’s broadcast band. The current version of the SCAT method employs delay lines to determine target range and a multiresolution array of spectral filters that select different rates of spectral notches or ripples centered at different frequencies of the band-pass filter bank at the input ( 60 ) ( https://github.com/gomingchen/SCAT ).…”

A comprehensive computational model of animal biosonar signal processing

“…The first component was Spectrogram Correlation-a system for forming pulse and echo spectrograms and then determining echo delay from the time that elapses between the broadcast and the echo at each frequency. The utility of spectrogram correlation for determining echo delay has been demonstrated in a number of different implementations of the model [23,[101][102][103][104]. Simulations of delay estimation show that its accuracy is comparable to matched filtering [24].…”

“…These side peaks mark the glint delays themselves. Subsequent iterations of the model adopted several alternative methods for reading the glint interference pattern out of the spectrograms to estimate the glint delay spacing underlying the interference pattern [101][102][103][104]. Subsequent behavioral and neurophysiological research has refined our understanding of auditory mechanisms PLOS COMPUTATIONAL BIOLOGY in bats, focusing attention particularly on how peaks and nulls in the echo spectrogram are encoded in neural responses [106][107][108].…”