[ieee 2011 ieee sensors - limerick, ireland (2011.10.28-2011.10.31)] 2011 ieee sensors proceedings -...

Biomimetic Sonar, Outer Ears versus Arrays

Jan Steckel

University of Antwerp

FTEW MTT Department

Prinsstraat 13, B-2000 Antwerpen

Belgium

[email protected]

Filips Schillebeeckx


FTEW MTT Department


Belgium

[email protected]

Herbert Peremans


FTEW MTT Department


Belgium

[email protected]

Abstract—Biomimetic sonar systems, i.e. sonar systems makinguse of spectral cues for the localization of one or more reflectors,depend heavily on the spatial filters of the reception subsystem.These spatial filters can be implemented in two ways, e.g.,by means of an artificial pinna or by means of an array ofmicrophones in combination with a beamforming algorithm. Inthis paper we compare two such systems using an informationtheoretic model, which allows objective evaluation of each systemfrom an echolocation point of view.

Index Terms—Biomimetic sonar, Phased Array, Artificial pin-nae, Beamforming

I. INTRODUCTION

Inspired by the excellent navigation and prey hunting skills

of bats [1] we argue that engineers can learn from bat

biosonar when attempting to bridge the performance gap with

existing in-air robotic sonar systems. From our study of bats

we conclude that a biomimetic sonar system should adhere

to the following principles: maximal information extraction

per echo, use of body shape to simplify echo interpretation,

i.e. trade physical (analog) processing for neural (digital)

processing, and the use of behavioral patterns to simplify echo

interpretation. As an example of the relative simplicity of

analog versus digital processing, we show how 3D reflector

localization is possible by interpreting the binaural spectra

generated by a biomimetic sonar consisting of an emitter and

either two microphones fitted with simple outer-ear shaped

baffles or a 32 element microphone array. The biomimetic

approach proposed here is quite different from the usual

approach taken by roboticists, i.e. a small number of high

information content measurements collected by an advanced

sonar system (see Fig. 1) compared to large numbers of low

information content measurements [2] collected by a simple

range sensor.

To allow optimization of such biomimetic sonar systems we

have developed an objective information theoretic performance

measure [3] that quantifies their localization capabilities in the

presence of realistic noise. We conclude that the array system

while being considerably more complex, i.e. requiring 32 mi-

crophone channels and a digital beamforming algorithm, than

the simple binaural system, i.e. requiring only 2 microphone

channels and no digital beamforming, has similar localization

capabilities. The main advantage of the array system is that

modification of the spatial filters requires no movement or

deformation of any physical parts but can be arrived at by

reprogramming the weights in the beamforming algorithm.

II. OVERVIEW OF THE BIOMIMETIC SYSTEMS

Both implementations of the biomimetic echolocation sys-

tem make use of a Polaroid transducer for emitting the

vocalizations [4]. This transducer allows the emission of a

broadband chirp (fm-pulse of duration 2ms sweeping down

from 120kHz to 30kHz) with a relatively high output power. It

has been known for some time that the spectral cues introduced

by the outer ear (the Head Related Transfer Function, HRTF,

[5]) play an important role in bat echolocation [6], [7].

However, we have shown that for an active sonar system

the target localization performance [8] is determined by the

combination of the emitter directionality and the HRTF. In

particular, the high directivity of the Polaroid transducer makes

the emission subsystem a dominant factor in the spatial filter-

ing of the complete echolocation system. Hence, localization

performance of our biomimetic sonar systems is significantly

affected by the emission directivity.

a) b)

Fig. 1. Biomimetic sonar: a) array system, b) binaural system fitted withplastic pinnae.

The two biomimetic echolocation systems differ greatly in

terms of the implementation of the reception subsystem. In

one system the receptive spatial filters are implemented by

means of plastic replicas of real and abstracted bat pinnae

[8] fitted on a miniature (=omnidirectional) microphone (see

Fig. 1 b)). In the other system the receptive spatial filters are

implemented by means of a microphone array (see Fig. 1 a)).

Array systems allow for the implementation of a wide range

of spatial filtering patterns by means of beamforming [9].

978-1-4244-9289-3/11/$26.00 ©2011 IEEE

A. HRTF Implementation using Artificial Pinnae

By means of rapid prototyping techniques the microphones

can be fitted with baffles that are 3D models of either real

or simplified bat pinnae. The simplified pinnae consist of

different combinations of features that are present in real

bat pinnae, i.e., tragus and ripple pattern, and have been

conjectured to play an important role in the spatial filtering

[10]. Figure 2 shows the measured HRTF’s of three types

of simplified pinnae and a replica of the pinna of the bat

Phyllostomus discolor [6].

Fig. 2. Measured spatial filters of different baffle shapes (equal areaprojection of frontal hemisphere, 3db contours)

All HRTF’s show a similar complexity in terms of size and

number of main lobes and side lobes, but the replica of the

real pinna shows the most pronounced scanning of the main

lobe as a function of frequency. Nevertheless, as shown in the

next section (see figure 5), the target localisation performance,

as measured by the information criterium, is comparable for

all four pinna shapes.

B. HRTF Implementation using Microphone Array

in the array system, using standard beamforming techniques

[9], [11], [12], arbitrary directivity patterns (e.g. bat HRTF’s)

can be implemented. Using a filter-and-sum method the spatial

filters resulting from the interactions of the acoustic waves

with the receiver baffles were approximated. The resulting

directivity patterns can be seen in figure 3. We note that

the spatial filters duplicate the most prominent features, e.g.,

mainlobe position and size, of the bat’s HRTF. We find that, in

accordance to the theoretical predictions [9], the small number

of array elements and the minimum separation between those

elements are the two most important limiting factors explain-

ing the remaining approximation errors. Adapting the filter

parameters allows the implementations of changing HRTF’s,

e.g. to model the pinna deformations and movements observed

in bats. Note that the advantage of an adaptive HRTF comes at

the cost of increased complexity, i.e. 32 versus 2 microphones

and beamforming by digital post-processing versus analog pre-

processing (HRTF).

Bat HRTF, 39 kHz Array HRTF, 39 kHz




0 -5 -10 -15 -20 -25

Amplitude (dB)

Fig. 3. HRTF of Phyllostomus discolor and its array approximation.

III. COMPARISON OF THE TWO SYSTEMS USING AN

INFORMATION THEORETIC MODEL

To be able to compare the performance of the two very

different biomimetic echolocation systems, we make use of

an objective information theoretic measure derived in [3]. In

this model the environment is viewed as a source of symbols

θ, with θ representing the direction=(azimuth,elevation) of

the reflecting target. The spatial filter of the complete sonar

system (emission+reception) is viewed as an encoder that

encodes the symbols θ into an echo spectrum S(f, θ). The

echo spectrum is considered to be a signal that is sent

through a noisy communication channel. Channel distortions

included in the model represent both additive white system

noise and unknown reflector filtering. Using a corresponding

decoding process, we can quantify how much target direction

information is lost during transmission through the channel.

The directional information, i.e. the mutual information

between received echo spectra and target directions, quantifies

how good the echolocation task is conditioned for a specific

target direction. Figure 4 shows the directional information for

both the array and the plastic pinna system. By comparing the

directional information maps for the two systems, we conclude

that, despite their inherent differences, both systems provide

similar target localization performance.

θθ

φ

φ

φ

0 2 4 6 8 10 12 (bit)

30dB

20dB

40dB

( )α

( )α

( )α

Fig. 4. Directional information (max 13.5 bits) maps for the two biomimeticsystems.

In addition to being a function of the target direction θ this

directional information also depends on the reflection strength

α. The reflection strength quantifies the signal to noise ratio.

As can be seen from figure 5, the directional information

averaged over the frontal hemisphere behaves quite similarly

as a function of reflection strength for all three simplified pinna

shapes and for the replica of the bat pinna.

4

12

Reflection Strength (dB)α

8

0

Avera

ge Info

rmation (

bits)

20 80 1000 40 60

No Tragus, no Ripple

Tragus, no Ripple

No Tragus, Ripple

Phyllostomus discolor

Fig. 5. Directional information as a function of echo strength for the differentbaffle shapes.

IV. ADAPTIVE SPATIAL FILTERING WITH THE ARRAY

SYSTEM

To illustrate the advantages of the array system we per-

formed two consecutive measurements and processed them

each with a different spatial filter, i.e. we changed the filter

coefficients in the filter-and-sum beamforming algorithm. The

first measurement is processed with the standard Phyllostomus

discolor HRTF as approximated by the beamforming algo-

rithm (see figure 3). The second measurement is processed

with an adapted HRTF derived from the standard one by

panning both pinnae over 20 degr. inwards. Figure 6 illustrates

how the combination of measurements collected through these

two different spatial filters makes it possible to select a single,

unambiguous, target direction despite the ambiguity present in

each individual measurement.

a) b)

xx

x

1.00

0.00

0.25

0.50

0.75

c)

oo

o

o

o

Fig. 6. Posterior probability maps of target direction (a) measurement 1(standard ear configuration), (b) measurement 2 (20 degr. pan ear configura-tion), (c) combination of both measurements. (blue circles: ambiguous targetpositions, blue cross: true target position)

V. CONCLUSIONS AND FUTURE WORK

From the implemented prototypes, we can conclude that,

despite implementation differences, both the biomimetic array

system and the system based on the use of artificial pinnae

have comparable target localization capabilities based on the

information theoretic performance criterion. Future work in-

cludes the development of dynamic echolocation models that

can fully exploit the adaptive nature of the array system. By

incorporating ear movements and ear deformations, further

insights can be gained in bat echolocation. Hence, despite

the increased hardware complexity and computational costs,

we believe that HRTF’s implemented on array receivers might

prove useful for bat echolocation research.

ACKNOWLEDGMENTS

This work was funded by the EU CHIROPING (Chiroptera,

Robots, Sonar) project. This project is funded by the Seventh

Framework Programme ICT Challenge 2: Cognitive Systems,

Interaction, Robotics.

REFERENCES

[1] G. Neuweiler, The biology of bats. Oxford University Press, USA,2000.

[2] J. Tardós, J. Neira, P. Newman, and J. Leonard, “Robust mapping andlocalization in indoor environments using sonar data,” The International

Journal of Robotics Research, vol. 21, no. 4, p. 311, 2002.[3] J. Reijniers, D. Vanderelst, and H. Peremans, “Morphology-Induced

Information Transfer in Bat Sonar,” Physical Review Letters, vol. 105,no. 14, p. 148701, 2010.

[4] C. Biber, S. Ellin, E. Shenk, and J. Stempeck, “The polaroid ultrasonicranging system,” 67th Convention of the Audio Engineering Society,October 1980.

[5] J. Blauert, Spatial hearing: the psychophysics of human sound localiza-

tion. The MIT Press, 1997.[6] U. Firzlaff and G. Schuller, “Spectral directionality of the external ear

of the lesser spear-nosed bat, Phyllostomus discolor,” Hearing research,vol. 181, no. 1-2, pp. 27–39, 2003.

[7] J. Wotton and J. Simmons, “Spectral cues and perception of the verticalposition of targets by the big brown bat, Eptesicus fuscus,” The Journal

of the Acoustical Society of America, vol. 107, p. 1034, 2000.[8] F. Schillebeeckx, F. De Mey, D. Vanderelst, and H. Peremans,

“Biomimetic Sonar: Binaural 3D Localization using Artificial Bat Pin-nae,” The International Journal of Robotics Research, 2010.

[9] H. Van Trees, Optimum array processing, Part IV of Detection, Estima-

tion and Modulation Theory. Wiley Interscience, 2002.[10] R. Mueller and J. Hallam, “From bat pinnae to sonar antennae: Aug-

mented obliquely truncated horns as a novel parametric shape model,”in Proc. 8th Int. Conf. on the Simulation of Adaptive Behavior, 2004,pp. 87–95.

[11] M. Bai and K. Ou, “Head-related transfer function (HRTF) synthesisbased on a three-dimensional array model and singular value decomposi-tion,” Journal of Sound and Vibration, vol. 281, no. 3-5, pp. 1093–1115,2005.

[12] J. Chen, B. Van Veen, and K. Hecox, “External ear transfer functionmodeling: A beamforming approach,” The Journal of the Acoustical

Society of America, vol. 92, p. 1933, 1992.

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