Bats are known for their highly capable biosonar systems which make them be able to navigate and forage in dense vegetation. Their biosonar system consists of one emitter (nose or mouth) and two receivers (ears). Some bat species, e.g. in the rhinolophid and hipposiderid families, have complicated pinna motion patterns. It has been shown that these pinna motion patterns fall into two distinct categories: rigid motions and non-rigid motions. In the current work, the pinna of Pratt's leaf-nosed bat (Hipposideros pratti) was used as a biological model system to understand how a sensor could benefit from variability. Hence, the variability in the rigid pinna motions and in the non-rigid pinna motions has been investigated by tracking a dense set of landmarks on the pinna surface with stereo vision. Axis-angle representations have shown that the rigid pinna motions exhibited a large continuous variation with rotation axes covering 180 degrees in azimuth and elevation. Distributions of clusters of the landmarks on the pinna surface have shown that the non-rigid pinna motions fall into at least two subgroups. Besides, the acoustic impact of the rigid pinna motions have been investigated using a biomimetic pinna. Normalized mutual information between the acoustic inputs with different rotation axes has shown that different rotation axes can provide at least 50% new sensory information. These results demonstrate that the variability in the pinna motions is an interesting concept for sensor, and how the bats approach that needs to be further investigated. / Master of Science / Sensors have been developed for a long time, and they can be used to detect the environments and then deliver the required sensing information. There are many different types of sensors, such as vision-based sensors (infrared camera and laser scanner) and sound-based sensors (sonar and radar). Ultrasonic transducers are one of the sound-based sensors, and they are more stable and reliable in environments where smoke or steam is present. Similar to human-made ultrasonic transducers, bats have developed highly capable biosonar systems that consist of one ultrasonic emitter (nose or mouth) and two ultrasonic receivers (ears), and these biosonar systems enable them to fly and hunt in cluttered environments. Some bats, e.g. rhinolophid and hipposiderid bats, have dynamic noseleaves (elaborate baffle shapes surrounding the nostrils) and pinna (outer ear), and these could enhance the sensing abilities of bats. Hence, the purpose of this thesis has been to investigate this variability to improve the human-made sensors by focusing on the dynamic pinna of the bats. It has been shown that bats have two distinct categories of pinna motions: rigid motions which change only the orientation of the pinna, and non-rigid motions which change also the shape of the pinna. However, the variability within the rigid and non-rigid pinna motions has received little attention. Therefore, the present work has investigated the variability in the rigid pinna motions and in the non-rigid pinna motions. Landmark points were placed on the pinna of certain bats and the pinna motions were tracked by high-speed video cameras. The rigid pinna motions exhibit a large continuous variation in where the pinna is orientated during rotation. Distributions of clusters of the landmarks on the pinna have shown that the non-rigid pinna motions fall into at least two subgroups. The acoustic impacts of the rigid pinna motions have been studied by a biomimetic pinna which reproduced the observed range of the rigid pinna motions. Ultrasonic signals mimicking the bats were emitted to be received by the biomimetic pinna. Based on these signals, it has been shown that different rotation axes and even small changes can provide over 50% new sensory information. These findings give engineers a potential way to improve the human-made sensors.

In bats, the directivity patterns for reception are shaped by the surface geometry of the pinnae. Since many bat species are capable of large ear deformations, these beampatterns can be time-variant. To investigate this time-variance using numerical methods, a digital model that is capable of representing the pinna geometry during the entire deformation cycle has been developed. Due to large deformations and occlusions, some of the surfaces relevant to sound diffraction may not be visible and the geometry of the entire pinna has to be computed from limited data. This has been achieved by combining a complete digital model of the pinna in one position with time-variant sparse sets of three dimensional landmark data. The landmark positions were estimated using stereo vision methods. A finite element model based on elasticity was constructed from CT scans of the pinna post mortem. This elastic model was deformed to provide a good fit to the positions of the landmarks and retain values of smoothness and surface energy comparable to life. This model was able to handle ratios of data to degrees of freedom around 1:5000 and still effect life-like deformations with an acceptable goodness of fit. / Master of Science

Bats are a paragon of evolutionary success. They rely on parsimonious sensory inputs provided by echolocation, yet are able to master lives in complex environments. The outer ears (pinnae) of bats are intricately shaped receiver baffles that encode sensory information through a diffraction process. In some bat species with particularly sophisticated biosonar systems, such as horseshoe bats (Rhinolophidae), the pinnae are characterized by static as well as dynamic geometrical features. Furthermore, bats from these species can deform their pinnae while the returning ultrasonic waves impinge on them. Hence, these dynamic pinna geometries could be a substrate for novel, dynamic sensory encoding paradigms. In this dissertation, two aspects of this dynamic sensing process were investigated: (i) Do local shape features impact the acoustic effects during dynamic deformation of the bat pinna? and (ii) do these shape deformations provide a substrate for the dynamic encoding of sensory information? For this, a family of simplified biomimetic prototypes has been designed based on obliquely truncated cones manufactured from sheets of isobutyl rubber. These prototypes were augmented with biomimetic local shape features as well as with a parsimonious deformation mechanism based on a single linear actuator. An automated setup for the acoustic characterization of the time-variant prototype shapes has been devised and used to characterize the acoustic responses of the prototypes as a function of direction. It was found that the effects of local shape features did interact with each other and with the deformation of the overall shape. The impact of the local features was larger for bent than for upright shape configurations. Although the tested devices were much simpler than actual bat pinnae, they were able to reproduce numerical beampattern predictions that have been obtained for deforming horseshoe bat pinnae in a qualitative fashion. The dynamically deformable biomimetic pinna shapes were estimated to increase the sensory encoding capacity of the device by unit[80]{%} information when compared to static baffles. To arrive at this estimate, spectral clustering was used to break up the direction- and deformation-depended device transfer function into a discrete signal alphabet. For this alphabet, we could estimate the joint signal entropy across a bending cycle as a measure for sensory coding capacity. The results presented in this thesis suggest that bat biosonar posses unique dynamic sensing abilities which have no equivalent in man-made technologies. Sensing paradigms derived from bat biosonar could hence inspire new deformable wave-diffracting structures for the advancement in sensor technology. / Ph. D.

Research investigating the behavioral and physiological responses of bats to echoes typically includes analysis of acoustic signals from microphones and/or microphone arrays, using time difference of arrival (TDOA) between array elements or the microphones to locate flying bats (azimuth and elevation). This has provided insight into transmission adaptations with respect to target distance, clutter, and interference. Microphones recording transmitted signals and echoes near a stationary bat provide sound pressure as a function of time but no directional information. This dissertation introduces spatial audio techniques to bat biosonar studies as a complementary method to the current TDOA based acoustical study methods. This work proposes a couple of feasible methods based on spatial audio techniques, that both track bats in flight and pinpoint the directions of echoes received by a bat. A spatial audio/soundfield microphone array is introduced to measure sounds in the sonar frequency range (20-80 kHz) of the big brown bat (Eptesicus fuscus). The custom-built ultrasonic tetrahedral soundfield microphone consists of four capacitive microphones that were calibrated to match magnitude and phase responses using a transfer function approach. Ambisonics, a signal processing technique used in three-dimensional (3D) audio applications, is used for the basic processing and reproduction of the signals measured by the soundfield microphone. Ambisonics provides syntheses and decompositions of a signal containing its directional properties, using the relationship between the spherical harmonics and the directional properties. As the first proposed method, a spatial audio decoding technique called HARPEx (High Angular Resolution Planewave Expansion) was used to build a system providing angle and elevation estimates. HARPEx can estimate the direction of arrivals (DOA) for up to two simultaneous sources since it decomposes a signal into two dominant planewaves. Experiments proved that the estimation system based on HARPEx provides accurate DOA estimates of static or moving sources. It also reconstructed a smooth flight-path of a bat by accurately estimating its direction at each snapshot of pulse measurements in time. The performance of the system was also assessed using statistical analyses of simulations. A signal model was built to generate microphone capsule responses to a virtual source emitting an LFM signal (3 ms, two harmonics: 40-22 kHz and 80-44 kHz) at an angle of 30° in the simulations. Medians and RMSEs (root-mean-square error) of 10,000 simulations for each case represent the accuracy and precision of the estimations, respectively. Results show lower d (distance between a capsule and the soundfield microphone center) or/and higher SNR (signal-to-noise ratio) are required to achieve higher estimator performance. The Cramer-Rao lower bounds (CRLB) of the estimator are also computed with various d and SNR conditions. The CRLB which is for TDOA based methods does not cover the effects of different incident angles to the capsules and signal delays between the capsules due to a non-zero d, on the estimation system. This shows the CRLB is not a proper tool to assess the estimator performance. For the second proposed method, the matched-filter technique is used instead of HARPEx to build another estimation system. The signal processing algorithm based on Ambisonics and the matched-filter approach reproduces a measured signal in various directions, and computes matched-filter responses of the reproduced signals in time-series. The matched-filter result points a target(s) by the highest filter response. This is a sonar-like estimation system that provides information of the target (range, direction, and velocity) using sonar fundamentals. Experiments using a loudspeaker (emitter) and an artificial or natural target (either stationary or moving) show the system provides accurate estimates of the target's direction and range. Simulations of imitating a situation where a bat emits a pulse and receives an echo from a target (30°) were also performed. The echo sound level is determined using the sonar equation. The system processed the virtual bat pulse and echo, and accurately estimated the direction, range, and velocity of the target. The simulation results also appear to recommend an echo level over -3 dB for accurate and precise estimations (below 15% RMSE for all parameters). This work proposes two methods to track bats in flight or/and pinpoint the directions of targets using spatial audio techniques. The suggested methods provide accurate estimates of the direction, range, or/and velocity of a bat based on its pulses or of a target based on echoes. This demonstrates these methods can be used as key tools to reconstruct bat biosonar. They would be also an independent tool or a complementary option to TDOA based methods, for bat echolocation studies. The developed methods are believed to be also useful in improving man-made sonar technology. / Doctor of Philosophy / While bats are one of the most intriguing creatures to the general population, they are also a popular subject of study in various disciplines. Their extraordinary ability to navigate and forage irrespective of clutter using echolocation has gotten attention from many scientists and engineers. Research investigating bats typically includes analysis of acoustic signals from microphones and/or microphone arrays. Using time difference of arrival (TDOA) between the array elements or the microphones is probably the most popular method to locate flying bats (azimuth and elevation). Microphone responses to transmitted signals and echoes near a bat provide sound pressure but no directional information. This dissertation proposes a complementary way to the current TDOA methods, that delivers directional information by introducing spatial audio techniques. This work shows a couple of feasible methods based on spatial audio techniques, that can both track bats in flight and pinpoint the directions of echoes received by a bat. An ultrasonic tetrahedral soundfield microphone is introduced as a measurement tool for sounds in the sonar frequency range (20-80 kHz) of the big brown bat (Eptesicus fuscus). Ambisonics, a signal processing technique used in three-dimensional (3D) audio applications, is used for the basic processing of the signals measured by the soundfield microphone. Ambisonics also reproduces a measured signal containing its directional properties. As the first method, a spatial audio decoding technique called HARPEx (High Angular Resolution Planewave Expansion) was used to build a system providing angle and elevation estimates. HARPEx can estimate the direction of arrivals (DOA) for up to two simultaneous sound sources. Experiments proved that the estimation system based on HARPEx provides accurate DOA estimates of static or moving sources. The performance of the system was also assessed using statistical analyses of simulations. Medians and RMSEs (root-mean-square error) of 10,000 simulations for each simulation case represent the accuracy and precision of the estimations, respectively. Results show shorter distance between a capsule and the soundfield microphone center, or/and higher SNR (signal-to-noise ratio) are required to achieve higher performance. For the second method, the matched-filter technique is used to build another estimation system. This is a sonar-like estimation system that provides information of the target (range, direction, and velocity) using matched-filter responses and sonar fundamentals. Experiments using a loudspeaker (emitter) and an artificial or natural target (either stationary or moving) show the system provides accurate estimates of the target's direction and range. Simulations imitating a situation where a bat emits a pulse and receives an echo from a target (30°) were also performed. The system processed the virtual bat pulse and echo, and accurately estimated the direction, range, and velocity of the target. The suggested methods provide accurate estimates of the direction, range, or/and velocity of a bat based on its pulses or of a target based on echoes. This demonstrates these methods can be used as key tools to reconstruct bat biosonar. They would be also an independent tool or a complementary option to TDOA based methods, for bat echolocation studies. The developed methods are also believed to be useful in improving sonar technology.

Many animal species are known for their unparalleled abilities to encode sensory information that supports fast, reliable action in complex environments, but the mechanisms remain often unclear. Through fast ear motions, bats can encode information on target direction into time-frequency Doppler signatures. These species were thought to be evolutionarily tuned to Doppler shifts generated by a prey's wing beat. Self-generated Doppler shifts from the bat's own flight motion were for the most part considered a nuisance that the bats compensate for. My findings indicate that these Doppler-based biosonar systems may be more complicated than previously thought because the animals can actively inject Doppler shifts into their input signals. The work in this dissertation presents a novel nonlinear principle for sensory information encoding in bats. Up to now, sound-direction finding has required either multiple signal frequencies or multiple pressure receivers. Inspired by bat species that add Doppler shifts to their biosonar echoes through fast ear motions, I present a source-direction finding paradigm based on a single frequency and a single pressure receiver. Non-rigid ear motions produce complex Doppler signatures that depend on source direction but are difficult to interpret. To demonstrate that deep learning can solve this problem, I have combined a soft-robotic microphone baffle that mimics a deforming bat ear with a CNN for regression. With this integrated cyber-physical setup, I have able to achieve a direction-finding accuracy of 1 degree based on a single baffle motion. / Doctor of Philosophy / Bats are well-known for their intricate biosonar system that allow the animals to navigate even the most complex natural environments. While the mechanism behind most of these abilities remains unknown, an interesting observation is that some bat species produce fast movements of their ears when actively exploring their surroundings. By moving their pinna, the bats create a time-variant reception characteristic and very little research has been directed at exploring the potential benefits of such behavior so far. One hypothesis is that the speed of the pinna motions modulates the received biosonar echoes with Doppler-shift patterns that could convey sensory information that is useful for navigation. This dissertation intends to explore this hypothetical dynamic sensing mechanism by building a soft-robotic biomimetic receiver to replicate the dynamics of the bat pinna. The experiments with this biomimetic pinna robot demonstrate that the non-rigid ear motions produce Doppler signatures that contain information about the direction of a sound source. However, these patterns are difficult to interpret because of their complexity. By combining the soft-robotic pinna with a convolutional neural network for processing the Doppler signatures in the time-frequency domain, I have been able to accurately estimate the source direction with an error margin of less than one degree. This working system, composed of a soft-robotic biomimetic ear integrated with a deep neural net, demonstrates that the use of Doppler signatures as a source of sensory information is a viable hypothesis for explaining the sensory skills of bats.

The Littoral Acoustic Demonstration Center has collected passive acoustic monitoring data in the northern Gulf of Mexico since 2001. Recordings were made in 2007 near the Deepwater Horizon oil spill that provide a baseline for an extensive study of regional marine mammal populations in response to the disaster. Animal density estimates can be derived from detections of echolocation signals in the acoustic data. Beaked whales are of particular interest as they remain one of the least understood groups of marine mammals, and relatively few abundance estimates exist. Efficient methods for classifying detected echolocation transients are essential for mining long-term passive acoustic data. In this study, three data clustering routines using k-means, self-organizing maps, and spectral clustering were tested with various features of detected echolocation transients. Several methods effectively isolated the echolocation signals of regional beaked whales at the species level. Feedforward neural network classifiers were also evaluated, and performed with high accuracy under various noise conditions. The waveform fractal dimension was tested as a feature for marine biosonar classification and improved the accuracy of the classifiers. [This research was made possible by a grant from The Gulf of Mexico Research Initiative. Data are publicly available through the Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC) at https://data.gulfresearchinitiative.org.] [DOIs: 10.7266/N7W094CG, 10.7266/N7QF8R9K]