A biosonar model of finless porpoise (Neophocaena phocaenoides) for material composition discrimination of cylinders

Underwater target classification based on the combination of dolphin click trains and convolutional neural networks

Sonar remains a major way to detect and discriminate underwater targets by interpreting the echoes. In this study, we used broadband dolphin clicks to detect and classify targets. The peak and notch features of the echo spectra were coded, and echoes were obtained using five-click trains, with the number of clicks changing from 1 to 50. Codes containing the target interpretation were classified by convolutional neural networks (CNNs). Compared to a single click, the increasing number of clicks to 5, 10, 20, and 50 in a train would gradually improve the classification rate of targets by 3%, 6.1%, 8.2%, and 10.5% on average with a signal-to-noise ratio ranging from -10 to 15 dB. The 50-click train outperformed other click trains in target detection and classification. The CNNs achieved an average classification accuracy of 95.2% for a 50-click train, higher than that of the nearest neighbor method by 10.3% across signal-to-noise ratios. Therefore, the usage of dolphin clicks and CNN-based echo encoding technologies constitutes an effective method for enhancing target classification, offering valuable insights for future applications in detecting underwater targets.

The development of deep convolutional generative adversarial network to synthesize odontocetes' clicks

Odontocetes are capable of dynamically changing their echolocation clicks to efficiently detect targets, and learning their clicking strategy can facilitate the design of man-made detecting signals. In this study, we developed deep convolutional generative adversarial networks guided by an acoustic feature vector (AF-DCGANs) to synthesize narrowband clicks of the finless porpoise (Neophocaena phocaenoides sunameri) and broadband clicks of the bottlenose dolphins (Tursiops truncatus). The average short-time objective intelligibility (STOI), spectral correlation coefficient (Spe-CORR), waveform correlation coefficient (Wave-CORR), and dynamic time warping distance (DTW-Distance) of the synthetic clicks were 0.975, 0.968, 0.877, and 0.992, respectively. AF-DCGAN outperformed the minimum phase signal reconstruction (MPSR) method and variational quantized variational autoencoders (VQ-VAE) by 5.9% and 3.7% in STOI, 5.2% and 3.5% in Spe-CORR, and 5.8% and 2.8% in Wave-CORR, respectively. In addition, AF-DCGAN reduced DTW-Distances by 29.9% and 9.4% compared to MPSR and VQ-VAE, respectively. Results showed that AF-DCGAN was robust in synthesizing both narrowband and broadband clicks that can produce a substantial number of high-fidelity odontocetes' clicks with flexibility in modulating parameters. Employing AF-DCGAN to synthesize odontocete-like clicks could advance the development of a click database, offering promising applications in the research of biomimetic target detection and recognition.

Does rotation increase the acoustic field of view? Comparative models based on CT data of a live dolphin versus a dead dolphin

Rotational behaviour has been observed when dolphins track or detect targets, however, its role in echolocation is unknown. We used computed tomography data of one live and one recently deceased bottlenose dolphin, together with measurements of the acoustic properties of head tissues, to perform acoustic property reconstruction. The anatomical configuration and acoustic properties of the main forehead structures between the live and deceased dolphins were compared. Finite element analysis (FEA) was applied to simulate the generation and propagation of echolocation clicks, to compute their waveforms and spectra in both near- and far-fields, and to derive echolocation beam patterns. Modelling results from both the live and deceased dolphins were in good agreement with click recordings from other, live, echolocating individuals. FEA was also used to estimate the acoustic scene experienced by a dolphin rotating 180° about its longitudinal axis to detect fish in the far-field at elevation angles of -20° to 20°. The results suggest that the rotational behaviour provides a wider insonification area and a wider receiving area. Thus, it may provide compensation for the dolphin's relatively narrow biosonar beam, asymmetries in sound reception, and constraints on the pointing direction that are limited by head movement. The results also have implications for examining the accuracy of FEA in acoustic simulations using recently deceased specimens.

Numerical-modeling-based investigation of sound transmission and reception in the short-finned pilot whale (Globicephala macrorhynchus)

The sound-transmission, beam-formation, and sound-reception processes of a short-finned pilot whale (Globicephala macrorhynchus) were investigated using computed tomography (CT) scanning and numerical simulation. The results showed that sound propagations in the forehead were modulated by the upper jaw, air components, and soft tissues, which attributed to the beam formation in the external acoustic field. These structures owned different acoustic impedance and formed a multiphasic sound transmission system that can modulate sounds into a beam. The reception pathways composed of the solid mandible and acoustic fats in the lower head conducted sounds into the tympano-periotic complex. In the simulations, sounds were emitted in the forehead transmission system and propagated into water to interrogate a steel cylinder. The resulting echoes can be interpreted from multiple perspectives, including amplitude, waveform, and spectrum, to obtain the acoustic cues of the steel cylinder. By taking the short-finned pilot whale as an example, this study provides meaningful information to further deepen our understanding of biosonar system operations, and may expand sound-reception theory in odontocetes.

Possible limitations of dolphin echolocation: a simulation study based on a cross-modal matching experiment

Dolphins use their biosonar to discriminate objects with different features through the returning echoes. Cross-modal matching experiments were conducted with a resident bottlenose dolphin (Tursiops aduncus). Four types of objects composed of different materials (water-filled PVC pipes, air-filled PVC pipes, foam ball arrays, and PVC pipes wrapped in closed-cell foam) were used in the experiments, respectively. The size and position of the objects remained the same in each case. The data collected in the experiment showed that the dolphin’s matching accuracy was significantly different across the cases. To gain insight into the underlying mechanism in the experiments, we used finite element methods to construct two-dimensional target detection models of an echolocating dolphin in the vertical plane, based on computed tomography scan data. The acoustic processes of the click’s interaction with the objects and the surrounding media in the four cases were simulated and compared. The simulation results provide some possible explanations for why the dolphin performed differently when discriminating the objects that only differed in material composition in the previous matching experiments.