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Passive acoustic monitoring is widely used for detection and localization of marine mammals. Typically, pressure sensors are used, although several studies utilized acoustic vector sensors (AVSs), that measure acoustic pressure and particle velocity and can estimate azimuths to acoustic sources. The AVSs can localize sources using a reduced number of sensors and do not require precise time synchronization between sensors. However, when multiple animals are calling concurrently, automated tracking of individual sources still poses a challenge, and manual methods are typically employed to link together sequences of measurements from a given source. This paper extends the method previously reported by Tenorio-Hallé, Thode, Lammers, Conrad, and Kim [J. Acoust. Soc. Am. 151(1), 126-137 (2022)] by employing and comparing two fully-automated approaches for azimuthal tracking based on the AVS data. One approach is based on random finite set statistics and the other on message passing algorithms, but both approaches utilize the underlying Bayesian statistical framework. The proposed methods are tested on several days of AVS data obtained off the coast of Maui and results show that both approaches successfully and efficiently track multiple singing humpback whales. The proposed methods thus made it possible to develop a fully-automated AVS tracking approach applicable to all species of baleen whales., (© 2023 Acoustical Society of America.)

Acoustic vector sensors allow estimating the direction of travel of an acoustic wave at a single point by measuring both acoustic pressure and particle motion on orthogonal axes. In a two-dimensional plane, the location of an acoustic source can thus be determined by triangulation using the estimated azimuths from at least two vector sensors. However, when tracking multiple acoustic sources simultaneously, it becomes challenging to identify and link sequences of azimuthal measurements between sensors to their respective sources. This work illustrates how two-dimensional vector sensors, deployed off the coast of western Maui, can be used to generate azimuthal tracks from individual humpback whales singing simultaneously. Incorporating acoustic transport velocity estimates into the processing generates high-quality azimuthal tracks that can be linked between sensors by cross-correlating features of their respective azigrams, a particular time-frequency representation of sound directionality. Once the correct azimuthal track associations have been made between instruments, subsequent localization and tracking in latitude and longitude of simultaneous whales can be achieved using a minimum of two vector sensors. Two-dimensional tracks and positional uncertainties of six singing whales are presented, along with swimming speed estimates derived from a high-quality track.

Measurements from bottom-mounted acoustic vector sensors, deployed seasonally between 2008 and 2014 on the shallow Beaufort Sea shelf along the Alaskan North Slope, are used to estimate the ambient sound pressure power spectral density, acoustic transport velocity of energy, and dominant azimuth between 25 and 450 Hz. Even during ice-free conditions, this region has unusual acoustic features when compared against other U.S. coastal regions. Two distinct regimes exist in the diffuse ambient noise environment: one with high pressure spectral density levels but low directionality, and another with lower spectral density levels but high directionality. The transition between the two states, which is invisible in traditional spectrograms, occurs between 73 and 79 dB re 1 μPa 2 /Hz at 100 Hz, with the transition region occurring at lower spectral levels at higher frequencies. Across a wide bandwidth, the high-directionality ambient noise consistently arrives from geographical azimuths between 0° and 30° from true north over multiple years and locations, with a seasonal interquartile range of 40° at low frequencies and high transport velocities. The long-term stability of this directional regime, which is believed to arise from the dominance of wind-driven sources along an east-west coastline, makes it an important feature of arctic ambient sound.

Relative clock drift between instruments can be an issue for coherent processing of acoustic signals, which requires data to be time-synchronized between channels. This work shows how cross correlation of anisotropic narrowband ambient noise allows continuous estimation of the relative clock drift between independent acoustic recorders, under the assumption that the spatial distribution of the coherent noise sources is stationary. This method is applied to two pairs of commercial passive acoustic recorders deployed up to 14 m apart at 6 and 12 m depth, respectively, over a period of 10 days. Occasional calibration signals show that this method allows time-synchronizing the instruments to within ±1 ms. In addition to a large linear clock drift component on the order of tens of milliseconds per hour, the results reveal for these instruments non-linear excursions of up to 50 ms that cannot be measured by standard methods but are crucial for coherent processing. The noise field displays the highest coherence between 50 and 100 Hz, a bandwidth dominated by what are believed to be croaker fish, which are particularly vocal in the evenings. Both the passive and continuous nature of this method provide advantages over time-synchronization using active sources.

Ray-tracing is typically used to estimate the depth and range of an acoustic source in refractive deep-water environments by exploiting multipath information on a vertical array. However, mismatched array inclination and uncertain environmental features can produce imprecise trajectories when ray-tracing sequences of individual acoustic events. "Double-difference" methods have previously been developed to determine fine-scale relative locations of earthquakes along a fault [Waldhauser and Ellsworth (2000). Bull. Seismolog. Soc. Am. 90, 1353-1368]. This technique translates differences in travel times between nearby seismic events, recorded at multiple widely separated stations, into precise relative displacements. Here, this method for acoustic multipath measurements on a single vertical array of hydrophones is reformulated. Changes over time in both the elevation angles and the relative arrival times of the multipath are converted into relative changes in source position. This approach is tested on data recorded on a 128-element vertical array deployed in 4 km deep water. The trajectory of a controlled towed acoustic source was accurately reproduced to within a few meters at nearly 50 km range. The positional errors of the double-difference approach for both the towed source and an opportunistically detected sperm whale are an order of magnitude lower than those produced from ray-tracing individual events.