Passive acoustic localization and tracking using arrays and directional sensors

In bioacoustics, passive acoustic localization and tracking plays an important role in studying marine mammals and other organisms that produce underwater sounds. However, the implementation of such techniques faces many practical challenges, such as lack of environmental data for accurately modeling acoustic propagation, uncertainties in sensor position, time-synchronization of autonomous instruments, and logistical constraints due to large arrays. The three research chapters of this dissertation cumulatively address these hurdles.Chapter 2 develops a reformulation of the “double-difference” method for long-range tracking of acoustic sources. Originally developed for high-resolution localization of earthquakes across a network of widely distributed sensor, the double-difference approach is here adapted to exploit acoustic multipath on a vertical array, deployed in a deep-water waveguide. Results are shown to provide high-precision relative depth and range tracks of sources on the order of 50 km away, by compensating for biases caused by underdetermined array tilt and sound speed model. The method is demonstrated on both a towed acoustic source and a sperm whale (Physeter macrocephalus). Chapter 3 presents a passive time-synchronization technique for independent autonomous acoustic recorders. This approach relies on the coherent ambient noise sources maintaining the same statistical angular distribution around the instruments. Under this assumption, the temporal evolution of the cross-correlation function between sensor pairs reveals their relative time drift. This method enables continuous measurements of clock offset, including small-scale non-linear fluctuations of the drift, otherwise unobservable with standard time-synchronization techniques. Data from a field study in San Ignacio Lagoon, Mexico, is used to demonstrate this technique which is here applied to low frequency pulses, most likely originating from croaker fish (Sciaenidae family). Chapter 4 uses acoustic vector sensor data to track multiple sources simultaneously. The method is demonstrated on singing humpback whales (Megaptera novaeangliae) off western Maui. Here, the directional capabilities of vector sensors are exploited to identify and match azimuthal tracks from multiple sources between sensors, yielding localized whale tracks in terms of latitude and longitude over time. This approach shows potential for further applications such as tracking boats and analyzing the directional properties of ambient noise field