Passive acoustic mapping (PAM) is a promising imaging method that enables real-time three-dimensional monitoring of ultrasound therapy through the reconstruction of acoustic emissions passively received on an array of ultrasonic sensors. A passive beamforming method is presented that provides greatly improved spatial accuracy over the conventionally used time exposure acoustics (TEA) PAM reconstruction algorithm. Both the Capon beamformer and the robust Capon beamformer (RCB) for PAM are suggested as methods to reduce interference artifacts and improve resolution, which has been one of the experimental issues previously observed with TEA. Simulation results that replicate the experimental artifacts are shown to suggest that bubble interactions are the chief cause. Analysis is provided to show that these multiple bubble artifacts are generally not reduced by TEA, while Capon-based methods are able to reduce the artifacts. This is followed by experimental results from in vitro experiments and in vivo oncolytic viral therapy trials that show improved results in PAM, where RCB is able to more accurately localize the acoustic activity than TEA.

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Multiple sensor arrays provide the means for highly accurate localization of the (x, y) position of a source. In some applications, such as microphone arrays receiving aeroacoustic signals from ground vehicles, random fluctuations in the air lead to frequency-selective coherence losses in the signals that arrive at widely-separated sensors. We present performance analysis for localization of a wideband source using multiple, distributed sensor arrays. The wavefronts are modeled with perfect spatial coherence over individual arrays and frequency-selective coherence between distinct arrays, and the sensor signals are modeled as wideband, Gaussian random processes. Analysis of the Cramér-Rao bound (CRB) on source localization accuracy reveals that a distributed processing scheme involving bearing estimation at the individual arrays and time-delay estimation (TDE) between sensors on different arrays performs nearly as well as the optimum scheme, while requiring less communication bandwidth with a central processing node. We develop Ziv-Zakai bounds for TDE with partially coherent signals in order to study the achievability of the CRB. This analysis shows that a threshold value of coherence is required in order to achieve accurate time-delay estimates, and the threshold coherence value depends on the source signal bandwidth, the additive noise level, and the observation time. Results are included based on processing measured aeroacoustic data from ground vehicles to illustrate the frequency-dependent signal coherence and the TDE performance.

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