Passive acoustic non-line-of-sight localization without a relay surface

The detection and localization of a source hidden outside the Line-of-Sight (LOS) traditionally rely on the acquisition of indirect signals, such as those reflected from visible relay surfaces such as floors or walls. These reflected signals are then utilized to reconstruct the obscured scene. In this study, we present an approach that utilize signals diffracted from an edge of an obstacle to achieve three-dimensional (3D) localization of an acoustic point source situated outside the LOS. We address two scenarios - a doorway and a convex corner - and propose a localization method for each of them. For the first scenario, we utilize the two edges of the door as virtual detector arrays. For the second scenario, we exploit the spectral signature of a knife-edge diffraction, inspired by the human perception of sound location by the head-related transfer function (HRTF). In both methods, knife-edge diffraction is utilized to extend the capabilities of non-line-of-sight (NLOS) acoustic sensing, enabling localization in environments where conventional relay-surface based approaches may be limited.

K-space interpretation of image-scanning-microscopy

In recent years, image-scanning microscopy (ISM, also termed pixel-reassignment microscopy) has emerged as a technique that improves the resolution and signal-to-noise compared to confocal and widefield microscopy by employing a detector array at the image plane of a confocal laser scanning microscope. Here, we present a k-space analysis of coherent ISM, showing that ISM is equivalent to spotlight synthetic-aperture radar (SAR) and analogous to oblique-illumination microscopy. This insight indicates that ISM can be performed with a single detector placed in the k-space of the sample, which we numerically demonstrate.

Pixel-reassignment in Ultrasound Imaging

We present an adaptation of the pixel-reassignment technique from confocal fluorescent microscopy to coherent ultrasound imaging. The method, Ultrasound Pixel-Reassignment (UPR), provides a resolution and signal to noise (SNR) improvement in ultrasound imaging by computationally reassigning off-focus signals acquired using traditional plane-wave compounding ultrasonography. We theoretically analyze the analogy between the optical and ultrasound implementations of pixel reassignment, and experimentally evaluate the imaging quality on tissue-mimicking acoustic phantoms. We demonstrate that UPR provides a $25\%$ resolution improvement and a $3dB$ SNR improvement in in-vitro scans, without any change in hardware or acquisition scheme.