Indoor device-free localization (DFL) has many uses, including aged care, location-based services, ambient-assisted living, and fire safety management. In recent publications, thermopile sensors (very low-resolution infrared cameras) have been shown as being able to localize individuals while preserving their privacy. This article reports the performance evaluation of a large number of supervised machine learning techniques for the localization of a target using a ceiling-mounted thermopile. The algorithms were trained and validated using a large data set constructed from an individual walking arbitrary paths with the accurate ground truth provided by a virtual reality system. For robust performance evaluation, the algorithms were tested with data sets collected on a different day with several other subjects. A 2-D convolutional neural network exploiting spatial correlation and several recurrent neural network structures exploiting temporal correlation among the captured data provided the most accurate localization performance. Several data sets, constructed from the thermopile’s readings for four individual targets, were made available online for other researchers to use.

Ultrasonic guided wave-based nondestructive testing systems are widely used in various fields of industry where the structural integrity of components is of vital importance. Signal interpretation in these systems might become challenging due to multimodal and dispersive response of the interrogated structure. These phenomena degrade the signal-to-noise ratio and also lower the spatial/temporal resolution. This paper compares the use of Maximal Length Sequences and linear chirp excitation signals to develop a novel signal processing technique using dispersion compensation and cross-correlation. The technique is applied to both simulated and experimental multimodal signals from an aluminium rod for performance assessment. It is quantitatively validated that the technique noticeably improves the signal-to-noise ratio of the guided wave response and is able to acquire an accurate time of flight of the individual wave modes, and hence, the propagation distance. The technique is compared for both linear chirp and maximal length sequences excitation signals. Noise analysis for these excitation signals is also presented.

Ultrasonic Guided Wave (UGW) based NonDestructive Testing (NDT) systems are widely used in numerous branches of industry, where the structural integrity of components carries vital importance. In those systems, signal interpretations might become challenging due to multi-modal and dispersive response of the structure under examination. This results in degradation of the signals in terms of Signal-to-Noise Ratio (SNR) and spatial/temporal resolution. This paper uses Maximal Length Sequences (MLS) to develop a novel signal processing technique by employing the Short-Time Fourier Transform (STFT), dispersion compensation and cross-correlation. The technique is applied to experimental multi-modal signals from an aluminum rod for performance verification. It is quantitatively validated that the technique noticeably improves the SNR of the guided wave response, and is able to derive an accurate time of flight of the individual wave modes and thus the propagation distance.

We present a calibration technique for an acoustic imaging microphone array, combined with a digital camera. Computer vision and acoustic time of arrival data are used to obtain microphone coordinates in the camera reference frame. Our new method allows acoustic maps to be plotted onto the camera images without the need for additional camera alignment or calibration. Microphones and cameras may be placed in an ad-hoc arrangement and, after calibration, the coordinates of the microphones are known in the reference frame of a camera in the array. No prior knowledge of microphone positions, inter-microphone spacings, or air temperature is required. This technique is applied to a spherical microphone array and a mean difference of 3 mm was obtained between the coordinates obtained with this calibration technique and those measured using a precision mechanical method.