Abstract-Ultra wideband (UWB) Microwave imaging is one of the most promising emerging imaging technologies for breast cancer detection, and is based on the dielectric contrast between normal and cancerous tissues at microwave frequencies. UWB radar imaging involves illuminating the breast with a microwave pulse and reflected signals are used to determine the presence and location of significant dielectric scatterers, which may be representative of cancerous tissue within the breast. Beamformers are used to spatially focus the reflected signals and to compensate for path dependent attenuation and phase effects. While these beamforming algorithms have often been evaluated in isolation, variations in experimental conditions and metrics prompts the assessment of the beamformers on common anatomically and dielectrically representative breast models in order to effectively compare the performance of each. This paper seeks to investigate the following beamforming algorithms: Monostatic and Multistatic DelayAnd-Sum (DAS), Delay-Multiply-And-Sum (DMAS) and Improved Delay-And-Sum (IDAS). The performance of each beamformer is evaluated across a range of appropriate metrics.
A novel wideband microwave radar imaging method is presented to detect regions of significant dielectric contrast within the breast. Clutter reduction is paramount to any radar imaging algorithm, especially with clinical patient data where the tissue composition of the breast is inhomogeneous. Time-domain Data-Adaptive imaging methods have been previously applied in a narrowband manner for microwave radar breast imaging when the received signal spectral content was wideband. In this study, a wideband time-domain adaptive imaging approach is presented to perform Data-Adaptive focusing across the spectrum to reduce clutter. An equalisation filter is adapted to compensate for the propagation distortion through tissue using a calculated estimate of the average dielectric properties of the breast. The effectiveness of the proposed wideband adaptive imaging approach is evaluated in conjunction with the Delay-And-Sum (DAS) method using numerical, experimental and clinical data. Target scatterers are clearly detected while clutter levels are reduced significantly, between 4 and 6 dB, when compared to the DAS technique.
Index Terms-Microwave Imaging, Biomedical Radar Imaging, Ultra-Wideband, Beamforming0018-926X (c)
This repository offers smart-home wearable accelerometer and Radio Signal Strength Indicator (RSSI) data acquired : 1) with low-cost hardware; 2) with high-resolution location annotations; 3) from four UK homes. The data are intended to evaluate RSSI-based indoor localisation methods with activity measurements provided from a user-worn wearable device. A wrist worn accelerometer records activity signatures which are relayed to a number of receiving Access Points (AP) placed throughout the building. Upon reception of a packet, each AP measures the RSSI of the received radio signal and timestamps the accelerometer measurements. Location labels are recorded automatically using a small camera which registers fiducial floor tags as the participant carries out their normal routines in a natural way. Approximately 14 h of annotated wearable measurements are provided. A scripted fingerprint measurement is provided along with several unscripted natural living recordings, where the participant carried out a number of daily household activities which are annotated, where possible, throughout. Codes are provided to access the data and to replicate the ground-truthing procedure.
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