<p>Clutter is a problematic noise artifact in a variety of ultrasound applications. Clinical tasks complicated by the presence of clutter include detecting cancerous lesions in abdominal organs (e.g. livers, bladders) and visualizing endocardial borders to assess cardiovascular health. In this dissertation, an analytical expression for contrast loss due to clutter is derived, clutter is quantified in abdominal images, and sources of abdominal clutter are identified. Novel clutter reduction methods are also presented and tested in abdominal and cardiac images. </p><p>One of the novel clutter reduction methods is Short-Lag Spatial Coherence (SLSC) imaging. Instead of applying a conventional delay-and-sum beamformer to measure the amplitude of received echoes and form B-mode images, the spatial coherence of received echoes are measured to form SLSC images. The world's first SLSC images of simulated, phantom, and <italic>in vivo</italic> data are presented herein. They demonstrate reduced clutter and improved contrast, contrast-to-noise, and signal-to-noise ratios compared to conventional B-mode images. In addition, the resolution characteristics of SLSC images are quantified and compared to resolution in B-mode images. </p><p>A clinical study with 14 volunteers was conducted to demonstrate that SLSC imaging offers 19-33% improvement in the visualization of endocardial borders when the quality of B-mode images formed from the same echo data was poor. There were no statistically significant improvements in endocardial border visualization with SLSC imaging when the quality of matched B-mode images was medium to good.</p> / Dissertation

Due to recent improvements, robots are more applicable in factories and various production lines where smoke, fog, dust, and steam are inevitable. Despite their advantages, robots introduce new safety requirements when combined with humans. Radars can play a crucial role in this context by providing safe zones where robots are operating in the absence of humans. The goal of this Master’s thesis is to investigate different clutter suppression methods for single radar sensor reflection data via digital signal processing. This was done in collaboration with ABB Jokab AB, Sweden. The calculations and implementation of the digital signal processing algorithms are made with Octave. A critical problem is false detection that could possibly cause irreparable damage. Therefore, a safety system with an extremely low false alarm rate is desired to reduce costs and damages. In this project, we have studied four different digital low pass filters: moving average, multiple-pass moving average, Butterworth, and window-based filters. The results are compared, and it is ascertained that all the results are logically compatible, broadly comparable, and usable in this context.

<div>Pavement drainage systems are one of the key drivers of pavement function and longevity, and effective drain maintenance can significantly extend a pavement's service life. Maintenance of these drains, however, is often hampered by the challenge of locating the drains. Ground Penetrating Radar (GPR) typically offers a rapid and effective method to detect these underground targets. However, typical detection schema that rely upon the observation of the hyperbolic return from a GPR scan of a buried conduit still tend to miss many of the older drains beneath pavements as they may be partially or fully filled with sediment and/or may be fabricated from clay or other earthen materials, yielding a return signal that is convolved with significant background noise. </div><div><br></div><div>To manage this challenge, this work puts forward an improved background noise and clutter reduction method to enhance the target signals in what amounts to a constructed environment that tends to have more consistent subsurface properties than one might encounter in a general setting. Within this technique, two major algorithms are employed. Algorithm 1 is the core of this method, and plays the role of reducing background noise and clutter. Algorithm 2 is supplementary, and helps eliminate anomalous discontinuous returns generated by the equipment itself, which could otherwise lead to false detection indications in the output of Algorithm 1. Instead of traditional 2-D GPR images, the result of the proposed algorithms is a 1-D plot along the survey line, highlighting a set of “points of interest” that could indicate buried drain locations identified at any given GPR operating frequency. Subsurface exploration using two different operating frequencies, 900 MHz and 400 MHz herein, is then employed to further enhance detection confidence. Points of interest are ultimately coded to define the confidence of the detection. Comparing the final result of proposed algorithms with the original GPR images, the improved algorithm is demonstrated to provide significantly improved detection results, and could potentially be applied to similar problems in other contexts.</div><div><br></div><div>Besides the background reduction methods, a group of simulations performed using GPRMAX2D software are examined to explore the influence of road cross-section designs on sub-pavement drainage conduit GPR signatures, and evaluate the effectiveness of alternate GPR antennae configurations in locating these buried conduits in different ground conditions. Two different models were explored to simulate conduit detection. In addition, different pipe and soil conditions were modeled, such as pipe size, pipe material, soil moisture level, and soil type. Four different quantitative measurements are used to analyze GPR performance based on different key factors. The four measurements are 1) signal to background ratio (SBR) in dB; 2) signal to receiver noise ratio (SNR) in dB; 3) signal energy in Volts; and 4) average signal band power in Watts.</div><div><br></div><div>The water and clay content of subsurface soil can significantly influence the detection results obtained from ground penetrating radar (GPR). Due to the variation of the material properties underground, the center frequency of transmitted GPR signals shifts to a lower range as wave attenuation increases. Examination of wave propagation in the subsurface employing an attenuation filter based on a linear system model shows that received GPR signals will be shifted to lower frequencies than those originally transmitted. The amount of the shift is controlled by a wave attenuation factor, which is determined by the dielectric constant, electric conductivity, and magnetic susceptibility of the transmitted medium. This work introduces a receiver-transmitter-receiver dual-frequency configuration for GPR that employs two operational frequencies for a given test - one higher and one slightly lower - to take advantage of this phenomenon to improve subpavement drain detection results. In this configuration, the original signal is transmitted from the higher frequency transmitter. After traveling through underground materials, the signal is received by two receivers with different frequencies. One of the receivers has the same higher center frequency as the transmitter, and the other receiver has a lower center frequency. This configuration can be expressed as Rx(low-frequency)-Tx(high-frequency)-Rx(high-frequency) and was applied in both laboratory experiments and field tests. Results are analyzed in the frequency domain to evaluate and compare the properties of the signal obtained by both receivers. The laboratory experiment used the configuration of Rx(400MHz)-Tx(900MHz)-Rx(900MHz). The field tests, in addition to the configuration used in the lab tests, employed another configuration of Rx(270MHz)-Tx(400MHz)-Rx(400MHz) to obtain more information about this phenomenon. Both lab and field test results illustrate the frequency-shift phenomenon described by theoretical calculations. Based on the power spectrum for each signal, the lower frequency antenna typically received more energy (higher density values) at its peak frequency than the higher frequency antenna.</div>