Three dimensional computational imaging with single-pixel detectors

Computational imaging with single-pixel detectors utilises spatial correlation of light to obtain images. A series of structured illumination is generated using a spatial light modulator to encode the spatial information of an object. The encoded object images are recorded as total intensities with no spatial information by a single-pixel detector. These intensities are then sent to correlate with their corresponding illumination structures to derive an image. This correlation imaging method was first recognised as a quantum imaging technique called ghost imaging (GI) in 1995. Quantum GI uses the spatial correlation of entangled photon pairs to form images and was later demonstrated also by using classical correlated light beams. In 2008, an adaptive classical GI system called computational GI which employed a spatial light modulator and a single-pixel detector was proposed. Since its proposal, this computational imaging technique received intensive interest for this potential application. The aim of the work in this thesis was to improve this new imaging technique into a more applicable stage. Our contribution mainly includes three aspects. First an advanced reconstruction algorithm called normalised ghost imaging was developed to improve the correlation efficiency. By normalising the object intensity with a reference beam, the reconstruction single-to-noise ratio can be increased, especially for a more transmissive object. In the second work, a computational imaging scheme adapted from computational GI was designed by using a digital light projector for structured illumination. Compared to a conventional computational GI system, the adaptive system improved the reconstruction efficiency significantly. And for the first time, correlation imaging using structured illumination and single-pixel detection was able to image a 3 dimensional reflective object with reasonable details. By using several single-pixel detectors, the system was able to retrieve the 3 dimensional profile of the object. In the last work, effort was devoted to increase the reconstruction speed of the single-pixel imaging technique, and a fast computational imaging system was built up to generate real-time single-pixel videos

FMCW Signals for Radar Imaging and Channel Sounding

A linear / stepped frequency modulated continuous wave (FMCW) signal has for a long time been used in radar and channel sounding. A novel FMCW waveform known as “Gated FMCW” signal is proposed in this thesis for the suppression of strong undesired signals in microwave radar applications, such as: through-the-wall, ground penetrating, and medical imaging radar. In these applications the crosstalk signal between antennas and the reflections form the early interface (wall, ground surface, or skin respectively) are much stronger in magnitude compared to the backscattered signal from the target. Consequently, if not suppressed they overshadow the target’s return making detection a difficult task. Moreover, these strong unwanted reflections limit the radar’s dynamic range and might saturate or block the receiver causing the reflection from actual targets (especially targets with low radar cross section) to appear as noise. The effectiveness of the proposed waveform as a suppression technique was investigated in various radar scenarios, through numerical simulations and experiments. Comparisons of the radar images obtained for the radar system operating with the standard linear FMCW signal and with the proposed Gated FMCW waveform are also made. In addition to the radar work the application of FMCW signals to radio propagation measurements and channel characterisation in the 60 GHz and 2-6 GHz frequency bands in indoor and outdoor environments is described. The data are used to predict the bit error rate performance of the in-house built measurement based channel simulator and the results are compared with the theoretical multipath channel simulator available in Matlab

Wi-Fi based people tracking in challenging environments

People tracking is a key building block in many applications such as abnormal activity detection, gesture recognition, and elderly persons monitoring. Video-based systems have many limitations making them ineffective in many situations. Wi-Fi provides an easily accessible source of opportunity for people tracking that does not have the limitations of video-based systems. The system will detect, localise, and track people, based on the available Wi-Fi signals that are reflected from their bodies. Wi-Fi based systems still need to address some challenges in order to be able to operate in challenging environments. Some of these challenges include the detection of the weak signal, the detection of abrupt people motion, and the presence of multipath propagation. In this thesis, these three main challenges will be addressed. Firstly, a weak signal detection method that uses the changes in the signals that are reflected from static objects, to improve the detection probability of weak signals that are reflected from the person’s body. Then, a deep learning based Wi-Fi localisation technique is proposed that significantly improves the runtime and the accuracy in comparison with existing techniques. After that, a quantum mechanics inspired tracking method is proposed to address the abrupt motion problem. The proposed method uses some interesting phenomena in the quantum world, where the person is allowed to exist at multiple positions simultaneously. The results show a significant improvement in reducing the tracking error and in reducing the tracking delay

Roadmap on signal processing for next generation measurement systems

Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.AerodynamicsMicrowave Sensing, Signals & System

Photoacoustic Elastography and Next-generation Photoacoustic Tomography Techniques Towards Clinical Translation

Ultrasonically probing optical absorption, photoacoustic tomography (PAT) combines rich optical contrast with high ultrasonic resolution at depths beyond the optical diffusion limit. With consistent optical absorption contrast at different scales and highly scalable spatial resolution and penetration depth, PAT holds great promise as an important tool for both fundamental research and clinical application. Despite tremendous progress, PAT still encounters certain limitations that prevent it from becoming readily adopted in the clinical settings. This dissertation aims to advance both the technical development and application of PAT towards its clinical translation. The first part of this dissertation describes the development of photoacoustic elastography techniques, which complement PAT with the capability to image the elastic properties of biological tissue and detect pathological conditions associated with its alterations. First, I demonstrated vascular-elastic PAT (VE-PAT), capable of quantifying blood vessel compliance changes due to thrombosis and occlusions. Then, I developed photoacoustic elastography to noninvasively map the elasticity distribution in biological tissue. Third, I further enhanced its performance by combing conventional photoacoustic elastography with a stress sensor having known stress–strain behavior to achieve quantitative photoacoustic elastography (QPAE). QPAE can quantify the Young’s modulus of biological tissues on an absolute scale. The second part of this dissertation introduces technical improvements of photoacoustic microscopy (PAM). First, by employing near-infrared (NIR) light for illumination, a greater imaging depth and finer lateral resolution were achieved by near-infrared optical-resolution PAM (NIR-OR-PAM). In addition, NIR-OR-PAM was capable of imaging other tissue components, including lipid and melanin. Second, I upgraded a high-speed functional OR-PAM (HF-OR-PAM) system and applied it to image neurovascular coupling during epileptic seizure propagation in mouse brains in vivo with high spatio-temporal resolution. Last, I developed a single-cell metabolic PAM (SCM-PAM) system, which improves the current single-cell oxygen consumption rate (OCR) measurement throughput from ~30 cells over 15 minutes to ~3000 cells over 15 minutes. This throughput enhancement of two orders of magnitude achieves modeling of single-cell OCR distribution with a statistically meaningful cell count. SCM-PAM enables imaging of intratumoral metabolic heterogeneity with single-cell resolution. The third part of this dissertation introduces the application of linear-array-based PAT (LA-PAT) in label-free high-throughput imaging of melanoma circulating tumor cells (CTCs) in patients in vivo. Taking advantage of the strong optical absorption of melanin and the unique capability of PAT to image optical absorption, with 100% relative sensitivity, at depths with high ultrasonic spatial resolution, LA-PAT is inherently suitable for melanoma CTC imaging. First, with a center ultrasonic frequency of 21 MHz, the LA-PAT system was able to detect melanoma CTCs clusters and quantify their sizes based on the contrast-to-noise ratio (CNR). Second, I developed an LA-PAT system with a center ultrasonic frequency of 40 MHz and imaged melanoma CTCs in patients in vivo with a CNR greater than 12. We successfully imaged 16 melanoma patients and detected melanoma CTCs in 3 of them. Among the CTC-positive patients, 67% had disease progression despite systemic therapy. In contrast, only 23% of the CTC-negative patients showed disease progression. This study lays a solid foundation for translating CTC detection to bedside for clinical care and decision-making

Millimetre-Resolution Photonics-Assisted Radar

Radar is essential in applications such as anti-collision systems for driving, airport security screening, and contactless vital sign detection. The demand for high-resolution and real-time recognition in radar applications is growing, driving the development of electronic radars with increased bandwidth, higher frequency, and improved reconfigurability. However, conventional electronic approaches are challenging due to limitations in synthesising radar signals, limiting performance. In contrast, microwave photonics-enabled radars have gained interest because they offer numerous benefits compared to traditional electronic methods. Photonics-assisted techniques provide a broad fractional bandwidth at the optical carrier frequency and enable spectrum manipulation, producing wideband and high-resolution radar signals in various formats. However, photonic-based methods face limitations like low time-frequency linearity due to the inherent nonlinearity of lasers, restricted RF bandwidth, limited stability of the photonic frequency multipliers, and difficulties in achieving extended sensing with dispersion-based techniques. In response to these challenges, this thesis presents approaches for generating broadband radar signals with high time-frequency linearity using recirculated unidirectional optical frequency-shifted modulation. The photonics-assisted system allows flexible bandwidth tuning from sub-GHz to over 30 GHz and requires only MHz-level electronics. Such a system offers millimetre-level range resolution and a high imaging refresh rate, detecting fast-moving objects using the ISAR technique. With millimetre-level resolution and micrometre accuracy, this system supports contactless vital sign detection, capturing precise respiratory patterns from simulators and a living body using a cane toad. In the end, we highlight the promise of merging radar and LiDAR, foreshadowing future advancements in sensor fusion for enhanced sensing performance and resilience

Microfluidics and Nanofluidics Handbook

The Microfluidics and Nanofluidics Handbook: Two-Volume Set comprehensively captures the cross-disciplinary breadth of the fields of micro- and nanofluidics, which encompass the biological sciences, chemistry, physics and engineering applications. To fill the knowledge gap between engineering and the basic sciences, the editors pulled together key individuals, well known in their respective areas, to author chapters that help graduate students, scientists, and practicing engineers understand the overall area of microfluidics and nanofluidics. Topics covered include Finite Volume Method for Numerical Simulation Lattice Boltzmann Method and Its Applications in Microfluidics Microparticle and Nanoparticle Manipulation Methane Solubility Enhancement in Water Confined to Nanoscale Pores Volume Two: Fabrication, Implementation, and Applications focuses on topics related to experimental and numerical methods. It also covers fabrication and applications in a variety of areas, from aerospace to biological systems. Reflecting the inherent nature of microfluidics and nanofluidics, the book includes as much interdisciplinary knowledge as possible. It provides the fundamental science background for newcomers and advanced techniques and concepts for experienced researchers and professionals

Liquid Crystal on Silicon Devices: Modeling and Advanced Spatial Light Modulation Applications

Liquid Crystal on Silicon (LCoS) has become one of the most widespread technologies for spatial light modulation in optics and photonics applications. These reflective microdisplays are composed of a high-performance silicon complementary metal oxide semiconductor (CMOS) backplane, which controls the light-modulating properties of the liquid crystal layer. State-of-the-art LCoS microdisplays may exhibit a very small pixel pitch (below 4 ?m), a very large number of pixels (resolutions larger than 4K), and high fill factors (larger than 90%). They modulate illumination sources covering the UV, visible, and far IR. LCoS are used not only as displays but also as polarization, amplitude, and phase-only spatial light modulators, where they achieve full phase modulation. Due to their excellent modulating properties and high degree of flexibility, they are found in all sorts of spatial light modulation applications, such as in LCOS-based display systems for augmented and virtual reality, true holographic displays, digital holography, diffractive optical elements, superresolution optical systems, beam-steering devices, holographic optical traps, and quantum optical computing. In order to fulfil the requirements in this extensive range of applications, specific models and characterization techniques are proposed. These devices may exhibit a number of degradation effects such as interpixel cross-talk and fringing field, and time flicker, which may also depend on the analog or digital backplane of the corresponding LCoS device. The use of appropriate characterization and compensation techniques is then necessary