Cost reduction has been and will continue to be a primary driving force in the evolution of hardware design and associated technologies. The objective of this research is to design low-cost signal acquisition systems for characterizing wideband and high-speed signals. As the bandwidth and the speed of such signals increase, the cost of testing also increases significantly; therefore, innovative hardware and algorithm co-design are needed to relieve this problem. In Chapter 2, a low-cost multi-rate system is proposed for characterizing the spectra of wideband signals. The design is low-cost in the sense of the actual component cost, the system complexity, and the effort required for calibration. The associated algorithms are designed such that the hardware can be implemented with low-complexity yet be robust enough to deal with various hardware variations. A hardware prototype is built not only to verify the proposed hardware scheme and algorithms but to serve as a concrete example that shows that characterizing signals with sub-Nyqusit sampling rate is feasible. Chapter 3 introduces a low-cost time-domain waveform reconstruction technique, which requires no mutual synchronization mechanisms. This brings down cost significantly and enables the implementation of systems capable of capturing tens of Gigahertz (GHz) signals for significantly lower cost than high-end oscilloscopes found in the market today. For the first time, band-interleaving and incoherent undersampling techniques are combined to form a low-cost solution for waveform reconstruction. This is enabled by co-designing the hardware and the back-end signal processing algorithms to compensate for the lack of coherent Nyquist rate sampling hardware. A hardware prototype was built to support this work. Chapter 4 describes a novel test methodology that significantly reduces the required time for crosstalk jitter characterization in parallel channels. This is done by using bit patterns with coprime periods as channel stimuli and using signal processing algorithms to separate multiple crosstalk coupling effects. This proposed test methodology can be applied seamlessly in conjunction with the current test methodology without re-designing the test setup. More importantly, the conclusion derived from the mathematical analysis shows that only such test stimuli give unbiased characterization results, which are critical in all high-precision test setups. Hardware measurement results and analysis are provided to support this methodology. This thesis starts with an overview of the background and a literature review. Three major previously mentioned works are addressed in three separate chapters. Each chapter documents the hardware designs, signal processing algorithms, and associated mathematical analyses. For the purpose of verification, the hardware measurement setups and results are discussed at the end of these three chapters. The last chapter presents conclusions and future directions for work from this thesis.

Current controls the motion of a manipulator. The manipulators at ABB are powered by a three-phase alternating current system where shunt resistors are utilised to measure the current to the motors. Magnetic field sensors are instead investigated to eliminate issues with power losses, the number of components and the cost of the shunt resistors. Since current produces a magnetic field, it can be measured without contact using a magnetic field sensor. However, employing non-contact magnetic field sensors in three-phase implementations introduces problems with stray magnetic fields due to the three traces being in close proximity to each other. This magnetic crosstalk will influence the sensors, hence the current measurement for each trace. In this thesis separating this influence of the magnetic fields is done through a software approach. Initially, two magnetic field sensors, a tunnel magnetoresistance sensor and a Fluxgate sensor, were tested and evaluated to gain knowledge and understanding. From the different tests, it was decided to continue with the Fluxgate sensor. Further, a partial least-squares regression was constructed to separate the magnetic field and predict the current in each trace from the Fluxgate sensor output. From a simulation created, the current could be predicted with an error of approximately 1 nA, meaning less than 0.1% when considering a simulated linear model of the Fluxgate sensor.