FMCW radars are widely used in the process industry for range estimation, usu- ally for estimating the liquid level in a tank. Since the tank system, often is an automatically controlled system, reliable estimates of the surface level are re- quired, e.g. to avoid the tank from pouring over or become empty. The goal of this thesis is to investigate methods which can distinguish fre- quencies closer to each other than the FFT resolution limit. Two properties are of interest, the accuracy and the resolution performance. Three such methods have been evaluated: one that tries to compensate for the leakage and interference of close frequencies, one subspace-based method and one deconvolution method. The deconvolution is performed with the iterative Lucy Richardson algorithm. The methods are evaluated against each other and against a typical FFT based algorithm. The methods sensitivity to amplitude differences is examined together with the robustness against noise and disturbances which appear due to imperfections in the radar unit. The deconvolution algorithm is the one that performs the best. The subspace-based method SURE requires prior knowledge of the number of ingoing frequencies which is difficult to know for real data from an FMCW radar. The leakage compensation method main weakness is the influence of the phase difference between close frequencies. The deconvolution algorithm is evaluated on some real data, and it is proven that it has better resolution performance than the FFT. However, the accuracy of the estimates are dependent on the number of iterations used. With a large num- ber of iterations, the algorithm finds peaks with small amplitude nearby the large peaks and they will thus interact and hence contribute to a worse accuracy even in the undisturbed case. If too few iterations are used in the deconvolution algo- rithm the resolution performance is about the same as the FFT algorithm. With a suitable choice of iterations about 40–50 mm, extra of continuous measurements are achieved. However, the estimation error of the gained resolution can in the worst case be about 40–50 mm.

Multistory parking can accommodate a maximum number of vehicles in a limited space. However, in multistory and outdoor busy parking, it becomes challenging for drivers to find free parking slots, and they have to search in different parking lanes and floors. This results in the wastage of fuel and time and contaminates the atmosphere. To address this issue, the state-of-the-art solution exploits an optical sensor to detect if a car is present in the parking slot or not. The solution requires an optical sensor for each parking slot, which makes the optical sensor solution expensive and complex. Moreover, such a solution fails in harsh weather conditions in outdoor parking. A low-cost mm-wave radar-based solution is proposed to detect multiple cars using only one radar and pass the corresponding information to the developed computer/mobile app. Using the app, users can view the free parking slots in advance. Our proposed solution also provides free parking slot information at the parking entrance. A driver can select one from the available ones and park his car there. In the next version, people will be able to book the parking slots from the available ones. To detect the presence of vehicle in multiple parking slots, our proposed system uses Infineon’s Postion2Go module, which is one transmit and two receive antenna frequency-modulated continuous-wave (FMCW) radar. We develop a parking model using stationary objects, clutter, and vehicles in the parking. The vehicle detection algorithm is based on background subtraction and updation. First, the background is subtracted from each received snapshot to prominent the parking slot where the latest activity has been done. Then, once the activity is stable (the vehicle is fully parked or left), the background is updated. The algorithm also uses constant-false-alarm-rate (CFAR) for adaptive detection of vehicles and thresholds to detect different activities. The method of monitoring outdoor parking is simple, while the indoor parking is more challenging. Demonstrated results show the effectiveness of the proposed system.

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Supervision of human vital signs has always been an essential part in healthcare. Nowadays there is a strong interest in contact-less monitoring methods as they operate less static and offer higher flexibility to the people observed. Recent industrial development enabled radar functionality to be packed in single-chip solutions, decreasing application complexity and speeding up designs. Within this thesis, a vital sign radar prototype has been developed utilising a recently released 60GHz frequency modulated continous wave single-chip radar. The electronics development has been focused on compactness and high system integration. Special attention has been given to the onboard analogue signal filtering and digital data preprocessing. The resulting prototype radar is then tested and evaluated using test scenarios with increasing difficulty. The final experiments prove that the radar is capable of tracking human respiration rate and heartbeat simultaneously from a distance of 1m. It can be concluded that modern radar devices may be significantly miniaturised for e.g. portable operation while offering a wide variety of application possibilities including vital sign monitoring.

This dissertation examines and analyzes novel techniques that are useful in the collection and processing of data from a Frequency Modulated Continuous Wave Radar. The major topics discussed in this work are: reduction of amplitude modulation, signature collection without an anechoic chamber, transforming a signature into a matched filter, accounting for electromagnetic interference, accounting for digital noise, and the application of a Support Vector Machine to achieve classification. In addition, this work also provides a broad overview of a framework specifically developed to improve detection and classification without requiring expensive hardware modification. The four main categories analyzed in this work are distortion, spectral signature, optimal detection, and classification. Some notable contributions in this work include the assessment of a novel technique’s effectiveness to improve model accuracy by accounting for amplitude modulation in an FMCW radar, as well as discussion of improved techniques to perform signature collection with an FMCW radar in the absence of an anechoic chamber. The signature collection technique is a novel approach that utilizes physics and wavelets in an effort to improve Signal to Noise Ratio (SNR). This work also considers a novel technique to convert an FMCW target signature into coefficients for a matched filter, thus allowing for the full mathematical application of the optimal matched filter. In addition, this work provides an analysis of the improved performance of an FMCW radar through the development and use of a novel technique to account for both electromagnetic interference and digital noise. Finally the initial discovery, development, and refinement of an innovative application using SVM to classify the matched filter results of FMCW radar targets is given, thus resulting in previously uncollected and undocumented viable baseline data.

Limitations of current eldercare monitoring systems leave a need for new solutions. A monitoring system based on a frequency modulated continuous wave ultra-wideband short-range radar is proposed for this application. The complete proposed monitoring system is comprised of four blocks: boundary detection, silhouette capture, human identification, and data transmission. This paper develops the RF front end hardware for the silhouette capture subsystem. System requirements are derived for the silhouette capture subsystem. An architecture for the RF front end is designed, and required individual component specifications are determined. Components are selected off the shelf or custom designed for each socket. Full transmitter and receiver level plans are calculated to ensure expected system performance meets system requirements. A component library and full system schematic is created, PCB layout is completed, and PCB files are generated and sent for fabrication. PCB traces and individual components are characterized over frequency, and methods that improve inadequate performance are documented and discussed.

Radar sensors hold excellent capabilities to estimate distance and motion accu- rately, penetrate nonmetallic objects, and remain unaffected by weather conditions. These capabilities make these devices extremely flexible in their applications. Elec- tromagnetic waves centered at frequencies around 24 GHz offer high precision target measurements, compact antenna and circuitry design, and lower atmospheric absorp- tion than higher frequency-based systems. This thesis presents a case study for a 24 GHz frequency modulated continuous wave radar module. We start by addressing the theoretical background necessary for this work and describing the architecture of the module used. We present three classes’ classification accuracy, namely pedes- trians, cyclists, and cars. A set of features for the classification is designed based on theoretical models, and their effectiveness is validated through experiments. The features are extracted from the available geometrical and motion-related information and used to train different classification models to compare the results. Finally, a trade-off between feature number and accuracy is presented.

Acoustic Frequency Domain Reflectometry (AFDR) is a novel technique employing frequency modulated continuous wave (FMCW) methods in solid acoustic waveguide reflectometry. It is particularly suited to dispersion compensation and phase compensation due to the measurement domain being the frequency domain. This work rigorously analyzes, develops, and experimentally demonstrates AFDR, alongside various compensation methods and demodulation techniques. Distributed measurement of temperature is tested using several novel signal processing algorithms for strain determination and is estimated to have a resolution of 0.58 °C over a 20 cm gauge length. An error correction algorithm to improve SNR in the measurement of strain is proposed and validated. The sensing system has a theoretical spatial resolution of 2 mm and an estimated sensing resolution limit of about 1 cm. AFDR and the associated signal processing developments are positioned to be transformative across many areas of acoustics, with significant potential for distributed sensing along an acoustic waveguide. / Doctor of Philosophy / Acoustic Frequency Domain Reflectometry (AFDR) is demonstrated as a novel method for using acoustic waves to sense different material parameters. Acoustic waves can be guided down various structures, such as a metal wire. Rather than sending out a short burst of acoustic power and analyzing its echoes in the metal wire, this technique uses a constant source of acoustic waves with varying frequency, instead recording how the electrical characteristics of the acoustic source change as frequency changes. Since the measurement is made across frequency, this method is particularly suited to correct for various aspects of the acoustic wave that change with frequency in an otherwise undesirable way. The ability to compensate for acoustic wave speeds that change with frequency as well as imperfections intrinsic to the tuning itself using multiple new methods is demonstrated. Distributed measurement of temperature is tested using various signal processing algorithms, and estimated to have a resolution of 0.58 °C for a 20 cm sensing length. The validated sensing system theoretically has the ability to resolve changes over 2 mm, and the resolution over which sensing may be possible is estimated to be 1 cm. AFDR and the associated signal processing developments are positioned to be transformative across many areas of acoustics, with significant potential for distributed sensing along an acoustic waveguide.

<p>Denna rapport behandlar en fullständig metod för att följa, associera och klassificera ekospår. Vid radarnivåmätning ska ekon som härstammar ifrån samma fysikaliska objekt följas över tiden och klassificeras. Dagens radarnivågivare löser problemet genom konfiguration. Tankens geometri samt vilka störande objekt som finns anges vid installation.</p><p>Den framtagna metoden har delats upp i tre delmoment. Först binds individuella inmätta ekon samman till linjesegment. Dessa segment associeras samman till ekospår varefter dessa klassas fysikaliskt. Metoden kräver betydligt mindre konfiguration än den lösning som används för tillfället.</p> / <p>In this report a method for target tracking, association and classification of echo tracks in radar level gauges is discussed. In tank gauging echoes from the same physical object are called an echo track. The echoes must be tracked over time and classified. Currently radar level gauge units requires configuration to achieve classifications of echo</p><p>tracks. At installation tank geometry and disturbing echoes has to be registered.</p><p>The method has been divided into three parts. Firstly individual measured echoes are replaced by line segments. Association algorithms then create echo tracks from these segments. The third step is to classify these tracks physically. This method eliminates registering of disturbing echoes.</p>

Denna rapport behandlar en fullständig metod för att följa, associera och klassificera ekospår. Vid radarnivåmätning ska ekon som härstammar ifrån samma fysikaliska objekt följas över tiden och klassificeras. Dagens radarnivågivare löser problemet genom konfiguration. Tankens geometri samt vilka störande objekt som finns anges vid installation. Den framtagna metoden har delats upp i tre delmoment. Först binds individuella inmätta ekon samman till linjesegment. Dessa segment associeras samman till ekospår varefter dessa klassas fysikaliskt. Metoden kräver betydligt mindre konfiguration än den lösning som används för tillfället. / In this report a method for target tracking, association and classification of echo tracks in radar level gauges is discussed. In tank gauging echoes from the same physical object are called an echo track. The echoes must be tracked over time and classified. Currently radar level gauge units requires configuration to achieve classifications of echo tracks. At installation tank geometry and disturbing echoes has to be registered. The method has been divided into three parts. Firstly individual measured echoes are replaced by line segments. Association algorithms then create echo tracks from these segments. The third step is to classify these tracks physically. This method eliminates registering of disturbing echoes.