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.

Continuous-wave frequency-modulated radar, or FMCW radar, is simple in design, small in size and weight and uses low transmitting power. The range resolution depends on the bandwidth. FMCWradar is used in applications ranging from guided weapons systems to vehicle collision avoidance systems. Measuring the distance to the target is the essential feature of FMCW radar. Firstly, this thesis introduces the basic structure of the FMCW radar and the principle formeasuring distance. Secondly, by using software-dened radio (SDR),FMCW radar can be implemented and congured with a reduced costand complexity. In this report, the radar is implemented by means ofthe software GNU Radio Companion with a test signal. HackRF may be used in future work with an osmocom source instead of the testsignal.

Machine learning has been employed in the automotive industry together with cameras to detect objects in surround sensing technology. You Only Look Once is a state-of-the-art object detection algorithm especially suitable for real-time applications due to its speed and relatively high accuracy compared to competing methods. Recent studies have investigated whether radar data can be used as an alternative to camera data with You Only Look Once, seeing as radars are more robust to changing environments such as various weather and lighting conditions. These studies have used 3D data from radar consisting of range, angle, and velocity, transformed into a 2D image representation, either in the Range-Angle or Range-Doppler domain. Furthermore, the processed radar image can use either a Cartesian or a polar coordinate system for the rendering. This study will combine previous studies, using You Only Look Once with Range-Angle radar images and examine which coordinate system of Cartesian or polar is most optimal. Additionally, evaluating the localization and classification performance will be done using a combination of concepts and evaluation metrics. Ultimately, the conclusion is that the Cartesian coordinate system prevails with asignificant improvement compared to polar. / Maskininlärning har sedan länge använts inom fordinsindustrin tillsammans med kameror för att upptäcka föremål och få en ökad överblick över omgivningar. You Only Look Once är en toppmodern objektdetekteringsalgoritm särskilt lämplig för realtidsapplikationer tack vare dess hastighet och relativt höga noggrannhet jämfört med konkurrerande metoder. Nyligen genomförda studier har undersökt om radardata kan användas som ett alternativ till kameradata med You Only Look Once, eftersom radar är mer robusta för ändrade miljöer så som olika väder- och ljusförhållanden. Dessa studier har utnyttjat 3D data från radar bestående av avstånd, vinkel och hastighet, som transformerats till en 2D bildrepresentation, antingen i domänen Range-Angle eller Range-Doppler. Vidare kan den bearbetade radarbilden använda antingen ett kartesiskt eller ett polärt koordinatsystem för framställningen. Denna studie kommer att kombinera tidigare studier om You Only Look Once med Range-Angle radarbilder och undersöka vilket koordinatsystem, kartesiskt eller polärt, som är mest optimalt att använda för människodetektering med radar. Dessutom kommer en utvärdering av lokaliserings- och klassificeringsförmåga att göras med hjälp av en blandning av koncept och olika mått på prestanda. Slutsatsen gjordes att det kartesiska koordinatsystemet är det bättre alternativet med en betydligt högre prestanda jämfört med det polära koordinatsystemet.

This thesis presents work done to extend and improve the operation of homodyne dechirp-on-receive linearly frequency modulated radars. First, an investigation of the effect of common phase errors on the point response function of the radar is described. The dependence on the window function of the degradation due to phase errors is investigated, and a simple, precise, and general approach for calculating the degraded Point Spread Function (PSF) is described and demonstrated. This method is shown to be particularly useful when investigating the effect of chirp nonlinearity on the PSF. Next, a method for focussing range profiles that are degraded by chirp nonlinearity is described. This method is based on two established methods, the Phase Gradient Algorithm (PGA) and a time-domain re-sampling technique. The technique is entirely hardware independent, allowing any homodyne dechirp-on-receive linearly frequency modulated radar to be focussed. Where suitable archive signal data exists, focussed imagery can even be produced from radars that no longer exist. The complete algorithm and details of the implementation are described, and the technique is demonstrated on three representative radar cases: extreme chirp nonlinearity, typical chirp nonlinearity, and a retrospective case. In all of the cases, it was shown that the PSF was dramatically improved. A technique based on down conversion by aliasing for reducing the required sampling rate is described, and a simple technique for calculating suitable sampling rates is presented. This method is demonstrated for a typical application in which sampling rate reduction might be required, namely Moving Target Indication (MTI). The MTI application is described and quantified, including a simple technique for choosing suitable radar operation parameters. The MTI technique with subsampling was demonstrated in software simulations and in a simple radar experiment. A Synthetic Aperture Radar (SAR) test bench for researching component performance and scatterer properties in the context of SAR was developed. An appropriate image formation processing algorithm was found and modified to better suit the task of a short data collection baseline and drifting centre frequencies, both of which are present in the test bench situation. Software was written to collect data, to control the hardware, and to process the signals into SAR images. A data simulator was written to test the image formation algorithm implementation; it also served as a useful tool for investigating the effect of signal errors on the quality of the resultant SAR imagery. A suitable oscillator was chosen for the task, based on phase noise and centre frequency stability considerations, both of which are quantified and discussed. Preliminary SAR imagery was produced, indicating that the system operates correctly and in agreement with comparable systems.

In this thesis, principles of a pulse modulated frequency modulated continuous wave radar is analyzed and adding time delay to transmitted signal in the laboratory environment performed. The transmitted signal from the radar has a time delay for traveling the distance between radar and target. The distance from radar to target is more than one kilometers thus test of the functionality of the radar in the laboratory environment is unavailable. The delay is simulated regarding to elapsed time for the transmitted signal to be received. This delay achieved by using surface acoustic wave (SAW) delay line in the laboratory environment. The analyses of the components of the radar and the delay line test board are conducted.

The goal of the following thesis is to transfer radar basic theory in a practical work using Texas Instrument’s mmWave radar series. The range of practical applications for FMCW radars has increased, for example in automotive sector. Understanding the basics of radar mathematics in a simplified way, as well as the transfer from theory to practical work is important for any engineer working on radar projects. Even if the theory is known, the way from a theory to a running system can be hard, facing several problems, because the reality is limited. In two experiments, data from the radar is collected while cars are crossing the observation area of the radar.The data is then used to count the number of vehicles passing the observation area and to estimate the movement of the objects in the field of view.

The topic of multiple input multiple output (MIMO) radar recently gained considerable interest because it can transmit partially correlated or fully independent waveforms. The inherited waveform diversity helps MIMO radars identify more targets and adds flexibility to the beampattern design. The realized advantages come at the expense of enhanced processing requirements and increased system complexity. In this regards, a closed-form method is derived to generate practical finite-alphabet waveforms with specific correlation properties to match the desired beampattern. Next, the performance of adaptive estimation techniques is examined. Indeed, target localization or reflection coefficient estimation usually involves optimizing a given cost-function over a grid of points. The estimation performance is directly affected by the grid resolution. In this work, the cost function of Capon and amplitude and phase estimation (APES) adaptive beamformers are reformulated. The new cost functions can be evaluated using the two-dimensional fast-Fourier-transform (2D-FFT) which reduces the estimation runtime. Generalized expressions of the Cram´er-Rao lower bound are computed to assess the performance of our estimators. Afterward, a novel estimation algorithm based on the monopulse technique is proposed. In comparison with adaptive methods, monopulse requires less number of received pulses. Hence, it is widely used for fast target localization and tracking purposes. This work suggests an approach that localizes two point targets present in the hemisphere using one set of four antennas. To separate targets sharing the same elevation or azimuth angles, a second set of antennas is required. Two solutions are suggested to combine the outputs from the antenna sets and improve the overall detection performance. The last part of the dissertation focuses on the application and implementation side of radars rather than the theoretical aspects. It describes the realized hardware and software design of a compact portable 24 GHz frequency-modulated-continuous-wave (FMCW) radar. The prototype can assist the visually impaired during their outdoor journeys and prevents collisions with their surrounding environment. Moreover, the device performs diverse tasks such as range-direction mapping, velocity estimation, presence detection, and vital sign monitoring. The experimental result section demonstrates the device’s capabilities in different use-cases.

Unmanned aerial systems (UAS) are an influential technology which can enhance life in multiple ways. However, they must be able to sense and operate safely with manned aircraft. Radar is an attractive sensor for UAS because of its all-weather performance. It is challenging, though, to meet the size, weight, and power (SWaP) limitations of UAS and especially small-UAS while still maintaining the needed sensing capability. A working FMCW radar prototype has been created which meets the SWaP requirement of small-UAS. A simulation model for the radar was developed to test the processing algorithms of the radar and proved to be advantageous in that purpose. An automatic target detection algorithm was also successfully developed to allow the radar to identify targets of interest in a cluttered and dynamic environment. Fixed-wing airborne tests have been performed with the radar which show that the radar meets the SWaP requirements of small-UAS. They also show the prototype requires a higher sensitivity to detect other small-UAS. A successful redesign of the radar's receivers was done to make the radar more sensitive.

Location information is vital for any type of aircraft and even more crucial for Unmanned Aerial Systems (UAS). GPS is a readily available solution but signals can easily be jammed or lost. In this thesis, radar is explored as a backup system for self-localization when GPS signals are not available. The method proposed requires that an area be pre mapped by collecting radar data with known latitude and longitude coordinates. New radar data is then collected and compared to previously stored values. Channel matrices are stored at each point and are used as the basis for location comparisons. Various methods of matrix comparison are used and both simulation as well as experimental results are shown. The main results of this thesis show that position can be determined using channel matrices if the sensor is within a certain radius of previously stored locations. This radius is on the order of a wavelength or less. Using correlation matrix comparisons the radius of localization is broadened. A novel method using multiple channel and multiple frequency data proves to be successful and determines the position of an octorotor UAS with a mean position error of less than three meters. The design of a low-cost, compact, and light-weight FMCW radar for two applications is also presented. The first application is a novel radar based positioning system that utilizes multiple channel and multiple frequency information to determine position. The second application is a UAS sense and avoid system using a monopulse configuration. Without connectors or antennas, the radar weighs 45.7 grams, is 7.5 cm x 5 cm x 3 cm in size, and costs less than $100 when built in quantities of 100 or more (excludes antennas and connectors). It is tested using delay lines and corner reflectors and accurately determines the distance to close range targets.