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.

No description available.

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.

<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.

Radar is a tool that has had a tremendous impact since its discovery. This thesis evaluates an algorithm called ESPRIT. ESPRIT is used in radar to estimate the angles to detected objects. The angle of an object is referred to as its DOA (Direction of arrival). ESPRIT separates from similar algorithms by having lower computational complexity, storage needs, and robustness. The thesis compares ESPRIT with another DOA-estimation algorithm used by a company called Raytelligence. The other algorithm can not be named due to confidentiality. The comparison is based on gathered data from an FMCW (Frequency Modulated Continuous Wave) radar. The comparison aims to validate ESPRIT functionality and its competitiveness versus the other algorithm. The comparison is based on two criteria: Accuracy and complexity. The thesis also presents potential optimizations which can improve ESPRIT’s ability to estimate DOA. These are an increase in the number of antennas used in the DOA estimation, and using the preprocessing scheme Spatial smoothing. The result for DOA estimation shows that ESPRITs' strength lies in detecting several objects at the same distance. The difference between ESPRIT and the other DOA estimation algorithm was insignificant when estimating one object. No conclusion could be drawn about the estimation accuracy for one object detection. The result also showed that ESPRIT's performance increases with the number of antennas and which preprocessing scheme is used. The result for complexity showed that ESPRIT has higher complexity than the other DOA estimation algorithm. For ESPRIT to use its strength, which is to detect several objects at the same distance, the implementation of complex pre-processing schemes is required. This will further increase the difference in complexity between the two compared algorithms. / Radar är ett verktyg som har haft en enorm påverkan sen dess upptäckt. Denna avhandling utvärderar en algoritm som heter ESPRIT. ESPRIT används i radar för att estimera vinklarna till detekterade objekt. Vinkeln för ett objekt benämns som dess DOA (Direction of arrival). ESPRIT skiljer sig från liknande algoritmer genom dess lägre beräkningskomplexitet, lagringsbehov samt robusthet. Avhandlingen jämför ESPRIT med en annan DOA estimerings algoritm som används av företaget Raytelligence idag. På grund av sekretess kan denna algoritm inte namnges. Jämförelsen bygger på praktiskt insamlad data från en FMCW (Frequency Modulated Continious Wave) radar. Jämförelsen siktar på att validera att ESPRIT fungerar, samt dess konkurrersförmåga mot den andra algoritmen. Jämförelsen utgick från två kriterier: Noggranhet och komplexitet. Avhandlingen presenterar även möjliga optimiseringar som kan förbättra ESPRITs förmåga att estimera DOA. Dessa är ökning av antalet antenner som används i DOA estimeringen, samt att använda förbehandlingsschemat Spatial smoothing. Resultatet för DOA estimering visar att ESPRITs' styrka ligger i att kunna detektera flera objekt på samma avstånd. Skillnaden mellan ESPRIT och den andra DOA estimerings algoritmen, vid estimering av ett objekt var inte tillräckligt signifikant för att dra några slutsatser. Resultatet visade också att ESPRITs' prestationsförmåga ökar med antalet antenner, samt vilket förbehandlingsschema som används. Resultatet för komplexitet visade att ESPRIT har högre komplexitet än den andra DOA estimerings algoritmen. För att ESPRIT ska kunna nyttja sin styrka, att kunna detektera flera objekt på samma distans, krävs implementation av komplexa förbehandlingsscheman. Detta ökar skillnaden på komplexitet mellan de två jämförda algoritmerna ytterliggare.