Radar-based Application of Pedestrian and Cyclist Micro-Doppler Signatures for Automotive Safety Systems

Die sensorbasierte Erfassung des Nahfeldes im Kontext des hochautomatisierten Fahrens erfährt einen spürbaren Trend bei der Integration von Radarsensorik. Fortschritte in der Mikroelektronik erlauben den Einsatz von hochauflösenden Radarsensoren, die durch effiziente Verfahren sowohl im Winkel als auch in der Entfernung und im Doppler die Messgenauigkeit kontinuierlich ansteigen lassen. Dadurch ergeben sich neuartige Möglichkeiten bei der Bestimmung der geometrischen und kinematischen Beschaffenheit ausgedehnter Ziele im Fahrzeugumfeld, die zur gezielten Entwicklung von automotiven Sicherheitssystemen herangezogen werden können. Im Rahmen dieser Arbeit werden ungeschützte Verkehrsteilnehmer wie Fußgänger und Radfahrer mittels eines hochauflösenden Automotive-Radars analysiert. Dabei steht die Erscheinung des Mikro-Doppler-Effekts, hervorgerufen durch das hohe Maß an kinematischen Freiheitsgraden der Objekte, im Vordergrund der Betrachtung. Die durch den Mikro-Doppler-Effekt entstehenden charakteristischen Radar-Signaturen erlauben eine detailliertere Perzeption der Objekte und können in direkten Zusammenhang zu ihren aktuellen Bewegungszuständen gesetzt werden. Es werden neuartige Methoden vorgestellt, die die geometrischen und kinematischen Ausdehnungen der Objekte berücksichtigen und echtzeitfähige Ansätze zur Klassifikation und Verhaltensindikation realisieren. Wird ein ausgedehntes Ziel (z.B. Radfahrer) von einem Radarsensor detektiert, können aus dessen Mikro-Doppler-Signatur wesentliche Eigenschaften bezüglich seines Bewegungszustandes innerhalb eines Messzyklus erfasst werden. Die Geschwindigkeitsverteilungen der sich drehenden Räder erlauben eine adaptive Eingrenzung der Tretbewegung, deren Verhalten essentielle Merkmale im Hinblick auf eine vorausschauende Unfallprädiktion aufweist. Ferner unterliegen ausgedehnte Radarziele einer Orientierungsabhängigkeit, die deren geometrischen und kinematischen Profile direkt beeinflusst. Dies kann sich sowohl negativ auf die Klassifikations-Performance als auch auf die Verwertbarkeit von Parametern auswirken, die eine Absichtsbekundung des Radarziels konstituieren. Am Beispiel des Radfahrers wird hierzu ein Verfahren vorgestellt, das die orientierungsabhängigen Parameter in Entfernung und Doppler normalisiert und die gemessenen Mehrdeutigkeiten kompensiert. Ferner wird in dieser Arbeit eine Methodik vorgestellt, die auf Grundlage des Mikro- Doppler-Profils eines Fußgängers dessen Beinbewegungen über die Zeit schätzt (Tracking) und wertvolle Objektinformationen hinsichtlich seines Bewegungsverhaltens offenbart. Dazu wird ein Bewegungsmodell entwickelt, das die nichtlineare Fortbewegung des Beins approximiert und dessen hohes Maß an biomechanischer Variabilität abbildet. Durch die Einbeziehung einer wahrscheinlichkeitsbasierten Datenassoziation werden die Radar-Detektionen ihren jeweils hervorrufenden Quellen (linkes und rechtes Bein) zugeordnet und eine Trennung der Gliedmaßen realisiert. Im Gegensatz zu bisherigen Tracking-Verfahren weist die vorgestellte Methodik eine Steigerung in der Genauigkeit der Objektinformationen auf und stellt damit einen entscheidenden Vorteil für zukünftige Fahrerassistenzsysteme dar, um deutlich schneller auf kritische Verkehrssituationen reagieren zu können.:1 Introduction 1 1.1 Automotive environmental perception 2 1.2 Contributions of this work 4 1.3 Thesis overview 6 2 Automotive radar 9 2.1 Physical fundamentals 9 2.1.1 Radar cross section 9 2.1.2 Radar equation 10 2.1.3 Micro-Doppler effect 11 2.2 Radar measurement model 15 2.2.1 FMCW radar 15 2.2.2 Chirp sequence modulation 17 2.2.3 Direction-of-arrival estimation 22 2.3 Signal processing 25 2.3.1 Target properties 26 2.3.2 Target extraction 28 Power detection 28 Clustering 30 2.3.3 Real radar data example 31 2.4 Conclusion 33 3 Micro-Doppler applications of a cyclist 35 3.1 Physical fundamentals 35 3.1.1 Micro-Doppler signatures of a cyclist 35 3.1.2 Orientation dependence 36 3.2 Cyclist feature extraction 38 3.2.1 Adaptive pedaling extraction 38 Ellipticity constraints 38 Ellipse fitting algorithm 39 3.2.2 Experimental results 42 3.3 Normalization of the orientation dependence 44 3.3.1 Geometric correction 44 3.3.2 Kinematic correction 45 3.3.3 Experimental results 45 3.4 Conclusion 47 3.5 Discussion and outlook 47 4 Micro-Doppler applications of a pedestrian 49 4.1 Pedestrian detection 49 4.1.1 Human kinematics 49 4.1.2 Micro-Doppler signatures of a pedestrian 51 4.1.3 Experimental results 52 Radially moving pedestrian 52 Crossing pedestrian 54 4.2 Pedestrian feature extraction 57 4.2.1 Frequency-based limb separation 58 4.2.2 Extraction of body parts 60 4.2.3 Experimental results 62 4.3 Pedestrian tracking 64 4.3.1 Probabilistic state estimation 65 4.3.2 Gaussian filters 67 4.3.3 The Kalman filter 67 4.3.4 The extended Kalman filter 69 4.3.5 Multiple-object tracking 71 4.3.6 Data association 74 4.3.7 Joint probabilistic data association 80 4.4 Kinematic-based pedestrian tracking 84 4.4.1 Kinematic modeling 84 4.4.2 Tracking motion model 87 4.4.3 4-D radar point cloud 91 4.4.4 Tracking implementation 92 4.4.5 Experimental results 96 Longitudinal trajectory 96 Crossing trajectory with sudden turn 98 4.5 Conclusion 102 4.6 Discussion and outlook 103 5 Summary and outlook 105 5.1 Developed algorithms 105 5.1.1 Adaptive pedaling extraction 105 5.1.2 Normalization of the orientation dependence 105 5.1.3 Model-based pedestrian tracking 106 5.2 Outlook 106 Bibliography 109 List of Acronyms 119 List of Figures 124 List of Tables 125 Appendix 127 A Derivation of the rotation matrix 2.26 127 B Derivation of the mixed radar signal 2.52 129 C Calculation of the marginal association probabilities 4.51 131 Curriculum Vitae 135Sensor-based detection of the near field in the context of highly automated driving is experiencing a noticeable trend in the integration of radar sensor technology. Advances in microelectronics allow the use of high-resolution radar sensors that continuously increase measurement accuracy through efficient processes in angle as well as distance and Doppler. This opens up novel possibilities in determining the geometric and kinematic nature of extended targets in the vehicle environment, which can be used for the specific development of automotive safety systems. In this work, vulnerable road users such as pedestrians and cyclists are analyzed using a high-resolution automotive radar. The focus is on the appearance of the micro-Doppler effect, caused by the objects’ high kinematic degree of freedom. The characteristic radar signatures produced by the micro-Doppler effect allow a clearer perception of the objects and can be directly related to their current state of motion. Novel methods are presented that consider the geometric and kinematic extents of the objects and realize real-time approaches to classification and behavioral indication. When a radar sensor detects an extended target (e.g., bicyclist), its motion state’s fundamental properties can be captured from its micro-Doppler signature within a measurement cycle. The spinning wheels’ velocity distributions allow an adaptive containment of the pedaling motion, whose behavior exhibits essential characteristics concerning predictive accident prediction. Furthermore, extended radar targets are subject to orientation dependence, directly affecting their geometric and kinematic profiles. This can negatively affect both the classification performance and the usability of parameters constituting the radar target’s intention statement. For this purpose, using the cyclist as an example, a method is presented that normalizes the orientation-dependent parameters in range and Doppler and compensates for the measured ambiguities. Furthermore, this paper presents a methodology that estimates a pedestrian’s leg motion over time (tracking) based on the pedestrian’s micro-Doppler profile and reveals valuable object information regarding his motion behavior. To this end, a motion model is developed that approximates the leg’s nonlinear locomotion and represents its high degree of biomechanical variability. By incorporating likelihood-based data association, radar detections are assigned to their respective evoking sources (left and right leg), and limb separation is realized. In contrast to previous tracking methods, the presented methodology shows an increase in the object information’s accuracy. It thus represents a decisive advantage for future driver assistance systems in order to be able to react significantly faster to critical traffic situations.:1 Introduction 1 1.1 Automotive environmental perception 2 1.2 Contributions of this work 4 1.3 Thesis overview 6 2 Automotive radar 9 2.1 Physical fundamentals 9 2.1.1 Radar cross section 9 2.1.2 Radar equation 10 2.1.3 Micro-Doppler effect 11 2.2 Radar measurement model 15 2.2.1 FMCW radar 15 2.2.2 Chirp sequence modulation 17 2.2.3 Direction-of-arrival estimation 22 2.3 Signal processing 25 2.3.1 Target properties 26 2.3.2 Target extraction 28 Power detection 28 Clustering 30 2.3.3 Real radar data example 31 2.4 Conclusion 33 3 Micro-Doppler applications of a cyclist 35 3.1 Physical fundamentals 35 3.1.1 Micro-Doppler signatures of a cyclist 35 3.1.2 Orientation dependence 36 3.2 Cyclist feature extraction 38 3.2.1 Adaptive pedaling extraction 38 Ellipticity constraints 38 Ellipse fitting algorithm 39 3.2.2 Experimental results 42 3.3 Normalization of the orientation dependence 44 3.3.1 Geometric correction 44 3.3.2 Kinematic correction 45 3.3.3 Experimental results 45 3.4 Conclusion 47 3.5 Discussion and outlook 47 4 Micro-Doppler applications of a pedestrian 49 4.1 Pedestrian detection 49 4.1.1 Human kinematics 49 4.1.2 Micro-Doppler signatures of a pedestrian 51 4.1.3 Experimental results 52 Radially moving pedestrian 52 Crossing pedestrian 54 4.2 Pedestrian feature extraction 57 4.2.1 Frequency-based limb separation 58 4.2.2 Extraction of body parts 60 4.2.3 Experimental results 62 4.3 Pedestrian tracking 64 4.3.1 Probabilistic state estimation 65 4.3.2 Gaussian filters 67 4.3.3 The Kalman filter 67 4.3.4 The extended Kalman filter 69 4.3.5 Multiple-object tracking 71 4.3.6 Data association 74 4.3.7 Joint probabilistic data association 80 4.4 Kinematic-based pedestrian tracking 84 4.4.1 Kinematic modeling 84 4.4.2 Tracking motion model 87 4.4.3 4-D radar point cloud 91 4.4.4 Tracking implementation 92 4.4.5 Experimental results 96 Longitudinal trajectory 96 Crossing trajectory with sudden turn 98 4.5 Conclusion 102 4.6 Discussion and outlook 103 5 Summary and outlook 105 5.1 Developed algorithms 105 5.1.1 Adaptive pedaling extraction 105 5.1.2 Normalization of the orientation dependence 105 5.1.3 Model-based pedestrian tracking 106 5.2 Outlook 106 Bibliography 109 List of Acronyms 119 List of Figures 124 List of Tables 125 Appendix 127 A Derivation of the rotation matrix 2.26 127 B Derivation of the mixed radar signal 2.52 129 C Calculation of the marginal association probabilities 4.51 131 Curriculum Vitae 13

A REAL TIME PHASE SPACE BEAM SIZE AND DIVERGENCE MONITOR FOR SYNCHROTRON RADIATION

My prior work has shown that an electron beam position and angle monitoring system was able to measure the electron source position and angle at a single location in a beamline at a synchrotron source. This system, a phase space ̶ Beam Position Monitor (ps-BPM), relies on a monochromator to prepare a photon beam whose energy is at that of K-edge of an absorber filter. The natural divergence of the photon beam from the source gives an energy range that will encompass the K-edge of the filter. A measurement of the center of the monochromatic beam and the K-edge location through the absorber filter gives the position and angle of the electron source with sensitivity comparable to any beam position measurement system. Further, this thesis shows that this system is capable of measuring the source size and divergence at the same time by measuring the photon beam spatial distribution and the K-edge filtered beam distribution also with a sensitivity comparable to other existing methods for the source size; no other single measurement method is capable of divergence measurements. This was validated by measurements and simulations as the beam size in the storage ring was changed. The position measurements can be done in near real time and the size measurements can be done near 1 Hz. The system was extensively modeled for its application at the CLS as well as possible implementations at other higher brightness sources such as the Advanced Photon Source Upgrade (APS-U). The modeled performance of the ps-BPM system was compared against other methods for measuring the electron source properties for high brightness sources. These methods included pinhole imaging and double-slit interferometry. This system is being considered as a candidate system for the APS-U

Automatic Spatial Calibration of Ultra-Low-Field MRI for High-Accuracy Hybrid MEG--MRI

With a hybrid MEG--MRI device that uses the same sensors for both modalities, the co-registration of MRI and MEG data can be replaced by an automatic calibration step. Based on the highly accurate signal model of ultra-low-field (ULF) MRI, we introduce a calibration method that eliminates the error sources of traditional co-registration. The signal model includes complex sensitivity profiles of the superconducting pickup coils. In ULF MRI, the profiles are independent of the sample and therefore well-defined. In the most basic form, the spatial information of the profiles, captured in parallel ULF-MR acquisitions, is used to find the exact coordinate transformation required. We assessed our calibration method by simulations assuming a helmet-shaped pickup-coil-array geometry. Using a carefully constructed objective function and sufficient approximations, even with low-SNR images, sub-voxel and sub-millimeter calibration accuracy was achieved. After the calibration, distortion-free MRI and high spatial accuracy for MEG source localization can be achieved. For an accurate sensor-array geometry, the co-registration and associated errors are eliminated, and the positional error can be reduced to a negligible level.Comment: 11 pages, 8 figures. This work is part of the BREAKBEN project and has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 68686

Development of a silicon photomultiplier based innovative and low cost positron emission tomography scanner.

The Silicon Photomultiplier (SiPM) is a state-of-the-art semiconductor photodetector consisting of a high density matrix (up to 104) of independent pixels of micro-metric dimension (from 10 \u3bcm to 100 \u3bcm) which form a macroscopic unit of 1 to 6 mm2 area. Each pixel is a single-photon avalanche diode operated with a bias voltage of a few volts above the breakdown voltage. When a charge carrier is generated in a pixel by an incoming photon or a thermal effect, a Geiger discharge confined to that pixel is initiated and an intrinsic gain of about 106 is obtained. The output signal of a pixel is the same regardless of the number of interacting photons and provide only a binary information. Since the pixels are arranged on a common Silicon substrate and are connected in parallel to the same readout line, the SiPM combined output response corresponds to the sum of all fired pixel currents. As a result, the SiPM as a whole is an analogue detector, which can measure the incoming light intensity. Nowadays a great number of companies are investing increasing efforts in SiPM detector performances and high quality mass production. SiPMs are in rapid evolution and benefit from the tremendous development of the Silicon technology in terms of cost production, design flexibility and performances. They have reached a high single photon detection sensitivity and photon detection efficiency, an excellent time resolution, an extended dynamic range. They require a low bias voltage and have a low power consumption, they are very compact, robust, flexible and cheap. Considering also their intrinsic insensitivity to magnetic field they result to have an extremely high potential in fundamental and applied science (particle and nuclear physics, astrophysics, biology, environmental science and nuclear medicine) and industry. The SiPM performances are influenced by some effects, as saturation, afterpulsing and crosstalk, which lead to an inherent non-proportional response with respect to the number of incident photons. Consequently, it is not trivial to relate the measured electronic signal to the corresponding light intensity. Since for most applications it is desirable to qualify the SiPM response (i.e in order to properly design a detector for a given application, perform corrections on measurements or on energy spectra, calibrate a SiPM for low light measurements, predict detector performance) the implementation of characterization procedures plays a key role. The SiPM field of application that has been considered in this thesis is the Positron Emission Tomography (PET). PET represents the most advanced in-vivo nuclear imaging modality: it provides functional information of the physiological and molecular processes of organs and tissues. Thanks to its diagnostic power, PET has a recognized superiority over all other imaging modalities in oncology, neurology and cardiology. SiPMs are usually successfully employed for the PET scanners because they allow the measurement of the Time Of Flight of the two coincidence photons to improve the signal to noise ratio of the reconstructed images. They also permit to perfectly combine the functional information with the anatomical one by inserting the PET scanner inside the Magnetic Resonance Imaging device. Recently, PET technology has also been applied to preclinical imaging to allow non invasive studies on small animals. The increasing demand for preclinical PET scanner is driven by the fact that small animals host a large number of human diseases. In-vivo imaging has the advantage to enable the measurement of the radiopharmaceutical distribution in the same animal for an extended period of time. As a result, PET represents a powerful research tool as it offers the possibility to study the abnormalities at the origin of a disease, understand its dynamics, evaluate the therapeutic response and develop new drugs and treatments. However, the cost and the complexity of the preclinical scanners are limiting factors for the spread of PET technology: 70-80% of small-animal PET is concentrated in academic or government research laboratories. The EasyPET concept proposed in this Thesis, protected under a patent filed by Aveiro University, aims to achieve a simple and affordable preclinical PET scanner. The innovative concept is based on a single pair of detector kept collinear during the whole data acquisition and a moving mechanism with two degrees of freedom to reproduce the functionalities of an entire PET ring. The main advantages are in terms of the reduction of the complexity and cost of the PET system. In addition the concept is bound to be robust against acollinear photoemission, scatter radiation and parallax error. The sensitivity is expected to represent a fragility due to the reduced geometrical acceptance. This drawback can be partially recovered by the possibility to accept Compton scattering events without introducing image degradation effects, thanks to the sensor alignment. A 2D imaging demonstrator has been realized in order to assess the EasyPET concept and its performance has been analyzed in this Thesis to verify the net balance between competing advantages and drawbacks. The demonstrator had a leading role in the outreach activity to promote the EasyPET concept and a significant outcome is represented by the new partners that recently joined the collaboration. The EasyPET has been licensed to Caen S.p.a. and, thanks to the participation of Nuclear Instruments to the electronic board re-designed, a new prototype has been realized with additional improvements concerning the mechanics and the control software. In this Thesis the prototype functionalities and performances are reported as a result of a commissioning procedure. The EasyPET will be commercialized by Caen S.p.a. as a product for the educational market and it will be addressed to high level didactic laboratories to show the operating principles and technology behind the PET imaging. The topics mentioned above will be examined in depth in the following Chapters according to the subsequent order. In Chapter 1 the Silicon Photomultiplier will be described in detail, from their operating principle to their main application fields passing through the advantages and the drawback effects connected with this type of sensor. Chapter 2 is dedicated to a SiPM standard characterization method based on the staircase and resolving power measurement. A more refined analysis involves the Multi-Photon spectrum, obtained by integrating the SiPM response to a light pulse. It exploits the SiPM single photon sensitivity and its photon number resolving capability to measure some of its properties of general interest for a multitude of potential applications, disentangling the features related to the statistics of the incident light. Chapter 3 reports another SiPM characterization method which implements a post-processing of the digitized SiPM waveforms with the aim of extracting a full picture of the sensor characteristics from a unique data-set. The procedure is very robust, effective and semi-automatic and suitable for sensors of various dimensions and produced by different vendors. Chapter 4 introduces the Positron Emission Tomography imaging: its principle, applications, related issues and state of the art of PET scanner will be explained. Chapter 5 deals with the preclinical PET, reporting the benefits and the technological challenges involved, the performance of the commercially available small animal PET scanners, the main applications and the frontier research in this field. In Chapter 6 the EasyPET concept is introduced. In particular, the basic idea behind the operating principle, the design layout and the image reconstruction will be illustrated and then assessed through the description and the performance analysis of the EasyPET proof of concept and demonstrator. The effect of the use of different sensor to improve the light collection and the coincidence detection efficiency, together with the analysis of the importance of the sensor and the crystal alignment will be reported in Chapter 7. The design, the functionalities and the commissioning of the EasyPET prototype addressed to the educational market will be defined in Chapter 8. Finally, Chapter 9 contains a summary of the conclusions and an outlook of the future research studies