Self-Supervised Learning for Enhancing Angular Resolution in Automotive MIMO Radars

A novel framework to enhance the angular resolution of automotive radars is proposed. An approach to enlarge the antenna aperture using artificial neural networks is developed using a self-supervised learning scheme. Data from a high angular resolution radar, i.e., a radar with a large antenna aperture, is used to train a deep neural network to extrapolate the antenna element's response. Afterward, the trained network is used to enhance the angular resolution of compact, low-cost radars. One million scenarios are simulated in a Monte-Carlo fashion, varying the number of targets, their Radar Cross Section (RCS), and location to evaluate the method's performance. Finally, the method is tested in real automotive data collected outdoors with a commercial radar system. A significant increase in the ability to resolve targets is demonstrated, which can translate to more accurate and faster responses from the planning and decision making system of the vehicle.Comment: Under revision at IEEE Transactions on Vehicular Technolog

Sparse Array Architectures for Wireless Communication and Radar Applications

This thesis focuses on sparse array architectures for the next generation of wireless communication, known as fifth-generation (5G), and automotive radar direction-of-arrival (DOA) estimation. For both applications, array spatial resolution plays a critical role to better distinguish multiple users/sources. Two novel base station antenna (BSA) configurations and a new sparse MIMO radar, which both outperform their conventional counterparts, are proposed.\ua0We first develop a multi-user (MU) multiple-input multiple-output (MIMO) simulation platform which incorporates both antenna and channel effects based on standard network theory. The combined transmitter-channel-receiver is modeled by cascading Z-matrices to interrelate the port voltages/currents to one another in the linear network model. The herein formulated channel matrix includes physical antenna and channel effects and thus enables us to compute the actual port powers. This is in contrast with the assumptions of isotropic radiators without mutual coupling effects which are commonly being used in the Wireless Community.\ua0Since it is observed in our model that the sum-rate of a MU-MIMO system can be adversely affected by antenna gain pattern variations, a novel BSA configuration is proposed by combining field-of-view (FOV) sectorization, array panelization and array sparsification. A multi-panel BSA, equipped with sparse arrays in each panel, is presented with the aim of reducing the implementation complexities and maintaining or even improving the sum-rate.\ua0We also propose a capacity-driven array synthesis in the presence of mutual coupling for a MU-MIMO system. We show that the appearance of\ua0grating lobes is degrading the system capacity and cannot be disregarded in a MU communication, where space division\ua0multiple access (SDMA) is applied. With the aid of sparsity and aperiodicity, the adverse effects of grating lobes and mutual coupling\ua0are suppressed and capacity is enhanced. This is performed by proposing a two-phase optimization. In Phase I, the problem\ua0is relaxed to a convex optimization by ignoring the mutual coupling and weakening the constraints. The solution of Phase I\ua0is used as the initial guess for the genetic algorithm (GA) in phase II, where the mutual coupling is taken into account. The\ua0proposed hybrid algorithm outperforms the conventional GA with random initialization.\ua0A novel sparse MIMO radar is presented for high-resolution single snapshot DOA estimation. Both transmit and receive arrays are divided into two uniform arrays with increased inter-element spacings to generate two uniform sparse virtual arrays. Since virtual arrays are uniform, conventional spatial smoothing can be applied for temporal correlation suppression among sources. Afterwards, the spatially smoothed virtual arrays satisfy the co-primality concept to avoid DOA ambiguities. Physical antenna effects are incorporated in the received signal model and their effects on the DOA estimation performance are investigated

Coherent, super resolved radar beamforming using self-supervised learning

High resolution automotive radar sensors are required in order to meet the high bar of autonomous vehicles needs and regulations. However, current radar systems are limited in their angular resolution causing a technological gap. An industry and academic trend to improve angular resolution by increasing the number of physical channels, also increases system complexity, requires sensitive calibration processes, lowers robustness to hardware malfunctions and drives higher costs. We offer an alternative approach, named Radar signal Reconstruction using Self Supervision (R2-S2), which significantly improves the angular resolution of a given radar array without increasing the number of physical channels. R2-S2 is a family of algorithms which use a Deep Neural Network (DNN) with complex range-Doppler radar data as input and trained in a self-supervised method using a loss function which operates in multiple data representation spaces. Improvement of 4x in angular resolution was demonstrated using a real-world dataset collected in urban and highway environments during clear and rainy weather conditions.Comment: 28 pages 10 figure

Estudo de formas de onda e conceção de algoritmos para operação conjunta de sistemas de comunicação e radar

The focus of this thesis is the processing of signals and design of algorithms that can be used to enable radar functions in communications systems. Orthogonal frequency division multiplexing (OFDM) is a popular multicarrier modulation waveform in communication systems. As a wideband signal, OFDM improves resolution and enables spectral efficiency in radar systems, while also improving detection performance thanks to its inherent frequency diversity. This thesis aims to use multicarrier waveforms for radar systems, to enable the simultaneous operation of radar and communication functions on the same device. The thesis is divided in two parts. The first part, studies the adaptation and application of other multicarrier waveforms to radar functions. At the present time many studies have been carried out to jointly use the OFDM signal for communication and radar functions, but other waveforms have shown to be possible candidates for communication applications. Therefore, studies on the evaluation of the application of these same signals to radar functions are necessary. In this thesis, to demonstrate that other multicarrier waveforms can overcome the OFDM waveform in radar/communication (RadCom) systems, we propose the adaptation of the filter bank multicarrier (FBMC), generalized frequency division multiplexing (GFDM) and universal filtering multicarrier (UFMC) waveforms for radar functions. These alternative waveforms were compared performance-wise regarding achievable target parameter estimation performance, amount of residual background noise in the radar image, impact of intersystem interference and flexibility of parameterization. In the second part of the thesis, signal processing techniques are explored to solve some of the limitations of the use of multicarrier waveforms for RadCom systems. Radar systems based on OFDM are promising candidates for future intelligent transport networks. Exploring the dual functionality enabled by OFDM, we presents cooperative methods for high-resolution delay-Doppler and direction-of-arrival estimation. High-resolution parameter estimation is an important requirement for automotive radar systems, especially in multi-target scenarios that require reliable target separation performance. By exploring the cooperation between vehicles, the studies presented in this thesis also enable the distributed tracking of targets. The result is a highly accurate multi-target tracking across the entire cooperative vehicle network, leading to improvements in transport reliability and safety.O foco desta tese é o processamento de sinais e desenvolvimento de algoritmos que podem ser utilizados para a habilitar a função de radar nos sistemas de comunicação. OFDM (Orthogonal Frequency Division Multiplexing) é uma forma de onda com modulação multi-portadora, popular em sistemas de comunicação. Para sistemas de radar, O OFDM melhora a resolução e fornece eficiência espectral, além disso sua diversidade de frequências melhora o desempenho na detecção do radar. Essa tese tem como objetivo utilizar formas de onda multi-portadoras para sistemas de radar, possibilitando a operação simultânea de funções de radar e de comunicação num mesmo dispositivo. A tese esta dividida em duas partes. Na primeira parte da tese são realizados estudos da adaptabilidade de outras formas de onda multi-portadora para funções de radar. Nos dias atuais, muitos estudos sobre o uso do sinal OFDM para funções de comunicação e radar vêm sendo realizados, no entanto, outras formas de onda mostram-se possíveis candidatas a aplicações em sistemas de comunicação, e assim, avaliações para funções de sistema de radar se tornam necessárias. Nesta tese, com a intenção de demonstrar que formas de onda multi-portadoras alternativas podem superar o OFDM nos sistemas de Radar/comunicação (RadCom), propomos a adaptação das seguintes formas de onda: FBMC (Filter Bank Multicarrier); GFDM (Generalized Frequency Division Multiplexing); e UFMC (Universal Filtering Multicarrier) para funções de radar. Também produzimos uma análise de desempenho dessas formas de onda sobre o aspecto da estimativa de parâmetros-alvo, ruído de fundo, interferência entre sistemas e parametrização do sistema. Na segunda parte da tese serão explorados técnicas de processamento de sinal de forma a solucionar algumas das limitações do uso de formas de ondas multi-portadora para sistemas RadCom. Os sistemas de radar baseados no OFDM são candidatos promissores para futuras redes de transporte inteligentes, porque combinam funções de estimativa de alvo com funções de rede de comunicação em um único sistema. Explorando a funcionalidade dupla habilitada pelo OFDM, nesta tese, apresentamos métodos cooperativos de alta resolução para estimar o posição, velocidade e direção dos alvos. A estimativa de parâmetros de alta resolução é um requisito importante para sistemas de radar automotivo, especialmente em cenários de múltiplos alvos que exigem melhor desempenho de separação de alvos. Ao explorar a cooperação entre veículos, os estudos apresentados nesta tese também permitem o rastreamento distribuído de alvos. O resultado é um rastreamento multi-alvo altamente preciso em toda a rede de veículos cooperativos, levando a melhorias na confiabilidade e segurança do transporte.Programa Doutoral em Telecomunicaçõe

Signal processing architectures for automotive high-resolution MIMO radar systems

To date, the digital signal processing for an automotive radar sensor has been handled in an efficient way by general purpose signal processors and microcontrollers. However, increasing resolution requirements for automated driving on the one hand, as well as rapidly growing numbers of manufactured sensors on the other hand, can provoke a paradigm change in the near future. The design and development of highly specialized hardware accelerators could become a viable option - at least for the most demanding processing steps with data rates of several gigabits per second. In this work, application-specific signal processing architectures for future high-resolution multiple-input and multiple-output (MIMO) radar sensors are designed, implemented, investigated and optimized. A focus is set on real-time performance such that even sophisticated algorithms can be computed sufficiently fast. The full processing chain from the received baseband signals to a list of detections is considered, comprising three major steps: Spectrum analysis, target detection and direction of arrival estimation. The developed architectures are further implemented on a field-programmable gate array (FPGA) and important measurements like resource consumption, power dissipation or data throughput are evaluated and compared with other examples from literature. A substantial dataset, based on more than 3600 different parametrizations and variants, has been established with the help of a model-based design space exploration and is provided as part of this work. Finally, an experimental radar sensor has been built and is used under real-world conditions to verify the effectiveness of the proposed signal processing architectures.Bisher wurde die digitale Signalverarbeitung für automobile Radarsensoren auf eine effiziente Art und Weise von universell verwendbaren Mikroprozessoren bewältigt. Jedoch können steigende Anforderungen an das Auflösungsvermögen für hochautomatisiertes Fahren einerseits, sowie schnell wachsende Stückzahlen produzierter Sensoren andererseits, einen Paradigmenwechsel in naher Zukunft bewirken. Die Entwicklung von hochgradig spezialisierten Hardwarebeschleunigern könnte sich als eine praktikable Alternative etablieren - zumindest für die anspruchsvollsten Rechenschritte mit Datenraten von mehreren Gigabits pro Sekunde. In dieser Arbeit werden anwendungsspezifische Signalverarbeitungsarchitekturen für zukünftige, hochauflösende, MIMO Radarsensoren entworfen, realisiert, untersucht und optimiert. Der Fokus liegt dabei stets auf der Echtzeitfähigkeit, sodass selbst anspruchsvolle Algorithmen in einer ausreichend kurzen Zeit berechnet werden können. Die komplette Signalverarbeitungskette, beginnend von den empfangenen Signalen im Basisband bis hin zu einer Liste von Detektion, wird in dieser Arbeit behandelt. Die Kette gliedert sich im Wesentlichen in drei größere Teilschritte: Spektralanalyse, Zieldetektion und Winkelschätzung. Des Weiteren werden die entwickelten Architekturen auf einem FPGA implementiert und wichtige Kennzahlen wie Ressourcenverbrauch, Stromverbrauch oder Datendurchsatz ausgewertet und mit anderen Beispielen aus der Literatur verglichen. Ein umfangreicher Datensatz, welcher mehr als 3600 verschiedene Parametrisierungen und Varianten beinhaltet, wurde mit Hilfe einer modellbasierten Entwurfsraumexploration erstellt und ist in dieser Arbeit enthalten. Schließlich wurde ein experimenteller Radarsensor aufgebaut und dazu benutzt, die entworfenen Signalverarbeitungsarchitekturen unter realen Umgebungsbedingungen zu verifizieren

Codificação de bloco espaço-tempo na habilitação de sistemas MIMO-OFDM

The available bandwidth in the radio frequency spectrum is decreasing due to the growing number of applications and users. Therefore, in order to ensure a sustainable evolution in this area it is crucial to develop strategies to optimize the spectrum usage. Joining RADAR and communication functionalities in a single terminal represents exactly this same strategy. As such, the two functionalities, which usually compete for the same radio resources, can coexist through a cooperative relation in which they can thrive and cease to introduce interferences in between them. In this dissertation, the integration of both systems is achieved through the use of OFDM as the common waveform. Through the space time/frequency block codes, namely the Tarokh coding it is possible to introduce spatial diversity and orthogonality to the system, therefore increasing the system’s robustness and allowing to use the virtual antenna concept, which enables improved RADAR resolution and detection. In order to evaluate the system’s performance, a simulation platform was developed. In these simulations we start by firstly considering RADAR detection for single and multiple antenna systems and then integrate the radar and communication functionalities. We have verified the good performance levels of the proposed system, which thanks to its low complexity can be an interesting RadCom approach for future wireless systems.A largura de banda disponível no espectro de radio frequência enfrenta uma diminuição face ao crescente número de aplicações e utilizadores. Assim, por forma a assegurar uma evolução sustentável neste campo é fulcral desenvolver estratégias que otimizem o uso do espectro. A junção das funcionalidades RADAR e comunicação num só terminal faz parte dessa estratégia. Desta forma, duas funcionalidades usualmente concorrentes pelos mesmos recursos radio, podem coexistir em cooperação, sem interferência entre ambos. Nesta dissertação a integração dos dois sistemas é conseguida através do uso do OFDM como forma de onda comum. Através de códigos desenhados no espaço-tempo/frequência, nomeadamente a codificação de Tarokh, foi possível introduzir diversidade espacial e ortogonalidade no sistema, aumentando assim a sua robustez e permitindo o uso do conceito de antenas virtuais, que por sua vez possibilitam uma melhoria na resolução e deteção do RADAR. De forma a avaliar o desempenho do sistema desenvolveu-se uma plataforma de simulação. Nesta plataforma começou-se por considerar a deteção RADAR para sistemas com uma e múltiplas antenas, onde posteriormente se integraram as funcionalidades de comunicação. Os resultados obtidos mostraram um excelente desempenho do sistema, que devido à sua baixa complexidade, pode ser um sistema RadCom interessante para os futuros sistemas sem fios.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Architectures and Algorithms for the Signal Processing of Advanced MIMO Radar Systems

This thesis focuses on the research, development and implementation of novel concepts, architectures, demonstrator systems and algorithms for the signal processing of advanced Multiple Input Multiple Output (MIMO) radar systems. The key concept is to address compact system, which have high resolutions and are able to perform a fast radar signal processing, three-dimensional (3D), and four-dimensional (4D) beamforming for radar image generation and target estimation. The idea is to obtain a complete sensing of range, Azimuth and elevation (additionally Doppler as the fourth dimension) from the targets in the radar captures. The radar technology investigated, aims at addressing sev- eral civil and military applications, such as surveillance and detection of targets, both air and ground based, and situational awareness, both in cars and in flying platforms, from helicopters, to Unmanned Aerial Vehicles (UAV) and air-taxis. Several major topics have been targeted. The development of complete systems and innovative FPGA, ARM and software based digital architectures for 3D imaging MIMO radars, which operate in both Time Division Multiplexing (TDM) and Frequency Divi- sion Multiplexing (FDM) modes, with Frequency Modulated Continuous Wave (FMCW) and Orthogonal Frequency Division Multiplexing (OFDM) signals, respectively. The de- velopment of real-time radar signal processing, beamforming and Direction-Of-Arrival (DOA) algorithms for target detection, with particular focus on FFT based, hardware implementable techniques. The study and implementation of advanced system concepts, parametrisation and simulation of next generation real-time digital radars (e.g. OFDM based). The design and development of novel constant envelope orthogonal waveforms for real-time 3D OFDM MIMO radar systems. The MIMO architectures presented in this thesis are a collection of system concepts, de- sign and simulations, as well as complete radar demonstrators systems, with indoor and outdoor measurements. Several of the results shown, come in the form of radar images which have been captured in field-test, in different scenarios, which aid in showing the proper functionality of the systems. The research activities for this thesis, have been carried out on the premises of Air- bus, based in Munich (Germany), as part of a Ph.D. candidate joint program between Airbus and the Polytechnic Department of Engineering and Architecture (Dipartimento Politecnico di Ingegneria e Architettura), of the University of Udine, based in Udine (Italy).Questa tesi si concentra sulla ricerca, lo sviluppo e l\u2019implementazione di nuovi concetti, architetture, sistemi dimostrativi e algoritmi per l\u2019elaborazione dei segnali in sistemi radar avanzati, basati su tecnologia Multiple Input Multiple Output (MIMO). Il con- cetto chiave `e quello di ottenere sistemi compatti, dalle elevate risoluzioni e in grado di eseguire un\u2019elaborazione del segnale radar veloce, un beam-forming tri-dimensionale (3D) e quadri-dimensionale (4D) per la generazione di immagini radar e la stima delle informazioni dei bersagli, detti target. L\u2019idea `e di ottenere una stima completa, che includa la distanza, l\u2019Azimuth e l\u2019elevazione (addizionalmente Doppler come quarta di- mensione) dai target nelle acquisizioni radar. La tecnologia radar indagata ha lo scopo di affrontare diverse applicazioni civili e militari, come la sorveglianza e la rilevazione di targets, sia a livello aereo che a terra, e la consapevolezza situazionale, sia nelle auto che nelle piattaforme di volo, dagli elicotteri, ai Unmanned Aerial Vehicels (UAV) e taxi volanti (air-taxis). Le tematiche affrontante sono molte. Lo sviluppo di sistemi completi e di architetture digitali innovative, basate su tecnologia FPGA, ARM e software, per radar 3D MIMO, che operano in modalit`a Multiplexing Time Division Multiplexing (TDM) e Multiplexing Frequency Diversion (FDM), con segnali di tipo FMCW (Frequency Modulated Contin- uous Wave) e Orthogonal Frequency Division Multiplexing (OFDM), rispettivamente. Lo sviluppo di tecniche di elaborazione del segnale radar in tempo reale, algoritmi di beam-forming e di stima della direzione di arrivo, Direction-Of-Arrival (DOA), dei seg- nali radar, per il rilevamento dei target, con particolare attenzione a processi basati su trasformate di Fourier (FFT). Lo studio e l\u2019implementazione di concetti di sistema avan- zati, parametrizzazione e simulazione di radar digitali di prossima generazione, capaci di operare in tempo reale (ad esempio basati su architetture OFDM). Progettazione e sviluppo di nuove forme d\u2019onda ortogonali ad inviluppo costante per sistemi radar 3D di tipo OFDM MIMO, operanti in tempo reale. Le attivit`a di ricerca di questa tesi sono state svolte presso la compagnia Airbus, con sede a Monaco di Baviera (Germania), nell\u2019ambito di un programma di dottorato, svoltosi in maniera congiunta tra Airbus ed il Dipartimento Politecnico di Ingegneria e Architettura dell\u2019Universit`a di Udine, con sede a Udine