Requisitos de los candidatos: Buen expediente académico. Buen nivel de inglés. (No se requiere hablar alemán). Capacidad de trabajo en grupo.

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1 DLR - Deutsches Zentrum für Luft- und Raumfahrt. (Agencia Aeroespacial Alemana) Institute of Communications and Navigation Department of Communications Systems Weßling (Área Metropolitana de Múnich, Baviera) Se ofrece: Realizar el Trabajo Fin de Master (TFM) y, en algún caso, Trabajo Fin de Grado en diferentes temas. Integración en un grupo de investigación internacional. El DLR está compuesto por 32 institutos de investigación e instalaciones en 16 sedes que en total suman a más de 8000 empleados. Fecha de incorporación flexible a negociar. La estancia está dotada con una ayuda bajo la figura de un contrato de estudiante (legislación alemana). Es posible solicitar Erasmus Prácticas de forma adicional. Requisitos de los candidatos: Buen expediente académico. Buen nivel de inglés. (No se requiere hablar alemán). Capacidad de trabajo en grupo. Interesados, contactar con: Manuel Arrebola arrebola@uniovi.es Área de Teoría de la Señal y Comunicaciones Dpto. Ing. Eléctrica, Electrónica, de C y S

2 Start your mission with DLR space, and as the space agency of the German federal government. Approximately 8000 people work for DLR on a uniquely diverse range of topics spanning the fields of aeronautics, space, energy, transport and security research. They collaborate on projects extending from fundamental research to the development of the innovative applications and products of the future. If the idea of joining a top-class team of researchers LDACS Network Emulator Over the course of last several years, DLR has been actively working on developing a new L-band digital aeronautical communication system (LDACS) for civil aviation to meet the capacity requirements for future digital data link communications. LDACS prototypes will become available within the next years; however, the current unavailability of full-system prototypes leaves a gap preventing the evaluation of the overall system performance in realistic test-bed networks. The objective of this thesis is to develop and implement a method to emulate the LDACS datalink, such that it matches the expected LDACS user-plane performance in terms of bandwidth, latency, and loss, and can be used in test-bed IPv6 networks. The thesis should comprise two parts: (1) a theoretical part identifying and describing a suitable method for the LDACS network emulation; (2) the implementation of an LDACS emulator in a Unix environment and its validation against existing simulation results. Excellent knowledge of computer networks. Detailed knowledge of data link layer protocols is desired. Excellent scripting and programming knowledge in the Unix environment. Knowledge of ipfw and dummynet and experience with FreeBSD is desired. Independent working. personal and professional development. Disabled applicants with equivalent qualifications will be given preferential treatment. If you have any questions concerning specific aspects of the job, please contact Dr. Thomas Gräupl by calling or by sending an to Thomas.Graeupl@dlr.de.

3 space, and as the space agency of the German federal government. Approximately 7000 people work for DLR on a uniquely diverse range of topics spanning the fields of aeronautics, space, energy, transport and security research. They collaborate on projects extending from fundamental research to the development of the innovative applications and products of the future. If the idea of joining a top-class team of researchers Distributed Sparse Bayesian Learning for Robotic Swarm Exploration of Static Spatial Processes Distributed learning is a field that generalizes classical machine learning algorithms to a distributed framework in which data are distributed among a number of sensor-equipped agents or smart sensors. This task often arises in autonomous robotic exploration of spatially-distributed phenomena: agents have to collaboratively reconstruct a model of a spatial process from local, yet spatially-distributed measurements. When the observed process can be assumed to be sparse, data acquisition can be performed quite efficiently, since fewer measurements are needed to accurately reconstruct a sparse process. The goal of this Master Thesis is to implement and test a distributed sparse Bayesian learning (SBL) algorithm for modeling of a magnetic field. The magnetic field measurements are performed with a swarm of mobile robots; the processing has to be also realized in real-time. Based on the learned sparse representation, several information-driven exploration strategies that guide the robots to more informative sampling locations are to be implemented and tested. A potential candidate is expected to develop and test the corresponding algorithms on embedded PCs and multiple robotic platforms, as well as perform experiments, investigating the properties of the algorithms and their performance in a realistic environment. Excellent knowledge of signal processing and estimation theory Knowledge of Python or C++ knowledge of Robotic Operating System is advantageous Independent working and a good working knowledge of English or German personal and professional development. Disabled applicants with equivalent qualifications will be given preferential treatment. If you have any questions concerning specific aspects of the job, please contact Dr. Dmitriy Shutin by calling or by sending an to Dmitriy.Shutin@dlr.de

4 space, and as the space agency of the German federal government. Approximately 7000 people work for DLR on a uniquely diverse range of topics spanning the fields of aeronautics, space, energy, transport and security research. They collaborate on projects extending from fundamental research to the development of the innovative applications and products of the future. If the idea of joining a top-class team of researchers Towards autonomous localization of avalanche victims with a robotic system Avalanches cause hundreds of deaths every year only in Europe. Here, a fast localization of the victims is crucial since probability of survival dramatically decreases with time. The most common device to locate victims is an avalanche beacon (ARVA). This device must be carried by both the victim and rescuers. The ARVA transmits a magnetic field that can be measured by the rescuers. Once a strong magnetic signal is identified, the rescuer follows the magnetic field fluctuations to identify the location that yields the maximum magnetic field intensity. Nowadays the search and localization of the victim is carried out by rescue teams that walk the avalanche area to identify the beacon and locate the victim. However, this process has a high risk for the rescuer due to the challenging conditions in the mountains. Moreover, it requires specific training. Therefore, we propose the use of an autonomous robotic system MAVs equipped with an ARVA to efficiently perform this task. In contrast to humans, they can autonomously decide on their next actions and can fly to potentially risky areas. The goal of this Master Thesis is to investigate several algorithms to collaboratively locate avalanche victims with a robotic system. Firstly, a simulation environment and state-of-the-art algorithms will be developed. Secondly, the student will develop a novel algorithm to improve the efficiency of the localization task. In addition to the development of the mathematical foundations and algorithms, this research will involve the validation of the work on real robotic hardware - MAVs and/or ground based robots. The experimental tests will be carried out in our Holodeck laboratory equipped with a motion capture system. Independent working and fluent English. Excellent programming skills. Strong interest in experimental work. personal and professional development. Disabled applicants with equivalent qualifications will be given preferential treatment. If you have any questions concerning specific aspects of the job, please contact Alberto Viseras Ruiz by calling or by sending an to Alberto.ViserasRuiz@dlr.de

5 space, and as the space agency of the German federal government. Approximately 8000 people work for DLR on a uniquely diverse range of topics spanning the fields of aeronautics, space, energy, transport and security research. They collaborate on projects extending from fundamental research to the development of the innovative applications and products of the future. If the idea of joining a top-class team of researchers Two-way Ranging with LDACS1 Over the course of last several years, DLR has been actively working on developing a new L-band digital aeronautical communication system (LDACS) for civil aviation to meet the capacity requirements for future digital data link communications. LDACS1 is the broadband candidate and employs the Orthogonal Frequency-Division Multiplexing (OFDM) transmission scheme in both forward and reverse links. Recently, LDACS1 has been extended to include a ranging functionality. The LDACS1 signals from the ground stations are used to determine pseudo-ranges at the aircraft. Having available at least four range measurements from LDACS1 signals or other sensors allows for determining the aircraft position. An alternative for ranging is to use LDACS1 signals transmitted by the aircraft. These aircraft requests are acknowledged by the ground station after a pre-determined time. With this, two-way ranging is possible with LDACS1 signals leading to range estimates instead of pseudo-ranges. The same functionality is currently performed by the so-called Distance Measuring Equipment (DME). Including DME-ranging into LDACS1 might finally enable to decommission DME and free L-band spectrum for further applications. One main goal of this Master thesis is to determine the accuracy achievable with LDACS1 two-way ranging. To achieve this, a MATLAB simulation for two-way ranging including clock inaccuracies has to be set-up. The second goal of the Master thesis is to develop algorithms to improve the achievable range accuracy. Excellent knowledge of OFDM and good knowledge of ranging/positioning algorithms Excellent MATLAB knowledge Good mathematical/signal-processing background Independent working personal and professional development. Disabled applicants with equivalent qualifications will be given preferential treatment. If you have any questions concerning specific aspects of the job, please contact Dr. Michael Schnell by calling or by sending an to Michael.Schnell@dlr.de.

6 DLR.de/jobs Master Thesis / Internship Towards Reliable Train-to-Train Communications Develop Simulation Chain and Test State-of-the-Art Systems space, and as the space agency of the German federal government. Approximately 7700 people work for DLR on a uniquely diverse range of topics spanning the fields of aeronautics, space, energy, transport and security research. They collaborate on projects extending from fundamental research to the development of the innovative applications and products of the future. If the idea of joining a top-class team of researchers working in a supportive, inspirational environment appeals to you, then why not launch your mission with us? For our Institute of Communications and Navigation in Oberpfaffenhofen, we wish to recruit a qualified Master Student Background: DLR is currently developing a new generation of train communication systems based on wireless technologies for train control and monitoring functions, thus reducing onboard communication cables and simplifying the train coupling procedure. The development is covering different communications functions while being dependent on the development of the wireless technologies in other sectors. Taking these considerations into account, different levels of implementation with increasing difficulty are expected. These levels cover different applications starting from non-critical functions (e.g. multimedia, infotainment), functions relevant to vehicle availability (e.g. air conditioned) and the highest level being safety critical functions (full train control and monitoring system). For the characterization of a radio link in a high-speed Train-to-Train and Train-to-Ground environments, the master student shall develop a wireless communications system and a channel model using measurement data to study and evaluate the effects of the channel on the system. The work shall also assess the suitability of current standards like IEEE p for reliable Train-to-Train and Train-to-Ground communications. Key tasks: 1. Review and familiarize yourself with standardized wireless communications systems like IEEE p 2. Review and familiarize yourself with the state-of-the art in channel modeling for Train-to-Train and Trainto-Ground environments 3. Implement a wireless communications chain using simulation tools 4. Develop and implement a suitable channel model for given scenarios 5. Implement appropriate extensions for existing simulation tools 6. The work concludes with recommendations for the use of a suitable communication system and its operation conditions for a high-speed vehicular context. 7. Document methodologies and results in thesis report. We encourage publishing results Studies in electrical or communications engineering, computer science, or a related field Knowledge about communications technology required Knowledge about car-to-car or train-to-train communications required Knowledge about MATLAB and C++ required

7 DLR.de/jobs personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Disabled applicants with equivalent qualifications will be given preferential treatment. If you have any questions concerning specific aspects of the job, please contact Dr. Stephan Sand by calling or send an to stephan.sand@dlr.de.

8 space, and as the space agency of the German federal government. Approximately 8000 people work for DLR on a uniquely diverse range of topics spanning the fields of aeronautics, space, energy, transport and security research. They collaborate on projects extending from fundamental research to the development of the innovative applications and products of the future. If the idea of joining a top-class team of researchers Map Matching in Indoor Navigation Positioning in buildings and other environments where GNSS reception is difficult will require a combination of sensors and other information such as building plans. We are pursuing sensor fusion that combine GNSS, foot mounted inertial sensors, electronic compasses, baro-altimeters, maps and wireless distance measurements. A particularly powerful combination is INS step measurement in conjunction with maps, FootSLAM, which can converge to the correct position after less than a minute of motion. We have developed a two-layer sensor fusion architecture that operates with a Kalman filter where possible, and fuses other sensors and maps at a higher-level, lower rate, particle filter. FootSLAM estimates a map during the walk. For some buildings a floor plan is already available. In this master thesis, different ways of using the building layouts can be envisaged: e.g. using the map as prior map for FootSLAM or for constraining the particles with the knowledge of the walls within the particle filter. The main goal of this master thesis is to extend the current FootSLAM framework to handle maps. Especially, the conversion of available maps to be used as prior information for FootSLAM, the way of integrating them in the algorithm and the effect on using them in FootSLAM shall be investigated. The implemented algorithms shall be tested through several experiments. Further information on FootSLAM: Excellent knowledge of positioning algorithms (Kalman filter, particle filter) Excellent JAVA knowledge Good mathematical/signal-processing background Independent working Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Disabled applicants with equivalent qualifications will be given preferential treatment. If you have any questions concerning specific aspects of the job, please contact Dr. Susanna Kaiser by calling or by sending an to Susanna.Kaiser@dlr.de.

9 DLR.de/jobs space, and as the space agency of the German federal government. Approximately 8000 people work for DLR on a uniquely diverse range of topics spanning the fields of aeronautics, space, energy, transport and security research. They collaborate on projects extending from fundamental research to the development of the innovative applications and products of the future. If the idea of joining a top-class team of researchers Diploma/Master thesis Combining inertial measurement sets for pedestrian navigation Inertial technology is among the most promising technologies to enable navigation and positioning applications in indoor environments. These devices are widely available as they are integrated in smartphones, smart watches, ear pods, etc. Their size allows them even to be integrated within clothes. Nevertheless, the benefits of this technology come at a cost: the inertial signals are disturbed by noise sources that hinder the position estimation process. Yet, we foresee a growth in the number of inertial sensors that a user will carry in the future, so that there will be more than one inertial measurement unit (IMU) available for inertial navigation. According to the motto the more, the merrier, we propose to use the information from several IMUs to improve the estimation of the pedestrian s position. Initial studies showed promising results regarding the combination of IMUs for the estimation of the pedestrian s position. The goal of this master thesis is to exploit the benefits of having simultaneous inertial measurements from a foot- and pocket-mounted IMU. The algorithm developed must be tested with the available data set. Furthermore, a more challenging data set must be recorded to proof the concept developed. Excellent knowledge of positioning algorithms, filtering algorithms (Kalman filter, particle filter) Good mathematical/signal-processing background Excellent Matlab programming knowledge Independent working Good English (written and spoken) personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Disabled applicants with equivalent qualifications will be given preferential treatment. If you have any questions concerning specific aspects of the job, please contact Dina Bousdar at dina.bousdarahmed@dlr.de.

10 space, and as the space agency of the German federal government. Approximately 8000 people work for DLR on a uniquely diverse range of topics spanning the fields of aeronautics, space, energy, transport and security research. They collaborate on projects extending from fundamental research to the development of the innovative applications and products of the future. If the idea of joining a top-class team of researchers Global Maps for Multipath Assisted Positioning Positioning is essential for many applications in wireless radio communications. With Channel-SLAM, we proposed a paradigm shift in how to process the received signal in order to provide accurate position estimation for mobile receivers: rather than mitigating multipath, we propose to exploit multipath. Channel-SLAM treats each multipath component as a line of sight signal from a virtual transmitter which is time synchronized to the physical transmitter and static in its position. Hence, multipath propagation increases the number of transmitters by such virtual transmitters resulting in more accurate position estimation or enabling positioning in situations where the number of physical transmitters is insufficient. Channel-SLAM estimates the receiver position and the positions of the virtual transmitters simultaneously and does not require any prior information such as room-layout or a database for fingerprinting. Recently, Channel-SLAM was extended to enable mapping, where we derive a probabilistic map representation based on the receiver positions. Thus, if the receiver knows its current location, the information in the probabilistic map helps to estimate the trajectory of further receiver movement. Hence, as soon as the receiver returns to an already mapped position, information of the probabilistic map can be used for the movement to obtain better estimations of the receiver position. This Master thesis builds on and extends the previous work on Channel-SLAM. During the thesis, the student shall derive an algorithm which allows sharing maps of virtual transmitters between different receivers The derived algorithm shall provide a global dynamic map, which is updated by each receiver and therefore enables changes in the map environment. With a global dynamic map, virtual transmitters can be used similarly to real transmitters with the advantage that virtual transmitters are always in LoS to the receiver. Additionally, the results should be verified by simulations and/or measurements. Excellent MATLAB knowledge Good mathematical/signal-processing background Independent working personal and professional development. Disabled applicants with equivalent qualifications will be given preferential treatment. If you have any questions concerning specific aspects of the job, please contact Christian Gentner by calling or by sending an to christian.gentner@dlr.de.