Internship: Phase-Noise-Resilient Architectures for Large MIMO FMCW Automotive Radars

Job Responsibility:The internship focuses on the exploration and evaluation of next-generation automotive radar architectures that combine the benefits of large-scale MIMO imaging and phased-array beam steering. • Investigate the impact of phase noise accumulation and multipath propagation in large MIMO FMCW radar systems employing DDMA and related techniques. • Develop mathematical models and simulation frameworks to analyze radar system performance, including angle resolution, Doppler resolution, detection capability, and phase-noise robustness. • Research and evaluate hybrid radar architectures that combine MIMO imaging capability with directional phased-array transmission. • Explore beam-scanning strategies, DDMA-based transmission schemes, sparse transmit activation methods, and subarray-based beamforming concepts. • Design and perform MATLAB and/or Python simulations to compare alternative radar architectures and quantify associated system trade-offs.Project Deliverables • Literature review on MIMO radar, phased-array radar, DDMA processing, and phase-noise effects. • Simulation framework for evaluating hybrid radar architectures. • Analysis of trade-offs between angular resolution, Doppler resolution, frame rate, phase-noise robustness, and implementation complexity. • Evaluation of array configurations, beam scheduling approaches, and waveform design alternatives. • Final technical report and presentation summarizing findings and recommendations.Learning ObjectivesDuring this internship, the student will gain hands-on experience in: • Advanced FMCW automotive radar systems and signal processing. • MIMO radar, phased-array beamforming, and imaging radar concepts. • Array signal processing and direction-of-arrival estimation techniques. • System-level radar architecture design and performance optimization. • Research methodologies involving theoretical analysis, simulation, and engineering trade-off evaluation.Job Qualification: • The candidate must be pursuing a Master's degree in Electrical Engineering, Signal Processing, Applied Mathematics, Physics, or a related technical discipline. • Strong interest in radar systems, wireless communications, signal processing, and sensing technologies. • Familiarity with FMCW radar, MIMO radar, phased arrays, beamforming, antenna arrays, and RF impairments such as phase noise is highly beneficial. • Good understanding of FFT-based processing, range-Doppler processing, detection theory, estimation theory, array signal processing, and direction-of-arrival estimation. • Experience with MATLAB and/or Python for modeling, simulation, visualization, and algorithm development. • Knowledge of structured software development practices and version control tools such as Git is a plus. • Self-motivated, curious, analytical, and comfortable working on open research questions with both independent and collaborative work styles. • Strong written and verbal communication skills, with the ability to document technical findings and present results clearly. More information about NXP in the Netherlands... #LI-f5d0