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

Netherlands·Eindhovenentry

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Requirements Summary

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,

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Responsibilities

~1 min read

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.

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Investigate the impact of phase noise accumulation and multipath propagation in large MIMO FMCW radar systems employing DDMA and related techniques.
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Develop mathematical models and simulation frameworks to analyze radar system performance, including angle resolution, Doppler resolution, detection capability, and phase-noise robustness.
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Research and evaluate hybrid radar architectures that combine MIMO imaging capability with directional phased-array transmission.
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Explore beam-scanning strategies, DDMA-based transmission schemes, sparse transmit activation methods, and subarray-based beamforming concepts.
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Design and perform MATLAB and/or Python simulations to compare alternative radar architectures and quantify associated system trade-offs.

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.

During 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.

Requirements

~1 min read

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.

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