Our research experts

Dr. Gor Hakobyan

Future radar sensors for self-driving cars

“As a researcher you study what is yet to be discovered, and thus deal with complexity, uncertainty, and risk of failure. Having a sense of where to invest your time and mental resources and maybe even more importantly where not to, is what subtly distinguishes a good researcher. This takes vision, expertise, independent thinking, and most importantly, curiosity.”

Dr. Gor Hakobyan

I am passionate about bringing new methods and algorithms from the ground up to implementation in real-life sensor systems. Particularly, my focus is on enabling automotive radar to become a core sensor technology for self-driving cars. Stepping up the radar performance requires much more than a straightforward upscaling of the currently available systems. This provides a large scope for creativity, from simple but ingenious solutions to sophisticated mathematical modeling.

Curriculum vitae

Robert Bosch GmbH

from 2017
Research scientist in the area of automotive radar

University of Stuttgart

2018
PhD in the area of radar signal processing

Selected publications

  • OFDM-MIMO Radar with Optimized Non-Equidistant Subcarrier Interleaving

    G. Hakobyan et al. (2019)

    OFDM-MIMO Radar with Optimized Non-Equidistant Subcarrier Interleaving
    • G. Hakobyan, M. Ulrich, B. Yang
    • IEEE Transactions on Aerospace and Electronic Systems
  • Interference-Aware Cognitive Radar: A Remedy to the Automotive Interference Problem

    G. Hakobyan et al. (2019)

    Interference-Aware Cognitive Radar: A Remedy to the Automotive Interference Problem
    • G. Hakobyan, K. Armanious, B. Yang
    • IEEE Transactions on Aerospace and Electronic Systems
  • High-Performance Automotive Radar: A Review of Signal Processing Algorithms and Modulation Schemes

    G. Hakobyan, B. Yang (2019)

    High-Performance Automotive Radar: A Review of Signal Processing Algorithms and Modulation Schemes
    • G. Hakobyan and B. Yang
    • IEEE Signal Processing Magazine
  • Machine Learning Applications on Automotive Radar

    Robert Bosch Gmbh (2019)

    Machine Learning Applications on Automotive Radar
    • G. Hakobyan
    • 2 patent families
  • Orthogonal frequency division multiplexing multiple-input multiple-output automotive radar with novel signal processing algorithms

    G. Hakobyan (2018)

    Orthogonal frequency division multiplexing multiple-input multiple-output automotive radar with novel signal processing algorithms
    • PhD Dissertation
    • University of Stuttgart
  • A Novel Intercarrier-Interference Free Signal Processing Scheme for OFDM Radar

    G. Hakobyan, B. Yang (2018)

    A Novel Intercarrier-Interference Free Signal Processing Scheme for OFDM Radar
    • G. Hakobyan and B. Yang
    • IEEE Transactions on Vehicular Technology
  • Automotive LiDAR

    Robert Bosch Gmbh (2018)

    Automotive LiDAR
    • G. Hakobyan, O. Kern, R. Korn
    • 1 patent family
    • EP2019/064508
  • A novel OFDM-MIMO radar with non-equidistant subcarrier interleaving and compressed sensing

    G. Hakobyan et al. (2016)

    A novel OFDM-MIMO radar with non-equidistant subcarrier interleaving and compressed sensing
    • G. Hakobyan and B. Yang
    • International Radar Symposium
    • Best Paper Award in the Young Scientist Constest
  • A novel narrowband interference suppression method for OFDM radar

    G. Hakobyan, B. Yang (2016)

    A novel narrowband interference suppression method for OFDM radar
    • G. Hakobyan and B. Yang
    • European Signal Processing Conference (EUSIPCO)
  • Automotive Radar

    Robert Bosch Gmbh (2014 - 2019)

    Automotive Radar
    • G. Hakobyan
    • 7 patent families
    • Inventions of various radar system concepts, signal processing aglorithms, radar operation methods and interference mitigation schemes

Interview

Dr. Gor Hakobyan

Dr. Gor Hakobyan

Research scientist in the area of automotive radar

Please tell us what fascinates you most about research.

Coming up with simple solutions outside the realm of well-established research is what I enjoy the most. Being at the frontier of scientific research challenges creativity in new ways every time.

Dr. Gor Hakobyan

Dr. Gor Hakobyan

Research scientist in the area of automotive radar

What makes research done at Bosch so special?

At Bosch we have a sweet spot between academic and product-oriented research. Our research focuses on real-world products and solutions, while staying at the cutting edge of science and technology. What makes Bosch particularly special is the interdisciplinary nature of its corporate research due to the large variety of Bosch products. I am privileged to work daily with world-class experts in various research fields.

Dr. Gor Hakobyan

Dr. Gor Hakobyan

Research scientist in the area of automotive radar

What research topics are you currently working on at Bosch?

My research focuses on signal processing algorithms and system design of automotive radar sensors. Specifically, I work on mathematical methods that improve automotive radar performance to accommodate the needs of self-driving cars. This includes advanced signal processing algorithms, approaches for compressive signal acquisition and processing, and radar interference mitigation. Another technology which we actively drive with a potential to cause a massive paradigm shift in future is software-defined radar that operates with digitally-generated radar waveforms.

Dr. Gor Hakobyan

Dr. Gor Hakobyan

Research scientist in the area of automotive radar

What are the biggest scientific challenges in your field of research?

Self-driving cars need very accurate and robust sensing technologies for perception of the driving environment. To obtain a large level of detail in environment sensing, we need radar images with high resolution and large dynamic range. To step up today's radar to the performance required for autonomous driving, and this at an acceptable cost, is a big challenge that offers a fertile research ground.

Dr. Gor Hakobyan

Dr. Gor Hakobyan

Research scientist in the area of automotive radar

How do the results of your research become part of solutions "Invented for life"?

Radar is a core technology both for driver assistance systems today and self-driving cars in the near future. The comfort and safety systems based on radar improve the driving experience and prevent road accidents. Autonomous driving, which heavily relies on radar sensors for robust environment perception, will revolutionize mobility. In combination with data-driven perception algorithms, better sensors are the basis for safety of autonomous cars.

Dr. Gor Hakobyan

Get in touch with me

Dr. Gor Hakobyan
Research scientist in the area of automotive radar
E-mail

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