MERL - Mitsubishi Electric Research Laboratories

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Signal Processing

Acquisition and processing of information.

Our research in the area of signal processing encompasses a wide range of work in the areas of communications, sensing, estimation, localization, and speech and visual information processing. We explore novel approaches for signal acquisition and coding, methods to filter and recover signals in the presence of noise and other degrading factors, and techniques that infer meaning from the processed signals.

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  • Researchers

  • Awards

    •  AWARD   MERL Researchers Won IEEE ICC Best Paper Award.
      Date: May 22, 2019
      Awarded to: Siriramya Bhamidipati, Kyeong Jin Kim, Hongbo Sun, Philip Orlik
      MERL Contacts: Kyeong Jin (K.J.) Kim; Hongbo Sun
      Research Areas: Artificial Intelligence, Communications, Machine Learning, Signal Processing, Information Security
      Brief
      • MERL researchers, Kyeong Jin Kim, Hongbo Sun, Philip Orlik, along with lead author and former MERL intern Siriramya Bhamidipati were awarded the Smart Grid Symposium Best Paper Award at this year's International Conference on Communications (ICC) held in Shanghai, China. There paper titled "GPS Spoofing Detection and Mitigation in PMUs Using Distributed Multiple Directional Antennas," described a technique to rapidly detect and mitigate GPS timing attacks/errors via hardware (antennas) and signal processing (Kalman Filtering)
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    •  AWARD   MERL researcher wins IEEE Young Author Best Paper award
      Date: January 2, 2019
      Awarded to: Siheng Chen
      MERL Contact: Siheng Chen
      Research Area: Signal Processing
      Brief
      • MERL researcher, Siheng Chen, has won an IEEE Young Author Best Paper award for his paper entitled "Discrete Signal Processing on Graphs: Sampling Theory". This paper, published in the December 2015 issue of IEEE Transactions on Signal Processing, proposes a sampling theory for signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory and shows that perfect recovery is possible for graph signals bandlimited under the graph Fourier transform. The award honors the authors of an especially meritorious paper dealing with a subject related to IEEE's technical scope and appearing in one if its journals within a three year window of eligibility.
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    •  AWARD   Former Intern Receives IBM Scientific Award Honorable Mention
      Date: January 16, 2019
      Awarded to: Daniel Dinis
      MERL Contact: Rui Ma
      Research Areas: Communications, Signal Processing
      Brief
      • Former MERL intern Daniel Dinis from University of Aveiro (UA), Portugal has received the 2018 IBM Scientific Award with Honorable Mention referring to the contributions on "Real-time Tunable Delta-sigma modulators for All-Digital RF Transmitters" in his Ph.D. study.

        The award-winning work includes research conducted under the supervision of Arnaldo Oliveira and José Neto Vieira, professors from the Department of Electronics and Information Technology (DETI) of the UA, as well as contributions made during Daniel's 7 month internship in 2017 at MERL.

        The ceremony for the presentation of the 28th IBM Scientific Prize took on January 16th, at the Noble Hall of the Superior Technical Institute. It was chaired by Marcelo Rebelo de Sousa, President of the Portuguese Republic.
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  • News & Events

    •  NEWS   MERL Scientists Presenting 11 Papers at IEEE Global Communications Conference (GLOBECOM) 2019
      Date: December 9, 2019 - December 13, 2019
      Where: Waikoloa, Hawaii, USA
      MERL Contacts: Jianlin Guo; Kyeong Jin (K.J.) Kim; Toshiaki Koike-Akino; Rui Ma; Philip Orlik; Pu (Perry) Wang
      Research Areas: Communications, Computer Vision, Machine Learning, Signal Processing, Information Security
      Brief
      • MERL Signal Processing scientists and collaborators will be presenting 11 papers at the IEEE Global Communications Conference (GLOBECOM) 2019, which is being held in Waikoloa, Hawaii from December 9-13, 2019. Topics to be presented include recent advances in power amplifier, MIMO algorithms, WiFi sensing, video casting, visible light communications, user authentication, vehicular communications, secrecy, and relay systems, including sophisticated machine learning applications. A number of these papers are a result of successful collaboration between MERL and world-leading Universities including: Osaka University, University of New South Wales, Oxford University, Princeton University, South China University of Technology, Massachusetts Institute of Technology and Aalborg University.

        GLOBECOM is one of the IEEE Communications Society’s two flagship conferences dedicated to driving innovation in nearly every aspect of communications. Each year, more than 3000 scientific researchers and their management submit proposals for program sessions to be held at the annual conference. Themed “Revolutionizing Communications,” GLOBECOM2019 will feature a comprehensive high-quality technical program including 13 symposia and a variety of tutorials and workshops to share visions and ideas, obtain updates on latest technologies and expand professional and social networking.
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    •  NEWS   Anthony Vetro appointed as a Senior Area Editor of the new IEEE Open Journal of Signal Processing
      Date: November 8, 2019
      MERL Contact: Anthony Vetro
      Research Area: Signal Processing
      Brief
      • Anthony Vetro has been appointed for a two-year term as a Senior Area Editor of the new IEEE Open Journal of Signal Processing.

        This fully open access journal will publish high-quality, peer-reviewed papers covering the enabling technology for the generation, transformation, extraction, and interpretation of information. It comprises the theory, algorithms with associated architectures and implementations, and applications related to processing information contained in many different formats broadly designated as signals.
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  • Internships

    • SP1379: Intelligent Brain-Machine Interface

      The Signal Processing group at MERL is seeking a highly motivated, qualified individual to join our 3-month internship program of research on stressless man-machine interface with multi-modal bio-sensors. The ideal candidate is expected to possess an excellent background in brain-machine interfaces, data analytics, machine learning, sensor design, electro-magnetic analysis, augmented reality, and sensing algorithms. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    • SP1414: Learning for inverse problems and dynamical systems

      The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop algorithms that solve inverse problems in computational sensing that incorporate deep learning architectures for a variety of sensing applications. The project goal is to improve the performance and develop an analysis of algorithms used for inverse problems by incorporating new tools from machine learning and artificial intelligence. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, large-scale optimization, plug-and-play priors, learning-based modeling for imaging, learning theory for computational imaging, and Koopman theory/dynamic mode decomposition. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible.

    • SP1410: Coherent Optical Sensing

      MERL is seeking an intern to work on coherent optical sensing. The ideal candidate would be an experienced PhD student or post-graduate researcher working in coherent sensing. The candidate should have a detailed knowledge of optical interferometry and imaging with a focus on either optical coherence tomography, optical coherence microscopy or FMCW LIDAR. Strong programming skills in Matlab are essential. Experience of working in an optical lab environment would be advantageous. Duration is 3 to 6 months.


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  • Recent Publications

    •  Liu, F., Zhu, H., Li, C., Li, J., Wang, P., Orlik, P.V., "Angular-Domain Channel Estimation for One-Bit Massive MIMO Systems: Performance Bounds and Algorithms", IEEE Transactions on Vehicular Technology, DOI: 10.1109/TVT.2020.2966003, ISSN: 0018-9545, Vol. 69, No. 3, January 2020.
      BibTeX Download PDFAbout TR2020-009
      • @article{Liu2020jan,
      • author = {Liu, Fangqing and Zhu, Heng and Li, Changheng and Li, Jian and Wang, Pu and Orlik, Philip V.},
      • title = {Angular-Domain Channel Estimation for One-Bit Massive MIMO Systems: Performance Bounds and Algorithms},
      • journal = {IEEE Transactions on Vehicular Technology},
      • year = 2020,
      • volume = 69,
      • number = 3,
      • month = jan,
      • doi = {10.1109/TVT.2020.2966003},
      • issn = {0018-9545},
      • url = {https://www.merl.com/publications/TR2020-009}
      • }
    •  Teng, M., Safian, R., Alahmadi, Y., Zhuang, L., Kojima, K., "Miniaturized silicon photonics devices for integrated optical signal processors", JLT (Invited Review Paper), January 2020.
      BibTeX Download PDFAbout TR2020-010
    •  Wang, P., Li, H., "Target Detection with Imperfect Waveform Separation in Distributed MIMO Radar", IEEE Transactions on Signal Processing, DOI: 10.1109/TSP.2020.2964227, ISSN: 1053-587X, Vol. 68, No. 1, pp. 793-807, January 2020.
      BibTeX Download PDFAbout TR2020-007
      • @article{Wang2020jan,
      • author = {Wang, Pu and Li, Hongbin},
      • title = {Target Detection with Imperfect Waveform Separation in Distributed MIMO Radar},
      • journal = {IEEE Transactions on Signal Processing},
      • year = 2020,
      • volume = 68,
      • number = 1,
      • pages = {793--807},
      • month = jan,
      • doi = {10.1109/TSP.2020.2964227},
      • issn = {1053-587X},
      • url = {https://www.merl.com/publications/TR2020-007}
      • }
    •  Berntorp, K., Quirynen, R., Uno, T., Di Cairano, S., "Trajectory Tracking for Autonomous Vehicles on Varying Road Surfaces by Friction-Adaptive Nonlinear Model Predictive Control", Journal of Vehicle Systems Dynamics, January 2020.
      BibTeX Download PDFAbout TR2020-005
      • @article{Berntorp2020jan,
      • author = {Berntorp, Karl and Quirynen, Rien and Uno, Tomoki and Di Cairano, Stefano},
      • title = {Trajectory Tracking for Autonomous Vehicles on Varying Road Surfaces by Friction-Adaptive Nonlinear Model Predictive Control},
      • journal = {Journal of Vehicle Systems Dynamics},
      • year = 2020,
      • month = jan,
      • url = {https://www.merl.com/publications/TR2020-005}
      • }
    •  Berntorp, K., Hiroaki, K., "Bayesian Learning of Tire Friction with Automotive-Grade Sensors by Gaussian-Process State-Space Models", IEEE Conference on Decision and Control (CDC), December 2019.
      BibTeX Download PDFAbout TR2019-145
      • @inproceedings{Berntorp2019dec,
      • author = {Berntorp, Karl and Hiroaki, Kitano},
      • title = {Bayesian Learning of Tire Friction with Automotive-Grade Sensors by Gaussian-Process State-Space Models},
      • booktitle = {IEEE Conference on Decision and Control (CDC)},
      • year = 2019,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2019-145}
      • }
    •  Fujihashi, T., Koike-Akino, T., Watanabe, T., Orlik, P.V., "DNN-based Overhead Reduction for High-Quality Soft Delivery", IEEE Global Communications Conference (GLOBECOM), December 2019.
      BibTeX Download PDFAbout TR2019-133
      • @inproceedings{Fujihashi2019dec2,
      • author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi and Orlik, Philip V.},
      • title = {DNN-based Overhead Reduction for High-Quality Soft Delivery},
      • booktitle = {IEEE Global Communications Conference (GLOBECOM)},
      • year = 2019,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2019-133}
      • }
    •  Fujihashi, T., Koike-Akino, T., Watanabe, T., Orlik, P.V., "DNN-based Simultaneous Screen-to-Camera and Screen-to-Eye Communications", IEEE Global Communications Conference (GLOBECOM), December 2019.
      BibTeX Download PDFAbout TR2019-132
      • @inproceedings{Fujihashi2019dec,
      • author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi and Orlik, Philip V.},
      • title = {DNN-based Simultaneous Screen-to-Camera and Screen-to-Eye Communications},
      • booktitle = {IEEE Global Communications Conference (GLOBECOM)},
      • year = 2019,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2019-132}
      • }
    •  Jespersen, M.H., Pajovic, M., Koike-Akino, T., Wang, Y., Popovski, P., Orlik, P.V., "Deep Learning for Synchronization and Channel Estimation in NB-IoT Random Access Channel", IEEE Global Communications Conference (GLOBECOM), December 2019.
      BibTeX Download PDFAbout TR2019-140
      • @inproceedings{Jespersen2019dec,
      • author = {Jespersen, Mads Helge and Pajovic, Milutin and Koike-Akino, Toshiaki and Wang, Ye and Popovski, Petar and Orlik, Philip V.},
      • title = {Deep Learning for Synchronization and Channel Estimation in NB-IoT Random Access Channel},
      • booktitle = {IEEE Global Communications Conference (GLOBECOM)},
      • year = 2019,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2019-140}
      • }
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