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2015 Fiscal Year Research-status Report

Multidimensional compressive sensing based technologies for next-generation MIMO radar with SL3: Super-resolution, Low-complexity, Low-cost and Low-consumption

Research Project

Project/Area Number 15K06072
Research InstitutionAkita Prefectural University

Principal Investigator

徐 粒  秋田県立大学, システム科学技術学部, 教授 (40252324)

Co-Investigator(Kenkyū-buntansha) 桂 冠  秋田県立大学, システム科学技術学部, 特任助教 (80734904) [Withdrawn]
松下 慎也  秋田県立大学, システム科学技術学部, 准教授 (20435449)
Project Period (FY) 2015-04-01 – 2019-03-31
Keywordssub-Nyquist sampling / MIMO comunication system / least mean square (LMS) / sparse signal processing / adaptive filtering / channel identification
Outline of Annual Research Achievements

As the main task in the FY2015, sub-Nyquist adaptive sampling techniques and adaptive sparse signal identification techniques have been intensively investigated, and the obtained results are briefly summarized as follows:

A compressive sensing (CS) based sub-Nyquist adaptive sampling technique has been developed, by utilizing l_0-NLMS (normalized least mean square) algorithm and DHT (discrete Hartley transform), for random demodulation sampling in the frequency domain. The proposed method has low computational complexity and better robustness to noise than the existing methods, and can be applied to the realization of low-speed ADC based MIMO radar systems.

CS-based low-complexity identification techniques have been proposed by using adaptive sparse algorithms to achieve better performance for large-scale MIMO systems under different circumstances. Specifically, an effective large-scale MIMO channel identification method by using affine combination of sparse adaptive filtering has been developed to achieve low-complexity, and, by utilizing the mixed square/fourth error criterion, improved adaptive sparse signal identification methods, e.g., zero-attracting least mean square/fourth (ZA-LMS/F) algorithm and reweighted ZA-LMS/F (RZA-LMS/F) algorithm, have been established.

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

The main goals of developing new sub-Nyquist adaptive sampling techniques and adaptive sparse signal identification techniques for FY2015 have been fulfilled smoothly almost as expected and some of the obtained results have already been published as journal/conference papers (see the publication list for the details), which will provide a fundamental and sound base for further exploration of this research.

Strategy for Future Research Activity

In the next stage of this research project, the main goal is, just as scheduled in the detailed research plan, to develop super-resolution large-scale MIMO radar technologies with the SL3 requirements, via establishing advanced beamforming strategies for large-scale MIMO radar transmitter, modeling low-speed ADC based large-scale MIMO radar system, developing super-resolution identification strategies and algorithms, and verifying the proposed techniques by theoretical analysis as well as numerical simulation.

Causes of Carryover

A very little amount (\71) was left just because it was difficult to find an item that exactly cost this amount.

Expenditure Plan for Carryover Budget

This small amount will be used up together with the budget of the next fiscal year.

  • Research Products

    (18 results)

All 2016 2015 Other

All Int'l Joint Research (1 results) Journal Article (5 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 5 results,  Acknowledgement Compliant: 3 results,  Open Access: 1 results) Presentation (11 results) (of which Int'l Joint Research: 11 results) Remarks (1 results)

  • [Int'l Joint Research] Nanjing Univ. Posts Telecommunications/Lanzhou University/China University of Geosciences(China)

    • Country Name
      China
    • Counterpart Institution
      Nanjing Univ. Posts Telecommunications/Lanzhou University/China University of Geosciences
    • # of Other Institutions
      2
  • [Journal Article] Stable adaptive channel estimation method under impulsive noise environments2016

    • Author(s)
      G. Gui, T. Zhang, J. Dan, Li Xu
    • Journal Title

      International Journal of Communication Systems

      Volume: 印刷中 Pages: 印刷中

    • DOI

      10.1002/dac.3104

    • Peer Reviewed / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments2015

    • Author(s)
      W. Ma, H. Qu, G. Gui, Li Xu, J. Zhao, and B. Chen
    • Journal Title

      The Journal of the Franklin Institute

      Volume: 352 Pages: 2708-2727

    • DOI

      10.1016/j.jfranklin.2015.03.039

    • Peer Reviewed / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Improved adaptive sparse channel estimation using mixed square/fourth error criterion2015

    • Author(s)
      G. Gui, Li Xu, S. Matsushita
    • Journal Title

      Journal of the Franklin Institute

      Volume: 352 Pages: 4579-4594

    • DOI

      10.1016/j.jfranklin.2015.07.006

    • Peer Reviewed / Acknowledgement Compliant
  • [Journal Article] Low-complexity large-scale multiple-input multiple-output channel estimation using affine combination of sparse least mean square filters2015

    • Author(s)
      G. Gui, N. Liu, Li Xu, F. Adachi
    • Journal Title

      IET Communications

      Volume: 9 Pages: 2168-2175

    • DOI

      10.1049/iet-com.2014.0979

    • Peer Reviewed
  • [Journal Article] On projection reflection method in Hilbert spaces2015

    • Author(s)
      S. Matsushita, Li Xu
    • Journal Title

      Journal of Nonlinear and Convex Analysis

      Volume: 16 Pages: 2221-2226

    • Peer Reviewed / Open Access
  • [Presentation] Correntropy Induced Metric Penalized Sparse RLS Algorithm to Improve Adaptive System Identification2016

    • Author(s)
      G. Gui, L. Dai, B. Zheng, Li Xu, F. Adachi
    • Organizer
      The 2016 IEEE 83rd Vehicular Technology Conference (VTC2016-Spring)
    • Place of Presentation
      Nanjing, China
    • Year and Date
      2016-05-15 – 2016-05-18
    • Int'l Joint Research
  • [Presentation] Fast NLMF-Type algorithms for adaptive sparse system identifications2015

    • Author(s)
      G. Gui, B. Liu, Li Xu, W. Ma
    • Organizer
      2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)
    • Place of Presentation
      Hongkong
    • Year and Date
      2015-12-16 – 2015-12-19
    • Int'l Joint Research
  • [Presentation] Correntropy induced metric penalized NLMF algorithm to improve sparse system identification2015

    • Author(s)
      G. Gui, Li Xu, B. Zheng
    • Organizer
      The 4th IEEE/CIC International Conference on Communications in China (ICCC2015)
    • Place of Presentation
      Shenzhen, China
    • Year and Date
      2015-11-02 – 2015-11-04
    • Int'l Joint Research
  • [Presentation] Iterative-Promoting Variable Step-Size LMS Algorithm based Adaptive Sparse Channel Estimation2015

    • Author(s)
      B. Liu, G. Gui, Li Xu
    • Organizer
      The 21st Asia‐Pacific Conference on Communications (APCC2015)
    • Place of Presentation
      Kyoto, Japan
    • Year and Date
      2015-10-14 – 2015-10-16
    • Int'l Joint Research
  • [Presentation] Stable Sparse Channel Estimation Algorithm under Non-Gaussian Noise Environments2015

    • Author(s)
      G. Gui, Li Xu, N. Shimoi
    • Organizer
      The 21st Asia‐Pacific Conference on Communications (APCC2015)
    • Place of Presentation
      Kyoto, Japan
    • Year and Date
      2015-10-14 – 2015-10-16
    • Int'l Joint Research
  • [Presentation] A Hybrid Optimization Approach for Discrete-Time H∞ Static-Output-Feedback Control Problem2015

    • Author(s)
      Z. Feng, Li Xu, Z. Liu, D. Li
    • Organizer
      The 34th Chinese Control Conference (CCC2015)
    • Place of Presentation
      Hangzhou, China
    • Year and Date
      2015-07-28 – 2015-07-30
    • Int'l Joint Research
  • [Presentation] A New Order Reduction Approach Based on Elementary Operation for Roesser State-Space Model2015

    • Author(s)
      D. Zhao, Q. Li, S. Yan, Li Xu
    • Organizer
      The 34th Chinese Control Conference (CCC2015)
    • Place of Presentation
      Hangzhou, China
    • Year and Date
      2015-07-28 – 2015-07-30
    • Int'l Joint Research
  • [Presentation] Improved Adaptive Sparse Channel Estimation Using Re-Weighted L1-norm Normalized Least Mean Fourth Algorithm2015

    • Author(s)
      C. Ye, G. Gui, Li Xu, N. Shimoi
    • Organizer
      SICE Annual Conference 2015
    • Place of Presentation
      Hangzhou, China
    • Year and Date
      2015-07-28 – 2015-07-30
    • Int'l Joint Research
  • [Presentation] Iteration-Promoting Variable Step Size Least Mean Square Algorithm for Accelerating Adaptive Channel Estimation2015

    • Author(s)
      B. Liu, G. Gui, Li Xu, N. Shimoi
    • Organizer
      SICE Annual Conference 2015
    • Place of Presentation
      Hangzhou, China
    • Year and Date
      2015-07-28 – 2015-07-30
    • Int'l Joint Research
  • [Presentation] Robust adaptive sparse channel estimation in the presence of impulsive noises2015

    • Author(s)
      G. Gui, Li Xu, W. Ma, B. Chen
    • Organizer
      The IEEE International Conference on Digital Signal Processing (DSP)
    • Place of Presentation
      Singapore
    • Year and Date
      2015-07-21 – 2015-07-24
    • Int'l Joint Research
  • [Presentation] 2-D Zero-Phase IIR Notch Filters Design Based on State-Space Representation of 2-D Frequency Transformation2015

    • Author(s)
      S. Yan, L. Sun, Li Xu
    • Organizer
      The 2015 IEEE International Symposium on Circuits and Systems (ISCAS2015)
    • Place of Presentation
      Lisbon, Portugal
    • Year and Date
      2015-05-24 – 2015-05-27
    • Int'l Joint Research
  • [Remarks] 研究業績

    • URL

      http://web.sc.eis.akita-pu.ac.jp/~xuli/publist.html

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Published: 2017-01-06  

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