• Compressive Sensing for Wideband Synthetic Aperture Radar Imaging Systems
  • Turbo Equalization for Underwater Wireless Communications

Compressive Sensing for Wideband Synthetic Aperture Radar Imaging Systems


Compressive Sensing for Wideband Synthetic Aperture Radar Imaging Systems

Dr. Rosa Zheng Project Image 1

INVESTIGATORS
Y. Rosa Zheng (zhengyr@mst.edu, 573-341-6632), Kristen Donnell, Tayeb Ghasr

 
FUNDING SOURCE
Army Office of Research, Intelligent Systems Center (Missouri S&T)


PROJECT DESCRIPTION
This research investigates compressive sensing method for near-field microwave and millimeter wave imaging systems. Two types of imaging systems are considered: one is wideband microwave camera that consists of randomly placed transmitter and receiver elements, another is wideband synthetic aperture radar imager that raster-scans the sample under test with a single transmit and receive element. The research objectives are to maintain image quality while reducing the cost of the imagers and reducing the time of operation. These objectives are achieved through compressive sensing and its image reconstruction algorithms by: (1) reducing the number of elements in the microwave camera, (2) reducing the number of scanning points in the raster scan imager, (3) incorporating advanced CS algorithms with SAR transforms and achieving high-quality image reconstruction. More details of the project description is available on the weblinks: http://web.mst.edu/~zhengyr and http://amntl.mst.edu/


PUBLICATIONS

  1. A Splitting Bregman-Based Compressed Sensing Approach for Radial UTE MRI,” D. Bi and L. Ma and X. Xie and Y. Xie and X. Li and Y. R. Zheng, IEEE Transactions on Applied Superconductivity, Vol. 26, No. 7, pp. 1-5. Oct. 2016.
  2. Efficient 2-D Millimeter-wave Synthetic Aperture Radar Image Reconstruction from Compressed Sampling,” D. Bi, Y. Xie, X. Li, and Y. R. Zheng, Elsevier J. DSP, Vol. 50, No. C, pp. 171-179, March 2016.
  3. A Sparsity Basis Selection Method for Compressed Sensing,” D. Bi, Y. Xie, X. Li, and Y. R. Zheng, IEEE Sig. Process. Letters, Vol. 22, no. 10, pp. 1738 - 1742, Oct. 2015.
  4. Synthetic Aperture Radar Imaging using Basis Selection Compressed Sensing,” D. Bi, Y. Xie, and Y. R. Zheng, Springer J. Circuits, Systems & Signal Processing, DOI: 10.1007/s00034-015-9974-y. vol. 34, no. 8, pp. 2561–2576, Aug. 2015.
  5. A comparative study of sparse methods for 3-D synthetic aperture radar image reconstruction,” Z. Yang and Y. R. Zheng, Elsevier DSP, Vol. 32, pp. 24—33, Sep. 2014.
  6. Compressed Sensing for SAR-Based Wideband Three-dimensional Microwave Imaging System Using Nonuniform Fast Fourier Transform,” H. Kajbaf, J.T. Case, Z. Yang, and Y. R. Zheng, IET Radar, Sonar and Navigation, vol. 7, no. 6, pp. 658 – 670, July 2013.
  7. Improving Efficiency of Microwave Wideband Imaging Using Compressed Sensing Techniques,” H. Kajbaf, Y. R. Zheng, and R. Zoughi, Material Evaluations, American Society for Nondestructive Testing, vol. 70, no. 12, pp. 1420-1432, Dec. 2012.
  8. Near-Field 3-D Synthetic Aperture Radar Imaging via Compressed Sensing,” Z. Yang and Y. R. Zheng, IEEE ICASSP, Kyoto, Japan, Mar. 25-30, 2012. pp. 2513-2516.
  9. 3D Image Reconstruction from Sparse Measurement of Wideband Millimeter Wave SAR Experiments,” H. Kajbaf, J. T. Case, Y. R. Zheng, IEEE Int’l Conf. Image Processing (ICIP2011), Brussels, Belgium, Sep 11-14, 2011. pp.2701-2704.

Turbo Equalization for Underwater Wireless Communications


Turbo Equalization for Underwater Wireless Communications

Dr. Rosa Zheng Project Image 2

INVESTIGATORS
Y. Rosa Zheng (zhengyr@mst.edu, 573-341-6632), Chengshan Xiao


FUNDING SOURCE
Office of Naval Research, Intelligent Systems Center (Missouri S&T)


PROJECT DESCRIPTION
This research investigates Turbo equalization for single-carrier underwater wireless communications. Two types of Turbo equalization schemes are considered: one is time-domain Turbo equalizer, including Turbo linear equalizer, block decision Turbo equalizer, soft decision Turbo equalizer, and soft interference cancellation equalizer, and bi-directional SDFE; another is frequency-domain Turbo equalization, including frequency-domain linear Turbo equalizer and FD decision-feedback Turbo equalizers. The developed Turbo equalizers achieved high reliability for severe triply-selective fading channels in underwater acoustic communications, especially in medium range (1-10 km) high data-rate (>10kbps) acoustic communications. The developed single-carrier Turbo equalizers exhibit higher data efficiency and better reliability than OFDM (Orthogonal Frequency Division Multiplexing) schemes. These equalizer algorithms have been evaluated by more than 20 real-world experiments conducted in oceans, rivers, and lakes. More details of the project is available on the weblink: http://web.mst.edu/~zhengyr


PUBLICATIONS

  1. Frequency Domain Turbo Equalization under MMSE Criterion for Single Carrier MIMO Systems,” Z. Chen, Y. R. Zheng, J. Wang, and J. Song, IEEE Trans. Vehicular Technology, accepted Mar. 2016.
  2. Turbo Equalization for Underwater Acoustic Communications,” Y. R. Zheng, J. Wu, and C. Xiao, IEEE Commun. Mag., Vol. 53, No. 11, pp. 79-87, Nov. 2015.
  3. Bidirectional Soft Decision Feedback Turbo Equalization for MIMO Systems,” W. Duan and Y. R. Zheng, IEEE Trans. Veh. Techno., Vol. 65, No. 7, pp. 4925 – 4936, Aug. 2016.
  4. Iterative Channel Estimation and Turbo Equalization for Multiple-Input Multiple-Output Underwater Acoustic Communications,” Z. Yang and Y. R. Zheng, IEEE J. Oceanic Eng., Vol. 41, No. 1, pp. 232 - 241, Jan. 2016.
  5. Efficient Implementation of an Iterative MIMO-OFDM Receiver Using MMSE Interference Cancelation,” B. Han and Y. R. Zheng, IET Commun., vol. 8, No. 7, pp. 990 – 999, May 2014.
  6. Two-stage List Sphere Decoding for Under-Determined Multiple-Input Multiple-Output Systems,” C. Qian, J. Wu, Y. R. Zheng, and Z. Wang, IEEE Trans. Wireless Commun., vol. 12, No. 12, pp. 6476 - 6487. Dec. 2013.
  7. Joint Frequency-Domain Multiuser Turbo Equalization with Successive Interference Cancellation for Doubly-Selective Fading Channels,” J. Zhang and Y. R. Zheng, Springer J. Wireless Personal Communications, vol. 68, no. 4, pp. 1317-1330, Feb. 2013.
  8. Single-Carrier Frequency-Domain Turbo Equalization without Cyclic Prefix or Zero Padding for Underwater Acoustic Communications,” L. Wang, J. Tao and Y. R. Zheng,  J. Acoustic Society America, vol. 136, no. 6, pp. 3809-3817. Dec. 2012.