Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (1): 1-8.doi: 10.23919/JSEE.2023.000001

• REMOTE SENSING •     Next Articles

Coherent change detection of fine traces based on multi-angle SAR observations

Xiuli KOU1,2(), Guanyong WANG2(), Jun LI2,*(), Jie CHEN1()   

  1. 1 School of Electronics and Information Engineering, Beihang University, Beijing 100191, China
    2 Beijing Institute of Radio Measurement, Beijing 100854, China
  • Received:2022-06-26 Accepted:2022-10-31 Online:2023-02-18 Published:2023-03-03
  • Contact: Jun LI;;;
  • About author:
    KOU Xiuli was born in 1986. She received her B.S. and M.S. degrees from Xidian University in 2009 and 2011 respectively. She is currently working toward her Ph.D. degree in signal and information processing in Beihang University, China. She is a senior engineer in Beijing Institute of Radio Measurement. Her research interests are synthetic apterture radar change detection and image interpretation. E-mail:

    WANG Guanyong was born in 1989. He received his B.S. degree from Tianjin University in 2011, and M.S. and Ph.D. degrees in 2014 and 2018 respectively from the Defense Technology Academy of China Aerospace Science and Industry Corporation. He is a senior engineer in Beijing Institute of Radio Measurement. His research interests are high band synthetic aperture radar (SAR) imaging and high precision motion compensation technology such as millimeter wave SAR signal processing. E-mail:

    LI Jun was born in 1982. He received his B.S. and Ph.D. degrees in electrical engineering from Xidian University, Xi ’an, China, in 2006 and 2011, respectively. He is a researcher with the Beijing Institute of Radio Measurement, Beijing, China. His research interests include radar system design, SAR/ISAR radar imaging and motion compensation. E-mail:

    CHEN Jie was born in 1973. He received his B.S. and Ph.D. degrees in information and communication engineering from Beihang University, Beijing, China, in 1996 and 2002, respectively. From 2004 to 2010, he has been an associate professor with the School of Electronics and Information Engineering, Beihang University. He was a visiting researcher with the School of Mathematics and Statistics, University of Sheffield, Sheffield, U.K., from 2009 to 2010, working on ionospheric effects on low-frequency space radars that measure forest biomass and ionospheric electron densities. Since July 2011, he has been a professor with the School of Electronics and Information Engineering, Beihang University. His research interests include multimodal remote sensing data fusion, high-resolution spaceborne synthetic aperture radar (SAR) image formation, and SAR image quality enhancement. E-mail:


Coherent change detection (CCD) is an effective method to detect subtle scene changes that occur between temporal synthetic aperture radar (SAR) observations. Most coherence estimators are obtained from a Hermitian product based on local statistics. Increasing the number of samples in the local window can improve the estimation bias, but cause the loss of the estimated images spatial resolution. The limitations of these estimators lead to unclear contour of the disturbed region, and even the omission of fine change targets. In this paper, a CCD approach is proposed to detect fine scene changes from multi-temporal and multi-angle SAR image pairs. Multi-angle CCD estimator can improve the contrast between the change target and the background clutter by jointly accumulating single-angle alternative estimator results without further loss of image resolution. The sensitivity of detection performance to image quantity and angle interval is analyzed. Theoretical analysis and experimental results verify the performance of the proposed algorithm.

Key words: coherent change detection (CCD), multi-angle, synthetic aperture radar (SAR)