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| Citation: | Ji Guangyu, Dong Yongwei, Bu Yuncheng, Li Yanlei, Zhou Liangjiang, Liang Xingdong. Multi-band SAR Coherent Change Detection Method Based on Coherent Representation Differences of Targets[J]. Journal of Radars, 2018, 7(4): 455-464. doi: 10.12000/JR18020
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Multi-band SAR Coherent Change Detection Method Based on Coherent Representation Differences of Targets
DOI: 10.12000/JR18020
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Abstract
Coherent Change Detection (CCD) detects micro changes in a scene using phase coherence of SAR images before and after a change. It is difficult for conventional CCD method to distinguish low coherence interference region from objective change region because of a single detection scale. Multi-band SAR target detection in a multiscale way develops variable coherent representation according to the diversity of electromagnetic wave penetration, target structure, and change magnitude. In this paper, a multi-band CCD method is proposed. Firstly, the CCD images of every band were acquired; secondly, the detected scene was classified on the basis of coherent representation of targets in each single band using improved Expectation-Maximization (EM) algorithm; thirdly, the objective change class in each single band was selected by a few supervised samples; lastly, multi-band fusion CCD image was acquired by the use of Dempster-Shafer (DS) evidence theory. This multi-band CCD result can eliminate low coherent interference in each single band and decrease false alarm probability. The method is validated by L- and P-band repeat-pass SAR images acquired before and after change. Results and index parameters demonstrate the validity and correctness of the proposed method. -
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References
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- Figure 1. Workflow of proposed multi-band CCD method
- Figure 2. SAR images of each band of scene before and after change to be detected and optical reference image
- Figure 3. CCD images of scene to be detected
- Figure 4. Comparison results between histogram of CCD image and fitting distribution model
- Figure 5. Comparison results between histogram of supervised sample data and fitting distribution model(For the reason of comparing conveniently, the histogram of supervised sample data times a corresponding multiple, so that it can be equal to the probability density of some fitting model part)
- Figure 6. Multi-band CCD result of experiment area
- Figure 7. Index analysis between mono-band CCD and multi-band CCD methods