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A new polarimetric phase optimization method based on eigenvalue decomposition and adaptive filtering

  • role： First author第一作者
  • Affiliation：

    School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China

  • Email：729575242@qq.com
  • Introduction：姜修成，研究方向为合成孔径雷达干涉测量算法研究及其应用。E-mail： 729575242@qq.com
JIANG Xiucheng,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China

  • Email：zhangzj@cug.edu.cn
  • Introduction：张正加，研究方向为合成孔径雷达干涉测量算法研究及在地面沉降、地质灾害和青藏高原冻土环境监测中的应用。E-mail： zhangzj@cug.edu.cn
ZHANG Zhengjia*,  
  • Affiliation：

    School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China

WANG Mengmeng,  
  • Affiliation：

    School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China

LIU Xiuguo,  
  • Affiliation：

    School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China

CHEN Qihao

résumé

The time-series interferometric synthetic aperture radar (InSAR) technology based on distributed scatterers (DSs) makes up for the drawback of the persistent scatterer InSAR technology, which struggles to obtain a sufficient number of deformation monitoring points in low-coherence regions. Given that DS targets are easily affected by temporal and spatial decorrelation factors, leading to the introduction of speckle noise, the phase of DS targets must be optimized. In this paper, a new polarimetric phase optimization method based on eigenvalue decomposition and adaptive filtering (EVD-FPO) is proposed to address these limitations. This method uses Sentinel-1A dual-polarization data amplitude information to identify DS and PS targets and uses eigenvalue decomposition polarimetric phase optimization technology based on the temporal and spatial coherence matrix and adaptive mean filtering technology to improve the phase quality. To prove the feasibility and effectiveness of the proposed method, 17 Sentinel-1A dual-polarization (VV-VH) SAR images are used to evaluate its performance. Experimental results show that the proposed EVD-FPO method can effectively increase the density of coherent target points and improve the phase quality. Compared with the single polarimetric amplitude dispersion method (VV-DA) and amplitude dispersion polarimetric phase optimization method (ESM-DA), EVD-FPO increases the coherence point target by 9.06 and 1.64 times, respectively. Compared with the single-polarization CAESAR method, the PSs extracted are more complete. EVD-FPO can suppress the phase noise of the DSs while protecting the phase of the PSs, and the phase quality is better than those of the ESM-DA and CAESAR methods. To evaluate the optimized phase results, this paper adopts the average phase derivative to evaluate the phase quality of each phase optimization method. As for the global average phase derivative, the variation of phase derivative of the ESM-DA method is 1.22, that of the CAESAR method is 0.998, and that of the EVD-FPO method is 0.974. These values indicate that the interferometric phase quality of EVD-FPO is higher than those of the other two methods. Similar conclusions are obtained for the average phase derivative at the coherence points. The variation of the phase derivative of the ESM-DA method is 1.184, that of the CAESAR method is 0.854, and that of EVD-FPO method is 0.810, which also indicates that the interferometric phase quality of EVD-FPO is higher than those of the two former methods. In addition, the effect of physical scattering mechanism of Sentinel-1 dual-polarization data on improving phase quality is investigated. Results show that the phase contribution of PS targets is mainly from VV polarization, while the phase contribution of DS targets is mainly from VH polarization. In general, the EVD-FPO method proposed in this paper is very meaningful for improving the density and phase quality of coherence points. It holds great potential for deformation monitoring in low-coherence areas where artificial targets are scarce.

mots-clés

remote sensing;polarimetric phase optimization;eigenvalue decomposition;adaptive filtering;coherence points;InSAR

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