Abstract
Layover detection has long been the focus of attention for interferometric synthetic aperture radar (InSAR) data processing. As for the existing layover detection methods, most of them are applied to single-baseline scenarios. Since multibaseline InSAR provides more image samples, the performance of layover detection can be further improved. In this article, a joint detection method of layover is proposed on the basis of local frequency and eigenvalue of multibaseline InSAR. To obtain a precise local frequency, maximum likelihood estimation is performed for flattened interferometric phase fusion and removing the reference terrain phase is chosen to ensure the proportionality of flattened phase to the baseline length. Adaptive image selection based on coherence is proposed to obtain a distinct eigenvalue. Then, the joint detection method is elaborated on. Based on the results of local frequency estimation and eigenvalue decomposition, precise thresholds are set for joint detection, and joint judgment is made by combining the layover detected by local frequency, the layover detected by eigenvalue, and the thresholds. Finally, the proposed method is validated through comparative experiments on simulated data and real data. Both theoretical analysis and experimental results show the feasibility and superiority of the proposed method.
Highlights
Synthetic Aperture Radar (SAR) exhibits excellent advantages in topographic mapping, e.g., all-weather, all-day, and the capability to collect topographic information from the areas with poor measurement conditions [1]
Only Chen et al [26] in our research team have conducted study on layover detection of multi-baseline Interferometric Synthetic Aperture Radar (InSAR), but the detection performance of their method is limited because only eigenvalue is used and all available images are used to estimate the eigenvalue without data choosing
Based on the results of local frequency estimation and eigenvalue decomposition of multi-baseline InSAR, the precise thresholds are determined for joint detection
Summary
Synthetic Aperture Radar (SAR) exhibits excellent advantages in topographic mapping, e.g., all-weather, all-day, and the capability to collect topographic information from the areas with poor measurement conditions [1]. Zou et al [25] applied information theory criteria to detect the layover area in spaceborne single-baseline InSAR. Multi-baseline InSAR provides more image samples, further improving the precision of the feature estimation applied for layover detection. Only Chen et al [26] in our research team have conducted study on layover detection of multi-baseline InSAR, but the detection performance of their method is limited because only eigenvalue is used and all available images are used to estimate the eigenvalue without data choosing. A joint detection method is proposed by combining local frequency and eigenvalue of multi-baseline InSAR data. Based on the results of local frequency estimation and eigenvalue decomposition of multi-baseline InSAR, the precise thresholds are determined for joint detection.
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