Multibaseline InSAR Layover Detection Based on Local Frequency and Eigenvalue

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 multi-baseline InSAR provides more image samples, the performance of layover detection can be further improved. In this paper, a joint detection method of layover is proposed on the basis of local frequency and eigenvalue of multi-baseline 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.

A Method for Selecting SAR Interferometric Pairs Based on Coherence Spectral Clustering

“…With the use of the proposed method, the adjacency matrix is constructed first. The combined local frequency and eigenvalue method proposed in [3] is used to detect layover and shadow areas. The strategy proposed in [34] is adopted for detecting water body areas.…”

“…Eigenvalue decomposition is performed of the coherence matrix of each representative pixel. The number of principal eigenvalues is estimated by the eigenvalue threshold method [3]. Fig.…”

“…They provide more samples for interferometric phase estimation, thus facilitating estimation accuracy enhancement. Therefore, the Multi-Channel InSAR (MCInSAR) [3], [4] and Multi-Temporal InSAR (MTInSAR) [5], [6] techniques have recently received widespread attention.…”

“…DEM data than the traditional single-channel InSAR technique, while in the MTInSAR technique, multiple interferometric pairs at different times are utilized to estimate the ground displacement time series [8], [9]. Usually, two SAR SLC images with coherence greater than a certain threshold are considered sufficiently coherent and can be used for interferometry [3]. In this paper, interferometric pairs with a coherence value greater than 0.55 are considered highcoherence interferometric pairs.…”