Statistically homogeneous pixel selection for small SAR data sets based on the similarity test of the covariance matrix

Song, Huina; Sun, Yingfei; Murphy, Robert W.; Zhang, Bowen; Li, Ning; Wang, Yingjie; Fei, Wenbo

doi:10.1080/2150704x.2017.1335907

Cited by 7 publications

(4 citation statements)

References 18 publications

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“…Due to the so called clutter diversity, the inference task becomes challenging since the statistical properties of the disturbance can change among the different nodes and polarizations [13]- [25]. In this respect, in [25] a statistical analysis of multistatic/polarimetric sea-clutter returns collected via the Netted RADar (NetRAD) system highlighted that, over an appropriate time interval (referred to as the coherence time), the sea-clutter returns collected from both monostatic and bistatic sensors can be modelled according to a Spherically Invariant Random Process (SIRP) [26]- [33]. This is tantamount to describing the clutter backscattering over the coherence time as the product of a nonnegative random variable and a zeromean circularly symmetric Gaussian process with unknown spectral characteristics, referred to as texture and speckle, respectively.…”

Section: Introductionmentioning

confidence: 99%

Testing Stationarity and Statistical Independence of Multistatic/Polarimetric Sea-Clutter With Application to NetRAD Data

Aubry,

Carotenuto,

De Maio

et al. 2024

IEEE Trans. Geosci. Remote Sensing

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The design of bespoke adaptive detection schemes relying on the joint use of multistatic/polarimetric measurements requires a preliminary statistical inference on the clutter interference environment. This is of paramount importance to develop an analytic model for the received signal samples, which is mandatory for the synthesis of radar detectors. In this respect, the aim of this paper is the development of suitable learning tools to study some important statistical features of the sea-clutter environment perceived at the nodes of a multistatic/polarimetric radar system. Precisely, stationarity of the data in the slow-time domain is first assessed resorting to Generalized Inner Product (GIP) based statistics. Then, the possible presence of structural symmetries in the clutter covariance matrices is investigated. Finally, relationships between some statistical parameters characterizing the sea-clutter returns on the bistatic polarimetric channels are explored via a specific sequential hypothesis testing. This research activity is complemented by the use of radar returns measured via the Netted RADar (NetRAD), which collects simultaneously monostatic and bistatic polarimetric measurements. The results indicate that the analyzed data can be modeled as drawn from a stationary Gaussian process within the coherence time. Additionally, the bistatic returns on the different polarimetric channels can be assumed statistically independent with speckle components possibly exhibiting proportional/equal covariance matrices depending on the transmit/receive polarization and bistatic geometry.

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Section: Introductionmentioning

confidence: 99%

Testing Stationarity and Statistical Independence of Multistatic/Polarimetric Sea-Clutter With Application to NetRAD Data

Aubry,

Carotenuto,

De Maio

et al. 2024

IEEE Trans. Geosci. Remote Sensing

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“…Many scholars have done a series of related research on the extraction of SHP [26][27][28][29]. Parizzi et al [30] compared and analyzed the Kullback-Leibler divergence, the KS test, the Anderson-Darling (AD) test and generalized likelihood ratio test (GLRT).…”

Section: Introductionmentioning

confidence: 99%

An Improved Method for Phase Triangulation Algorithm Based on the Coherence Matrix Eigen-Decomposition in Time-Series SAR Interferometry

He²,

Zhuang

et al. 2021

IEEE Access

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Time-series SAR interferometry, which combines permanent scatterers (PSs) and distributed scatterers (DSs), has been strongly developed in recent years. Unlike PS, DS corresponds to a natural target whose neighboring pixels share similar reflectivity values. The selection of DS is relevant to the goodnessof-fit value, the estimation of which is based on all possible combined interferometric phases and fails to avoid the adverse effect of low-quality phases. This paper used eigen-decomposition of coherence matrix that constructed based on the identified homogeneous pixels to perform phase optimization, and then only the interferometric phases with low noise and clear fringes are utilized to measure the goodness-of-fit. 30 Sentinel-1A images were applied to test the improved method of land subsidence monitoring in Beijing, China. The deformation results of different methods were cross verified and the area statistics of the study area were carried out. The results show that the maximum subsidence monitored by the improved method is located in Jinzhan Town with a maximum rate of -109 mm/yr. This improved method extracts more measurement points with accuracy ensured, which is proved to be an effective way to provide the high spatial density of deformation measurements. The land subsidence in this area is mainly caused by the excessive exploitation of groundwater resources. This research provides support for the prevention and control work of relevant departments.

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“…Successful application of DS requires statistically homogeneous pixel (SHP) identification and phase optimization. Existing methods for SHP identification employ the two-sample Kolmogorov-Smirnov (KS) test [15], mean amplitude and mean amplitude difference [16], polarimetry information [17], confidence interval based on the central limit theorem [18], one-sample test [19], similarity test of the covariance matrix [20], geometric distance and target features [21], various amplitude statistics [22], and nonlocal filters [23], [24]. Most of these methods can effectively solve the problem of SHP identification although they differ in terms of their efficiency and robustness.…”

Section: Introductionmentioning

confidence: 99%

Underground Coal Fires Identification and Monitoring Using Time-Series InSAR With Persistent and Distributed Scatterers: A Case Study of Miquan Coal Fire Zone in Xinjiang, China

Liu

Wang

et al. 2019

IEEE Access

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The Xinjiang is an important coal production base in China and also a serious coal fire disaster area. Coal fires not only waste resources, but also cause air pollution and damage to the ecological environment. Hence, it is very important to identify and monitor the underground coal fire areas accurately and efficiently for the control of coal fires. Interferometric synthetic aperture radar (InSAR) technology identifies and monitors coal fire areas by monitoring surface subsidence caused by burned out area. Compared with traditional coal fire monitoring technology, InSAR technology has the advantages of allweather and high efficiency. But the fire areas are often distributed in wild areas, this factor significantly limits the application of the traditional Persistent Scatterer interferometry (PSI) technology. In addition, Xinjiang coal fires are mostly located in historical goafs, so it is necessary to distinguish the subsidence caused by mining and coal fires. Therefore, distributed scatterer interferometry (DSI) technology is used to monitor the Miquan fire area in Xinjiang in this paper. The results show that compared with PSI technology, DSI technology can expand the number of effective monitoring points 124 times. On this basis, spatiotemporal analysis of surface subsidence in the study area suggests that the subsidence caused by mining and coal fires exhibits significantly different space-time evolution rules. Therefore, in the future, the coal fire area and mining area can be separated and identified according to these rules. The final identified coal fire area contains all measured coal fire points, and accurately monitors the fire extinguishing area. INDEX TERMS Coal fire monitoring, subsidence information, InSAR, spatio-temporal analysis.

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Statistically homogeneous pixel selection for small SAR data sets based on the similarity test of the covariance matrix

Cited by 7 publications

References 18 publications

Testing Stationarity and Statistical Independence of Multistatic/Polarimetric Sea-Clutter With Application to NetRAD Data

Testing Stationarity and Statistical Independence of Multistatic/Polarimetric Sea-Clutter With Application to NetRAD Data

An Improved Method for Phase Triangulation Algorithm Based on the Coherence Matrix Eigen-Decomposition in Time-Series SAR Interferometry

Underground Coal Fires Identification and Monitoring Using Time-Series InSAR With Persistent and Distributed Scatterers: A Case Study of Miquan Coal Fire Zone in Xinjiang, China

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