GB-SARによる変位計測とイメージングのための新しく効率的な技術に関する研究

要約のみTohoku University佐藤源之課

On the use of lateral wave for the interlayer debonding detecting in an asphalt airport pavement using a multistatic GPR system

In this paper, we focus on the detection of the interlayer debonding of the asphalt airport pavement by the Ground-penetrating Radar (GPR) system. Since the interlayer debonding usually occurs in the shallow region of the asphalt airport pavement (several centimeters), it is difficult to interpret the anomalies or the defects from the GPR signals composed of many waves under the boundary conditions. Moreover, the wavelength of the ordinary GPR system is over several centimeters. Therefore, the spatial resolution of the system is not accurate enough to consider the millimeter thickness of the debonding layer. To overcome these problems, we propose a new method based on evaluating the lateral wave behavior of common midpoint (CMP) gathers collected by a multiple static GPR system. The multi-static GPR system is a stepped frequency continuous wave (SFCW) radar system, which consists of 8 transmitting and 8 receiving bowtie antennas. The system operates in the frequency range from 50 MHz to 1.5 GHz. After the validation of the simulation, the results of the interlayer debonding detection were evaluated by a field experiment obtained at Tokyo International Airport. The proposed method can detect the debonding layers which are less than 1mm. Also, it is shown that our proposed method has a high consistency with the conventional acoustic finding method in the field measurement. It provides an innovative and effective method for the interlayer debonding detection of a partially damaged airport asphalt pavement, which is difficult to be observed by the ordinary GPR signals

Iterative atmospheric phase screen compensation for near-real-time ground-based InSAR measurements over a mountainous slope

In this article, an atmospheric phase screen (APS) compensation algorithm for a near real-time ground-based interferometry synthetic aperture radar (GB-InSAR) over a mountainous area is investigated. A novel APS compensation scheme is proposed to compensate the fluctuated APS caused by a spatial 3-D inhomogeneous refractivity index distribution without any a priori knowledge of moving location. The proposed method simultaneously addresses to identify moving pixels by a criterion of absolute velocity estimated by the coherent pixels technique (CPT). The proposed method consists mainly of three steps: 1) the stratified APS compensation; 2) identification of moving pixel candidate; and 3) the residual APS [remained APS after 1)] compensation by Kriging interpolation. The steps mentioned above are iteratively applied in order to increase the accuracy of the whole process. In this framework, we develop the 2-D quadratic polynomial model of the refractivity index with respect to slant range and topographic height for modeling the stratified APS. Furthermore, a prediction of the residual APS is achieved by applying the intrinsic random function of order k (IRF-k) Kriging interpolation, taking into account the nonstationarity of the residual APS. We evaluate the proposed method using zero-baseline GB-differential InSAR (GB-DInSAR) data over a mountainous area located in Minami-Aso, Kumamoto, Japan, through the near real-time post-landslide measurement campaign

An efficient and accurate GB-SAR imaging algorithm based on the fractional Fourier transform

In this paper, an efficient and accurate imaging algorithm is presented for Ground-Based Synthetic Aperture Radar (GB-SAR) or other radar systems that could be formed by a physical or synthetic linear aperture. The imaging algorithm is based on the fractional Fourier transform for the azimuth compression. A mathematical framework is derived according to the projection of a sample reflectivity image onto the pseudopolar coordinate and its implementation was presented. With the data acquisition geometry and the pseudopolar imaging coordinate, the phase of a point target can be expressed as a quadratic phase exponential. It makes that only one-dimensional fractional Fourier transform is needed for the azimuth compression of the time domain backscatter data for the GB-SAR imaging problem. By further research, the optimal transformation order which represents the spatial frequency changes by the fractional Fourier transform was given subsequently. Taking advantage of this optimal representation, the proposed approach avoids the large calculation that occurs in the time domain back projection (TDBP). Comparing to the far-field pseudopolar format algorithm (FPFA), the accuracy of the proposed algorithm is much improved. Meanwhile, the proposed approach holds the almost same computational cost and complexity as the FPFA. The proposed approach keeps the advantages of the imaging quality of the TDBP and the computational cost of the FPFA that are two important aspects of the GB-SAR applications. Both the numerical simulation and the field GB-SAR experiment show that the algorithm is more suitable for the high precision GBSAR imaging, especially for the near-field

Advanced bridge monitoring strategies by polarimetric GB-SAR

Use of advanced health monitoring strategies for bridges is essential to provide a comprehensive condition assessment of these structures and ensure their structural integrity. To this purpose, new technologies have been applied in recent years for both static and dynamic assessments offering unprecedented opportunities within the context of risk management and structural analysis. Among these, areal deformation measurement techniques from ground-based synthetic aperture radar (GB-SAR) sensors were successfully applied for continuous monitoring of dynamic and static displacements of bridges [1] [2]. However, a main limitation for the ground-based microwave interferometry is that, as a linear measurement technique, it is difficult to pinpoint the damage location and obtain accurate displacement time-series for bridges [3]. Moreover, it is known that vertical displacements are usually more relevant than horizontal displacements in the dynamic monitoring of bridges, and the GB-SAR interferometry can only provide the line-of-sight (LOS) displacement of the monitored bridge [4]. In this research, we focus on remote monitoring of the dynamic displacement responses of bridges with a polarimetric GB-SAR system. To this purpose, various strategies were used to overcome the existing limitations of this technique. Results from the monitoring of a long-span metallic railway bridge and a reinforced concrete Shinkansen bridge are discussed. The aim of this research is to provide more comprehensive and accurate information for bridge health monitoring using a polarimetric sensor. To this extent, a polarimetric analysis was performed to identify the reflection from the side surface of the bridges. In addition, the information about the polarisation orientation angle and the local incidence angle were processed under the acquisition geometry to calculate the radar look angle. Therefore, the bridge deformation fields in the vertical direction were easily converted using the slant range distances and the corresponding maximum transient vertical deformation was transformed through the LOS deformation while a train passing the bridge

Tree monitoring using ground penetrating radar: two case studies using reverse-time migration

Non-destructive testing (NDT) for health monitoring of trees is a suitable candidate for detecting signs of early decay [1]. Recent developments [2,3,4] have highlighted that ground-penetrating radar (GPR) has the potential to provide with a robust and accurate detection tool with minimum computational and operational requirements in the field. In particular, a processing framework is suggested in [2] that can effectively remove ringing noise and unwanted clutter. Subsequently, an arc length parameterisation is employed in order to utilise a wheel-measurement device to accurately position the measured traces. Lastly, two migration schemes; Kirchhoff and reversetime migration, are successfully applied on numerical and laboratory data in [3]. In the current paper, the detection scheme described in [2,3] using reverse-time migration is tested in two case studies that involve diseased urban trees within the greater London area, UK (Kensington and Gunnersbury park). Both of the trees were cut down after the completion of the measurements and furthermore cut into several slices to get direct information with regards to their internal structure. The processing scheme described in [3,4] managed to adequately detect the internal decay present in both trees. The aforementioned case studies provide coherent evidences to support the premise that GPR is capable of detecting decay in diseased trunks and therefore has the potential to become an accurate and efficient diagnostic tool against emerging infectious diseases of trees

Reverse-Time Migration for Evaluating the Internal Structure of Tree-Trunks Using Ground-Penetrating Radar

The authors would like to express their sincere thanks and gratitude to the following trusts, charities, organizations and individuals for their generosity in supporting this project: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook, Sir Henry Keswick, Ian Bond, P. F. Charitable Trust, Prospect Investment Management Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation and The Wyfold Charitable Trust. This paper is dedicated to the memory of Jonathon West, a friend, a colleague, a forester, a conservationist and an environmentalist who died following an accident in the woodland that he loved.Peer reviewedPostprin

An enhanced data processing framework for mapping tree root systems using ground penetrating radar

The preservation of natural assets is nowadays an essential commitment. In this regard, root systems are endangered by fungal diseases which can undermine the health and stability of trees. Within this framework, Ground Penetrating Radar (GPR) is emerging as a reliable non-destructive method for root investigation. A coherent GPR-based root-detection framework is presented in this paper. The proposed methodology is a multi-stage data analysis system that is applied to semi-circular measurements collected around the investigated tree. In the first step, the raw data are processed by applying several standard and advanced signal processing techniques, to reduce noise-related information. In the second stage, the presence of any discontinuity element within the survey area is investigated by analysing the signal reflectivity. Then, a tracking algorithm aimed at identifying patterns compatible with tree roots is implemented. Finally, the mass density of roots is estimated by means of continuous functions, to achieve a more realistic representation of the root paths and to identify their length in a continuous and more realistic domain. The method was validated in a case study in London (UK), where the root system of a real tree was surveyed using GPR and a soil test pit was excavated for validation purposes. Results support the feasibility of the data processing framework implemented in this study

Mapping and assessment of tree roots using ground penetrating radar with low-cost GPS

In this paper, we have presented a methodology combining ground penetrating radar (GPR) and a low-cost GPS receiver for three-dimensional detection of tree roots. This research aims to provide an effective and affordable testing tool to assess the root system of a number of trees. For this purpose, a low-cost GPS receiver was used, which recorded the approximate position of each GPR track, collected with a 500 MHz RAMAC shielded antenna. A dedicated post-processing methodology based on the precise position of the satellite data, satellite clock offsets data, and a local reference Global Navigation Satellite System (GNSS) Earth Observation Network System (GEONET) Station close to the survey site was developed. Firstly, the positioning information of local GEONET stations was used to filter out the errors caused by satellite position error, satellite clock offset, and ionosphere. In addition, the advanced Kalman filter was designed to minimise receiver offset and the multipath error, in order to obtain a high precision position of each GPR track. Kirchhoff migration considering near-field effect was used to identify the three-dimensional distribution of the root. In a later stage, a novel processing scheme was used to detect and clearly map the coarse roots of the investigated tree. A successful case study is proposed, which supports the following premise: the current scheme is an affordable and accurate mapping method of the root system architecture

Tree trunk inspections using a polarimetric GPR system

In this work, a novel signal processing framework for polarimetric GPR measurements is presented for inspection of tree trunks decay. The framework combines a polarimetric noise filter and an arc-shaped diffraction imaging algorithm. The polarimetric noise filter can increase the signal-to-noise ratio (SNR) of B-scans caused by the bark and the high-loss propriety of the tree trunk based on a 3D Pauli feature vector of the Bragg scattering theory. The arc-shaped diffraction stacking and an imaging aperture are then designed to suppress the effects of the irregular shape of the tree trunk on the signal. The proposed detection scheme is successfully validated with real tree trunk measurements. The viability of the proposed processing framework is demonstrated by the high consistency between the results and the real-truth trunk cross-sections