Reconstruction From Antenna-Transformed Radar Data Using a Time-Domain Reconstruction Method

2007 ◽  
Vol 45 (3) ◽  
pp. 689-696 ◽  
Author(s):  
Hui Zhou ◽  
Motoyuki Sato ◽  
Takashi Takenaka ◽  
Guofa Li
Keyword(s):  
Time Domain ◽  
Radar Data ◽  
Reconstruction Method

scholarly journals Gaussian Model Adaptive Processing in Time Domain (GMAP-TD) for Weather Radars

2013 ◽  
Vol 30 (11) ◽  
pp. 2571-2584 ◽  
Author(s):  
Cuong M. Nguyen ◽  
V. Chandrasekar
Keyword(s):  
Time Domain ◽  
Gaussian Model ◽  
Radar Data ◽  
Adaptive Processing ◽  
Colorado State University ◽  
Weather Radars ◽  
Ground Clutter ◽  
Moment Estimation ◽  
Interpolation Procedure ◽  
The Time Domain

Abstract The Gaussian model adaptive processing in the time domain (GMAP-TD) method for ground clutter suppression and signal spectral moment estimation for weather radars is presented. The technique transforms the clutter component of a weather radar return signal to noise. Additionally, an interpolation procedure has been developed to recover the portion of weather echoes that overlap clutter. It is shown that GMAP-TD improves the performance over the GMAP algorithm that operates in the frequency domain using both signal simulations and experimental observations. Furthermore, GMAP-TD can be directly extended for use with a staggered pulse repetition time (PRT) waveform. A detailed evaluation of GMAP-TD performance and comparison against the GMAP are done using simulated radar data and observations from the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar using uniform and staggered PRT waveform schemes.

Early-photon guided reconstruction method for time-domain fluorescence lifetime tomography

2016 ◽  
Vol 14 (7) ◽  
pp. 071702-71706 ◽  
Author(s):  
Lin Zhang Lin Zhang ◽  
Chuangjian Cai Chuangjian Cai ◽  
Yanlu Lv Yanlu Lv ◽  
and Jianwen Luo and Jianwen Luo
Keyword(s):  
Fluorescence Lifetime ◽  
Time Domain ◽  
Reconstruction Method

scholarly journals Application of Laplace Domain Waveform Inversion to Cross-Hole Radar Data

2019 ◽  
Vol 11 (16) ◽  
pp. 1839
Author(s):  
Xu Meng ◽  
Sixin Liu ◽  
Yi Xu ◽  
Lei Fu
Keyword(s):  
Time Domain ◽  
Waveform Inversion ◽  
Radar Data ◽  
Dominant Frequency ◽  
Data Set ◽  
Laplace Domain ◽  
Full Waveform ◽  
Highly Nonlinear ◽  
The Time Domain ◽  
Ground Penetrating

Full waveform inversion (FWI) can yield high resolution images and has been applied in Ground Penetrating Radar (GPR) for around 20 years. However, appropriate selection of the initial models is important in FWI because such an inversion is highly nonlinear. The conventional way to obtain the initial models for GPR FWI is ray-based tomogram inversion which suffers from several inherent shortcomings. In this paper, we develop a Laplace domain waveform inversion to obtain initial models for the time domain FWI. The gradient expression of the Laplace domain waveform inversion is deduced via the derivation of a logarithmic object function. Permittivity and conductivity are updated by using the conjugate gradient method. Using synthetic examples, we found that the value of the damping constant in the inversion cannot be too large or too small compared to the dominant frequency of the radar data. The synthetic examples demonstrate that the Laplace domain waveform inversion provide slightly better initial models for the time domain FWI than the ray-based inversion. Finally, we successfully applied the algorithm to one field data set, and the inverted results of the Laplace-based FWI show more details than that of the ray-based FWI.

scholarly journals Adaptive Reconstruction of a Dynamic Force Using Multiscale Wavelet Shape Functions

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Wen-Yu He ◽  
Yang Wang ◽  
Songye Zhu
Keyword(s):  
Time Domain ◽  
Shape Function ◽  
Dynamic Responses ◽  
Dynamic Force ◽  
Reconstruction Method ◽  
Force Response ◽  
Shape Functions ◽  
Reconstruction Accuracy ◽  
Force Reconstruction ◽  
Response Equation

The shape function-based method is one of the very promising time-domain methods for dynamic force reconstruction, because it can significantly reduce the number of unknowns and shorten the reconstruction time. However, it is challenging to determine the optimum time unit length that can balance the tradeoff between reconstruction accuracy and efficiency in advance. To address this challenge, this paper develops an adaptive dynamic force reconstruction method based on multiscale wavelet shape functions and time-domain deconvolution. A concentrated dynamic force is discretized into units in time domain and the local force in each unit is approximated by wavelet scale functions at an initial scale. Subsequently, the whole response matrix is formulated by assembling the responses induced by the wavelet shape function forces of all time units which are calculated by the structural finite element model (FEM). Then, the wavelet shape function-based force-response equation is established for force reconstruction. Finally, the scale of the force-response equation is lifted by refining the wavelet shape function with high-scale wavelets and dynamic responses with more point data to improve the reconstruction accuracy gradually. Numerical examples of different structural types are analyzed to verify the feasibility and effectiveness of the proposed method.

Application of a new 2D time-domain full-waveform inversion scheme to crosshole radar data

Geophysics ◽  
2007 ◽  
Vol 72 (5) ◽  
pp. J53-J64 ◽  
Author(s):  
Jacques R. Ernst ◽  
Alan G. Green ◽  
Hansruedi Maurer ◽  
Klaus Holliger
Keyword(s):  
Time Domain ◽  
Waveform Inversion ◽  
Synthetic Data ◽  
Radar Data ◽  
Data Sets ◽  
Full Waveform Inversion ◽  
Arrival Times ◽  
Full Waveform ◽  
First Arrival ◽  
Radar Wave

Crosshole radar tomography is a useful tool in diverse investigations in geology, hydrogeology, and engineering. Conventional tomograms provided by standard ray-based techniques have limited resolution, primarily because only a fraction of the information contained in the radar data (i.e., the first-arrival times and maximum first-cycle amplitudes) is included in the inversion. To increase the resolution of radar tomograms, we have developed a versatile full-waveform inversion scheme that is based on a finite-difference time-domain solution of Maxwell’s equations. This scheme largely accounts for the 3D nature of radar-wave propagation and includes an efficient method for extracting the source wavelet from the radar data. After demonstrating the potential of the new scheme on two realistic synthetic data sets, we apply it to two crosshole field data sets acquired in very different geologic/hydrogeologic environments. These are the first applications of full-waveform tomography to observed crosshole radar data. The resolution of all full-waveform tomograms is shown to be markedly superior to that of the associated ray tomograms. Small subsurface features a fraction of the dominant radar wavelength and boundaries between distinct geological/hydrological units are sharply imaged in the full-waveform tomograms.

scholarly journals Characterisation of subglacial water using a constrained transdimensional Bayesian Time Domain Electromagnetic Inversion

2019 ◽  
Author(s):  
Siobhan F. Killingbeck ◽  
Adam D. Booth ◽  
Philip W. Livermore ◽  
Charles R. Bates ◽  
Landis J. West
Keyword(s):  
Electrical Resistivity ◽  
Time Domain ◽  
Saline Water ◽  
Radar Data ◽  
High Resistivity ◽  
Fractured Bedrock ◽  
Geological Interpretation ◽  
Seismic Shear ◽  
Time Domain Electromagnetics ◽  
Ground Penetrating

Abstract. Subglacial water influences the dynamics of ice masses. The state of subglacial pore water, whether liquid or frozen, is associated with differences in electrical resistivity that span several orders of magnitude, hence liquid water can be inferred from electrical resistivity depth profiles. Such profiles can be obtained from inversions of time domain electromagnetics (TEM) soundings, but these are often non-unique. Here, we adapt an existing Bayesian transdimensional algorithm (MuLTI) to the inversion of TEM data constrained by independent depth constraints, to provide statistical properties and uncertainty analysis of the resistivity profile with depth. The method was applied to ground-based TEM data acquired on the terminus of the Norwegian glacier Midtdalsbreen, with depth constraints provided by co-located ground penetrating radar data. Our inversion shows that the glacier bed is directly underlain by material of resistivity 102 Ωm ± 100 %, with thickness 5–40 m, in turn underlain by a highly conductive basement (100 Ωm ± 15 %). High resistivity material, 5 × 104 Ωm ± 25 %, exists at the front of the glacier. All uncertainties are defined by the interquartile range of the posterior resistivity distribution. Combining these resistivity profiles with co-located seismic shear-wave velocity inversions to further reduce ambiguity in the hydro-geological interpretation of the subsurface, we propose a new 3D interpretation of the Midtdalsbreen subglacial material partitioned into partially frozen sediment, frozen sediment/permafrost and weathered/fractured bedrock with saline water.

Structural Damage Identification Method Based On Transmissibility in Time Domain

2021 ◽  
Author(s):  
Yunfeng Zou ◽  
Xuandong Lu ◽  
Jinsong Yang ◽  
Xuhui He ◽  
Tiantian Wang
Keyword(s):  
Time Domain ◽  
Structural Damage ◽  
High Efficiency ◽  
Damage Identification ◽  
Identification Accuracy ◽  
Reconstruction Method ◽  
Fe Model ◽  
Time Frequency ◽  
Identification Method ◽  
Structural Damage Identification

Abstract Structural damage identification technology is of great significance to improve the reliability and safety of civil structures and has attracted much attention in the study of structural health monitoring. In this paper, a novelty structural damage identification method based on the transmissibility in time domain is proposed. The method takes the discrepancy of transmissibility of structure response in time domain before and after damage as the basis of finite element model modification. The damage location and damage degree are obtained through iteration by minimizing the difference between the measurements at gauge locations and the reconstruction response extrapolated by FE model. Taking the advantage of the response reconstruction method based on empirical mode decomposition, the damage information is possible to obtain in the absence of prior knowledge on external excitation information. Moreover, this method is carried out in the time domain, without the need to identify the modal parameters and perform time-frequency analysis, which simplicity ensures the high efficiency of damage identification. The effectiveness and accuracy of the proposed method are studied by simulation, including reconstruction error and measurement noise. The identification results demonstrate that the proposed structural damage identification method improves the calculation effectiveness considerably and ensures the identification accuracy.

Sign in / Sign up

Export Citation Format

Share Document