Low Complexity Algorithm for Range-Point Migration-Based Human Body Imaging for Multistatic UWB Radars

High-resolution, short-range sensors that can be applied in optically challenging environments (e.g., in the presence of clouds, fog, and/or dark smog) are in high demand for various applications. Ultrawideband radar is a promising sensor that is suitable for short-range surveillance or watching sensors. Range-point migration (RPM) has been recently established as a promising imaging approach to achieve accurate and real-time 3-D imaging. However, when objects with many scattering points are dealt with, such as a human body, RPM suffers from high computational costs. In this letter, we propose an algorithm with a lower complexity for an RPM-based 3-D imaging method by introducing a sampling-based scattering center extraction with a simplified evaluation function, in which an efficient sample pattern is provided by a golden ratio. The results from a finite-difference time-domain-based numerical test, which introduces a realistic human body object, demonstrate that our proposed method remarkably reduces the computational cost without sacrificing the reconstruction accuracy

Acceleration of Range Points Migration-Based Microwave Imaging for Nondestructive Testing

We report on an experimental investigation of the properties of volume holographic recording in photopolymerizable nanoparticle?polymer composites (NPCs) doped with chain transferring multifunctional di- and tri-thiols as chain transfer agents. It is shown that the incorporation of the multifunctional thiols into NPCs more strongly influences on volume holographic recording than that doped with mono-thiol since more chemical reactions involve in the polymer network formation. It is found that, as similar to the case of mono-thiol doping, there exist optimum concentrations of di- and tri-thiols for maximizing the saturated refractive index modulation. It is also seen that recording sensitivity monotonically decreases with an increase in multifunctional thiol concentration due to the partial inhibition of the photopolymerization event by excessive thiols

Range-Point Migration-Based Image Expansion Method Exploiting Fully Polarimetric Data for UWB Short-Range Radar

Ultrawideband radar with high-range resolution is a promising technology for use in short-range 3-D imaging applications, in which optical cameras are not applicable. One of the most efficient 3-D imaging methods is the range-point migration (RPM) method, which has a definite advantage for the synthetic aperture radar approach in terms of computational burden, high accuracy, and high spatial resolution. However, if an insufficient aperture size or angle is provided, these kinds of methods cannot reconstruct the whole target structure due to the absence of reflection signals from large part of target surface. To expand the 3-D image obtained by RPM, this paper proposes an image expansion method by incorporating the RPM feature and fully polarimetric data-based machine learning approach. Following ellipsoid-based scattering analysis and learning with a neural network, this method expresses the target image as an aggregation of parts of ellipsoids, which significantly expands the original image by the RPM method without sacrificing the reconstruction accuracy. The results of numerical simulation based on 3-D finite-difference time-domain analysis verify the effectiveness of our proposed method, in terms of image-expansion criteria

Super-Resolution Time of Arrival Estimation Using Random Resampling in Compressed Sensing

There is a strong demand for super-resolution time of arrival (TOA) estimation techniques for radar applications that can that can exceed the theoretical limits on range resolution set by frequency bandwidth. One of the most promising solutions is the use of compressed sensing (CS) algorithms, which assume only the sparseness of the target distribution but can achieve super-resolution. To preserve the reconstruction accuracy of CS under highly correlated and noisy conditions, we introduce a random resampling approach to process the received signal and thus reduce the coherent index, where the frequency-domain-based CS algorithm is used as noise reduction preprocessing. Numerical simulations demonstrate that our proposed method can achieve super-resolution TOA estimation performance not possible with conventional CS methods

Parametric Wind Velocity Vector Estimation Method for Single Doppler LIDAR Model

Doppler lidar (LIght Detection And Ranging) can provide accurate wind velocity vector estimates by processing the time delay and Doppler spectrum of received signals. This system is essential for real-time wind monitoring to assist aircraft taking off and landing. Considering the difficulty of calibration and cost, a single Doppler lidar model is more attractive and practical than a multiple lidar model. In general, it is impossible to estimate two or three dimensional wind vectors from a single lidar model without any prior information, because lidar directly observes only a 1-dimensional (radial direction) velocity component of wind. Although the conventional VAD (Velocity Azimuth Display) and VVP (Velocity Volume Processing) methods have been developed for single lidar model, both of them are inaccurate in the presence of local air turbulence. This paper proposes an accurate wind velocity estimation method based on a parametric approach using typical turbulence models such as tornado, micro-burst and gust front. The results from numerical simulation demonstrate that the proposed method remarkably enhances the accuracy for wind velocity estimation in the assumed modeled turbulence cases, compared with that obtained by the VAD or other conventional method

Three-Dimensional Imaging Method Incorporating Range Points Migration and Doppler Velocity Estimation for UWB Millimeter-Wave Radar

High-resolution, short-range sensors that can be applied in optically challenging environments (e.g., in the presence of clouds, fog, and/or dark smog) are in high demand. Ultrawideband (UWB) millimeter-wave radars are one of the most promising devices for the above-mentioned applications. For target recognition using sensors, it is necessary to convert observational data into full 3-D images with both time efficiency and high accuracy. For such conversion algorithm, we have already proposed the range points migration (RPM) method. However, in the existence of multiple separated objects, this method suffers from inaccuracy and high computational cost due to dealing with many observed RPs. To address this issue, this letter introduces Doppler-based RPs clustering into the RPM method. The results from numerical simulations, assuming 140-GHz band millimeter radars, show that the addition of Doppler velocity into the RPM method results in more accurate 3-D images with reducing computational costs

UWB パルス レーダ ノ タメ ノ コウセイノウ リッタイゾウ スイテイホウ

京都大学0048新制・課程博士博士(情報学)甲第13419号情博第281号新制||情||55(附属図書館)UT51-2007-Q820京都大学大学院情報学研究科通信情報システム専攻(主査)教授 佐藤 亨, 教授 松山 隆司, 教授 松田 哲也学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDA

Complex Permittivity Imaging by Incorporating Synthetic Aperture Radar and Inverse Scattering Method for Stratified Ground Medium

This article introduces the incorporationapproach with synthetic aperture radar (SAR) and contrast source inversion (CSI) based nonlinear inverse scattering (NIS) approach for quantitative permittivity imaging for buried object under multilayered heterogeneous ground media. It is challenging issue to retrieve a complex permittivity from ground-penetrating radar (GPR) data, since the NIS problem considerably suffers from inaccuracy due to severe ill-posed condition. To overcome this limitation, this article introduces the SAR image-based region of interest (ROI) limitation in the CSI optimization scheme, where the number of unknowns are massively reduced. Furthermore, the SAR image is also upgraded by the pre-CSI optimization, where the Green's function and background clutter for heterogeneous background (e.g., multilayered medium) are accurately generated. The FDTD-based numerical tests, assuming GPR observation model, show that our proposed scheme effectively reconstructs a dielectric property of buried object, even in severe condition