scholarly journals Three-Dimensional High-Resolution MIMO Radar Imaging via OFDM Modulation and Unitary ESPRIT

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Jingjing Zhao ◽  
Yongxiang Liu ◽  
Kai Huo ◽  
Jiaxi Ye ◽  
Bo Xiao

Imaging and recognition of targets with complex maneuvers bring a new challenge to conventional radar applications. In this paper, the three-dimensional (3D) high-resolution image is attained in real-time by a Multiple-Input-Multiple-Output (MIMO) radar system with single Orthogonal-Frequency-Division-Multiplexing (OFDM) pulse. First, to build the orthogonal transmit waveform set for MIMO transmission, we utilize complex orthogonal designs (CODs) for OFDM subcarrier modulation. Based on the OFDM modulation, a preprocessing method is developed for transmit waveform separation without conventional matched filtering. The result array manifold is the Kronecker product of the steering vectors of subcarrier/transmit antenna/receive antenna uniform linear arrays (ULAs). Then, the high-resolution image of target is attained by the Multidimensional Unitary Estimation of Signal Parameters via Rotational Invariant Techniques (MD-UESPRIT) algorithm. The proposed imaging procedures include the multidimensional spatial smoothing, the unitary transform via backward-forward averaging, and the joint eigenvalue decomposition (JEVD) algorithm for automatically paired coordinates estimation. Simulation tests compare the reconstruction results with the conventional methods and analyze the estimation precision relative to signal-to-noise ratio (SNR), system parameters, and errors.

2012 ◽  
Vol 4 (10) ◽  
pp. 1198-1206 ◽  
Author(s):  
Hiroshi Kamioka ◽  
Yoshitaka Kameo ◽  
Yuichi Imai ◽  
Astrid D. Bakker ◽  
Rommel G. Bacabac ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Jianfang Cao ◽  
Zibang Zhang ◽  
Aidi Zhao

Considering the problems of low resolution and rough details in existing mural images, this paper proposes a superresolution reconstruction algorithm for enhancing artistic mural images, thereby optimizing mural images. The algorithm takes a generative adversarial network (GAN) as the framework. First, a convolutional neural network (CNN) is used to extract image feature information, and then, the features are mapped to the high-resolution image space of the same size as the original image. Finally, the reconstructed high-resolution image is output to complete the design of the generative network. Then, a CNN with deep and residual modules is used for image feature extraction to determine whether the output of the generative network is an authentic, high-resolution mural image. In detail, the depth of the network increases, the residual module is introduced, the batch standardization of the network convolution layer is deleted, and the subpixel convolution is used to realize upsampling. Additionally, a combination of multiple loss functions and staged construction of the network model is adopted to further optimize the mural image. A mural dataset is set up by the current team. Compared with several existing image superresolution algorithms, the peak signal-to-noise ratio (PSNR) of the proposed algorithm increases by an average of 1.2–3.3 dB and the structural similarity (SSIM) increases by 0.04 = 0.13; it is also superior to other algorithms in terms of subjective scoring. The proposed method in this study is effective in the superresolution reconstruction of mural images, which contributes to the further optimization of ancient mural images.


2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Xingxing Li ◽  
Dangwei Wang ◽  
Xiaoyan Ma

Target localization using a frequency diversity multiple-input multiple-output (MIMO) system is one of the hottest research directions in the radar society. In this paper, three-dimensional (3D) target localization is considered for two-dimensional MIMO radar with orthogonal frequency division multiplexing linear frequency modulated (OFDM-LFM) waveforms. To realize joint estimation for range and angle in azimuth and elevation, the range-angle-dependent beam pattern with high range resolution is produced by the OFDM-LFM waveform. Then, the 3D target localization proposal is presented and the corresponding closed-form expressions of Cramér-Rao bound (CRB) are derived. Furthermore, for mitigating the coupling of angle and range and further improving the estimation precision, a CRB optimization method is proposed. Different from the existing methods of FDA-based radar, the proposed method can provide higher range estimation because of multiple transmitted frequency bands. Numerical simulation results are provided to demonstrate the effectiveness of the proposed approach and its improved performance of target localization.


Author(s):  
Robert M. Glaeser

It is well known that a large flux of electrons must pass through a specimen in order to obtain a high resolution image while a smaller particle flux is satisfactory for a low resolution image. The minimum particle flux that is required depends upon the contrast in the image and the signal-to-noise (S/N) ratio at which the data are considered acceptable. For a given S/N associated with statistical fluxtuations, the relationship between contrast and “counting statistics” is s131_eqn1, where C = contrast; r2 is the area of a picture element corresponding to the resolution, r; N is the number of electrons incident per unit area of the specimen; f is the fraction of electrons that contribute to formation of the image, relative to the total number of electrons incident upon the object.


Author(s):  
А.С. Алексеев ◽  
А.А. Никифоров ◽  
А.А. Михайлова ◽  
М.Р. Вагизов

В связи со старением информационных материалов о состоянии лесов существует потребность в разработке новых методов таксации древостоев, основанных на применении последних научно-технических достижений в области теории структуры и продуктивности древостоев, дистанционных методов изучения лесов, информационных и ГИС технологий. В статье приведены результаты разработки и проверки нового метода определения таксационных характеристик сомкнутых насаждений на основе правила 3/2 и подобных ему правил Хильми и Рейнеке, с одной стороны, и определения числа деревьев на единице площади по снимку сверх высокого разрешения, полученного с помощью БПЛА, с другой. С теоретической точки зрения эта зависимости величин запаса, средней высоты и среднего диаметра от числа стволов на единице площади относятся к классу аллометрических связей, очень часто встречающихся при количественном описании соотношений частей биологических систем разных уровней иерархии, от организмов до экосистем. Параметры аллометрических зависимостей запаса, средних высоты и диаметра от числа стволов на единице площади были определены для основных лесообразующих пород по данным таблиц хода роста нормальных (полных) древостоев с теоретическим показателем степени и затем использованы для расчетов. Число деревьев на единице площади определялось по снимку с разрешением 7,13 см/пиксель, полученному с помощью 4-роторной платформы. Обработка материалов аэрофотосъемки была выполнена в специализированной фотограмметрической системе Agisoft Photoscan. В результате были получены ортофотоплан и цифровая модель поверхности крон деревьев на изучаемую территорию с определением их высот. Для автоматизированной обработки полученных изображений с целью получения значений числа деревьев на единицу площади был создан специализированный скрипт на языке Java. Погрешности определения таксационных характеристик древостоев предлагаемым методом не выше установленных действующими нормативными материалами. Every time there is a demand for new innovative methods of forest resources estimation based on last achievements in theoretical science, remote sensing methods, information and GIS-technologies. In the paper are presented a new method and the results of its application to forest stands growing stock, mean height and diameter determination. The method is based on rule 3/2 and similar Reineke and Hilmy rules, on one hand and high resolution image made by unmanned aerial vehicle, which used for determination of number of trees per area unit, on other. The above rules are well known in quantitative biology as an allometric and widely used for description of different kind of relations in biological systems of various scale: from organisms to ecosystems. Parameters of above allometric relationships between growing stock, mean height and diameter and stems density per area unit was determine on the base of full stock growth and yield tables for main tree species and after used for experimental calculations. The number of trees per area unit was determined after special treatment of high resolution image made by unmanned flying machine. The growing stock, mean height and diameter determined by suggested method was compared with the data of regular forest inventory. Comparison gives positive result and method may be recommended for further development.


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