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<title cf:type="text"><![CDATA[Editorial department of the Journal of National University of Defense Technology -->电子科学与技术·信息与通信工程]]></title>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Deception jamming optimization strategy against adaptive filtering for netted radar]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202011]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[Aiming at the fact that the adaptive filtering is used to estimate the target state in the netted radar system when the tracking target is maneuvering, a deception jamming optimization strategy was proposed on the basis of the netted radar with the plot fusion data processing structure. The model of the target tracked by the netted radar was described according to the state and measurement equation, the adaptive filtering model of tracking maneuvering target was established at the same time. Based on all this, a deception jamming model was established, and the influence relationship of false target deception jamming against the adaptive filtering state estimation error covariance of the netted radar fusion center was derived under the constraint of target maneuver detection. The trace of the error covariance matrix was used to quantify the effect of deception jamming and stand for the objective function of optimization. The Schur complement theory of matrix was used to change the constraints to a linear matrix inequality, and a deception jamming optimization strategy was changed in the solution to the convex optimization problem for semidefinite programming. The simulation results verify the effectiveness of the proposed deception jamming optimization strategy.]]></description>
<pubDate>2022/4/1 11:52:57</pubDate>
<category><![CDATA[电子科学与技术·信息与通信工程]]></category>
<author><![CDATA[WANG Buhong, HUANG Tianqi, TIAN Jiwei]]></author>
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<atom:name>WANG Buhong, HUANG Tianqi, TIAN Jiwei</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202011]]></guid><cfi:id>6</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Research on influencing factors of thyristor expansion speed in pulse condition]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202012]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[In order to study the influence of different factors on the current expansion speed of the thyristor during the turn-on process of the pulse condition, the equivalent circuit model of the pulse forming network based on the structural characteristics and working principle of the thyristor was established, and the simulation was carried out. Numerical simulation results show that if the forward blocking voltage increases from 3 000 V to 5 000 V, the spreading speed will increase by 24.6%. If the base width increases from 500 μm to 900 μm, the spreading speed will decrease by 31.7%. If the carrier lifetime increases from 1 μs to 10 μs, the spreading speed will increase by 56.9%. While the temperature increases from 300 K to 330 K, the spreading speed only increases by 0.3%. It can be seen that the temperature has little effect on the propagation speed. The research results are helpful to select appropriate parameters to ensure the expansion speed required for opening, and have application value for improving the design of thyristor devices and improving the performance of thyristors.]]></description>
<pubDate>2022/4/1 11:52:57</pubDate>
<category><![CDATA[电子科学与技术·信息与通信工程]]></category>
<author><![CDATA[ZHANG Xiao, ZHANG Guanxiang, LU Junyong, DAI Yufeng, WU Wenxuan]]></author>
<atom:author xmlns:atom="http://www.w3.org/2005/Atom">
<atom:name>ZHANG Xiao, ZHANG Guanxiang, LU Junyong, DAI Yufeng, WU Wenxuan</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202012]]></guid><cfi:id>5</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Effect of transmitting nonideal quadrature signal on frequency diversity array beamform]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202013]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[To analyze the impact of transmitting nonideal quadrature signal on FDA (frequency diversity array) beamform, based on the signal model of FDA, the orthogonality issue of baseband signal was brought out, the beamform expression was deduced mathematically under the condition that FDA system transmitting nonideal orthogonal baseband signal, and the performance of matched reception processing was further analyzed. Based on the calculation amount of beamform transmission and matched reception of FDA system, the influencing factors were extracted, and a quantitative analysis of the relationship between the orthogonal characteristics of the baseband signals and the performance of the beamform and matched reception was constructed. Based on the numerical simulation of six kinds of typical random distribution biphasic coded baseband signals, the correctness of theoretical analysis was verified by experiments. Different random distributions show different baseband signal orthogonal characteristics, and their influence on the performance of FDA beamform transmission and matching reception varies with the orthogonal characteristics. From the perspective of orthogonality, the application potential of baseband signal based on Normal, Uniform and Logistic random distribution is better.]]></description>
<pubDate>2022/4/1 11:52:57</pubDate>
<category><![CDATA[电子科学与技术·信息与通信工程]]></category>
<author><![CDATA[YANG Jin, FU Yaowen, YANG Wei]]></author>
<atom:author xmlns:atom="http://www.w3.org/2005/Atom">
<atom:name>YANG Jin, FU Yaowen, YANG Wei</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202013]]></guid><cfi:id>4</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Low probability of intercept radar signal recognition based on multi-window spectrogram analysis]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202014]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[In the current complex battlefield environment, low probability of intercept radar signal has been widely used due to their large time-bandwidth product, strong anti-jamming performance, high resolution and low interception. It is difficult to identify the low probability of intercept radar signal by traditional radar reconnaissance methods. Based on the analysis of typical modulation of low probability of intercept radar, a radar signal classification and recognition method based on artificial intelligence was studied. Starting from the time-frequency characteristics of low probability of intercepted radar signals, a multi-window spectrogram analysis method was proposed. In this algorithm, Hermite function was used as the window function of spectrum analysis, and multiple window functions were also used for spectrum analysis. The effective signal with better aggregation is obtained, the noise interference is dispersed, and the time-frequency analysis characteristics of signal modulation characteristics are more obvious through this algorithm. On the basis of multi-window spectrogram, the idea of transfer learning was adopted, and ImageNet-VGG-f neural network was used to complete the task of signal classification and recognition. Experimental results show that the performance of the proposed algorithm is better than the traditional Choi-William distribution and Smooth and Pseudo Wigner-Ville distribution methods at low signal-to-noise ratio.]]></description>
<pubDate>2022/4/1 11:52:58</pubDate>
<category><![CDATA[电子科学与技术·信息与通信工程]]></category>
<author><![CDATA[LIU Lutao, CHEN Linjun, LI Pin]]></author>
<atom:author xmlns:atom="http://www.w3.org/2005/Atom">
<atom:name>LIU Lutao, CHEN Linjun, LI Pin</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202014]]></guid><cfi:id>3</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Nano millimeter wave radar for bridge cable tension measurement]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202015]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[After the detailed analysis of the diffusion characters of bridge cables, the principle of vibrating frequency-based cable tension estimation, and the principle of interferometric deformation measuring radar, a nano 77 GHz MMW (millimeter wave) radar was developed. A set of key parameters were achieved to control the maximum range, the deformation estimation precision, and the dynamic deformation measuring performance. Field experiments were conducted to compare the performances of the MMW radar with the 24 GHz K band radar. Results show that the new radar is a compact, light-weighted, low-power consumption,and the radar is of great value in cable tension measuring applications.]]></description>
<pubDate>2022/4/1 11:52:58</pubDate>
<category><![CDATA[电子科学与技术·信息与通信工程]]></category>
<author><![CDATA[WANG Jian, WANG Xiang, ZHOU Zhimin]]></author>
<atom:author xmlns:atom="http://www.w3.org/2005/Atom">
<atom:name>WANG Jian, WANG Xiang, ZHOU Zhimin</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202015]]></guid><cfi:id>2</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Tree species classification of airborne LiDAR data based on 3D deep learning]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202016]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[Aimed at the problem that the traditional tree species classification method based on LiDAR (light detection and ranging) data is difficult to directly and comprehensively use the 3D structure information of the point cloud, a tree species classification method of airborne LiDAR data based on 3D deep learning was proposed. This method directly abstracts high-dimensional features from 3D data without converting point clouds into voxels or two-dimensional images. Taking the airborne LiDAR data of white birch and larch in Saihanba National Forest Park as the research object, data filtering was performed to remove noise and ground points; the point cloud distance and improved watershed segmentation method were used to extract the individual wood and make a data set. Finally, a deep neural network composed of a weight-sharing multi-layer perceptron, a max pooling, a fully connected layer and a softmax classifier was established, which can extract the high-dimensional features of trees automatically and realize tree species classification. The experimental results show that the overall classification accuracy rate is 86.7%, the kappa coefficient is 0.73, the optimal feature dimension is 1 024, and the most advantageous point density is 2 048. Compared with the method projecting individual tree point cloud to a two-dimensional view, this algorithm provides higher classification accuracy, and can reduce the calculation cost effectively and improve work efficiency.]]></description>
<pubDate>2022/4/1 11:52:58</pubDate>
<category><![CDATA[电子科学与技术·信息与通信工程]]></category>
<author><![CDATA[LIU Maohua, HAN Ziwei, CHEN Yiming, LIU Zhengjun, HAN Yanshun]]></author>
<atom:author xmlns:atom="http://www.w3.org/2005/Atom">
<atom:name>LIU Maohua, HAN Ziwei, CHEN Yiming, LIU Zhengjun, HAN Yanshun</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202202016]]></guid><cfi:id>1</cfi:id><cfi:read>true</cfi:read></item>
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