Table of Content

20 June 2016 Volume 43 Issue 3

  

Blind equalization method for OFDM systems in non-cooperative communication

LIU Mingqian;CHEN Jian;LI Bingbing;GUO Xiaoling

Journal of Xidian University. 2016, 43(3):  1-5.  doi:10.3969/j.issn.1001-2400.2016.03.001

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The traditional methods of blind equalization for orthogonal frequency division multiplexing(OFDM) systems have the problems of slow convergence rate and short received data. A novel blind equalization method of OFDM systems based on the multi-modulus hybrid algorithm and variable step size iteration of inter symbol interference is proposed to solve this problem. Piecewise multiplexing of the received data is adopted in this method, and then the modified constant modulus algorithm and the decision directed algorithm are mixed into the multi-modulus hybrid algorithm. This equalization method is utilized by the variable step size iteration based on inter symbol interference. Simulation results show that the proposed method has not only more stable convergence performance but also faster convergence speed than the traditional equalization methods in non-cooperative communication.

Performance analysis of network code division multiplexing over wireless sensor networks

YUE Jing;BAI Baoming

Journal of Xidian University. 2016, 43(3):  6-12.  doi:10.3969/j.issn.1001-2400.2016.03.002

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In a wireless sensor network (WSN), multiple groups of source nodes communicate with their respective destination nodes with the help of a common relay network. To remove the inter-session interference among multiple transmission sessions at each destination in a wireless sensor network, a network code division multiplexing (NCDM) scheme is proposed for the parallel session model. The fundamental of the NCDM scheme takes advantage of the property of the low-density generator matrix (LDGM) code to calculate the equivalent received signal. Then the NCDM scheme is analyzed. Based on the analysis of the soft processing, a new code design criterion for the construction of the generator matrix is developed. Simulation results show that by following the proposed code design criterion, the bit error ratio (BER) performance gap between the scheme we studied and the serial session scheme can be managed effectively.

Infinite max-margin Beta process factor analysis model

ZHANG Xuefeng;CHEN Bo;WANG Penghui;WEN Wei;LIU Hongwei

Journal of Xidian University. 2016, 43(3):  13-18+72.  doi:10.3969/j.issn.1001-2400.2016.03.003

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An infinite max-margin Beta process factor analysis (IMMBPFA) model is developed to deal with the classification problem on multimodal data. In this model, BPFA is utilized to capture the latent feature of data. With the idea of mixture experts, IMMBPFA divides the data into ‘infinite’ clusters via the Dirichlet process (DP) mixture model in the low-dimensional latent space and meanwhile learns a linear max-margin classifier on each cluster to construct a complex nonlinear classifier. Since the proposed model jointly learns BPFA, clustering and max-margin classifier in a unified Bayesian framework, it exhibits superior performance in both data description and discrimination. With the help of nonparametric Bayesian inference and the Gibbs sampler, we avoid the model selection problem and can estimate the parameters simply and effectively. Based on the experimental data obtained from Benchmark and measured radar high resolution range profile (HRRP) dataset, the effectiveness of proposed method is validated.

Imaging method for highly squinted SAR with spatially-variant doppler centroid correction

LI Zhenyu;CHEN Jianlai;LIANG Yi;XING Mengdao;BAO Zheng

Journal of Xidian University. 2016, 43(3):  19-24.  doi:10.3969/j.issn.1001-2400.2016.03.004

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In the high squint SAR imaging, the linear range walk correction (LRWC) is usually adopted to mitigate the coupling between range and azimuth. The conventional algorithms only consider the effects of Doppler frequency modulation rate dependence but ignore the spatially-variant Doppler centroid; this will affect the final focusing. In this paper, the effects of spatially-variant Doppler centroid in high-squint synthetic aperture radar (SAR) are analyzed and discussed, and a modified nonlinear chirp scaling algorithm with spatially-variant Doppler centroid correction in high squint SAR azimuth processing is proposed in order to improve the quality of the final focusing. Both simulation and real data processing validate the effectiveness of the proposed method.

Multistatic passive radar imaging algorithm for the gapped aperture

WANG Jue;WANG Jun;WU Yong;DENG Yaqi;LUO Zhen

Journal of Xidian University. 2016, 43(3):  25-30.  doi:10.3969/j.issn.1001-2400.2016.03.005

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Due to usually a small number of narrowband external illuminators and their uneven distribution, a single external illuminator and several receivers are used to synthetize aperture equivalently. The form of the target echo of the multistatic passive radar system is analyzed, and then the relationship of Fourier transform pair between target scattering function and the echo received by radar is deduced. Based on the prior knowledge of sparse distribution of the target, the algorithm of Compressed Sensing is used to recover the scattering coefficient of targets. Finally, the positions of receivers have been optimized by minimizing the correlation of the dictionary matrix based on minimizing the correlation coefficient of the dictionary matrix by the algorithm of Simulated Annealing (SA). Simulations show that the performance of the recovery of the image is improved significantly after optimizing.

Imaging method for the extended scene of missile-borne bistatic forward-looking SAR

MENG Ziqiang;LI Yachao;XING Mengdao;BAO Zheng

Journal of Xidian University. 2016, 43(3):  31-37.  doi:10.3969/j.issn.1001-2400.2016.03.006

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Due to such problems as high order terms in double square roots and more serious range cell migration than monostatic or bistatic SAR in range history, caused by high velocities and accelerations in both the transmitter and the receiver platforms in a new and special bistatic synthetic aperture radar imaging mode, i.e., missile-borne bistatic forward-looking synthetic aperture radar, an imaging algorithm correcting space variance for the extended scene for is proposed. The range walk is firstly corrected in the time domain to reduce the two dimensional (2D) coupling. And then the space variance of phase terms, in the 2D frequency spectrum of the echo signal with high precision gained by the method of series reversion, is analyzed quantitatively. The imaging is completed through polynomial fitting and variant match filter designing. With simple operation and less computation, our algorithm is convenient for imaging processing and subsequent procedure in the missile-borne platform. Simulation results show our imaging method significantly corrects the space variance, improves the focus quality of fringe targets, and thus extends the imaging scene.

Volume integral method for calculation of weak scattering from electronically large dielectric targets

FAN Jun;LEI Zhenya;XIE Yongjun;LI Xiaofeng

Journal of Xidian University. 2016, 43(3):  38-42+66.  doi:10.3969/j.issn.1001-2400.2016.03.007

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To calculate the high-frequency scattering fields from the weak scattering dielectric objects, starting with the vector and scalar wave equation separately,Born approximation and Rytov approximation are introduced to directly compute the radar cross section and extended to the high-frequency analysis of the electrical large weak scattering dielectric objects based on the volume integral equation. By weakening the mutual actions between the scattering field, the incident field and the total scattering field through this approximation, the complicated procedures for solving the matrix by the traditional method can be avoided, thus saving the computational resources and the time consumption. Numerical results show that the approach is accurate and effective.

Identifying pathogenic SNP loci by enrichment analysis

YANG Liying;YIN Liyang;YUAN Xiguo;ZHANG Junying

Journal of Xidian University. 2016, 43(3):  43-48.  doi:10.3969/j.issn.1001-2400.2016.03.008

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Aiming at the recognition of pathogenic SNP loci for complex diseases, this paper proposes an ensemble learning frame via the enrichment analysis mechanism, which can combine different approaches efficiently. Based on the proposed frame, Relief-F and CA trend testing are combined to identify disease-related SNP loci. The new approach can identify not only the single pathogenic site, but also the interaction between the locus at the same time. Experiments have been carried both on simulated data and on real data. Experimental results show that the proposed approach can significantly improve the recognition performance of pathogenic SNP loci for complex diseases. The proposed ensemble learning framework could provide reference for combining different approaches.

Improved NSGA-Ⅱ algorithm based on the uniformly crowding distance

WANG Mingzhao;WANG Yuping;WANG Xiaoli;WEI Zhen

Journal of Xidian University. 2016, 43(3):  49-54+130.  doi:10.3969/j.issn.1001-2400.2016.03.009

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With the wide application and further study of the genetic algorithm in multi-objective optimization problems, the NSGA-Ⅱ has been one of the representative evolutionary algorithms for multi-objective optimization problems. Crowding distance in the NSGA-Ⅱ plays an important role in convergence and uniform distribution of the solutions, but the NSGA-Ⅱ does not fully take the effect of each individual and the whole population into consideration. To estimate the region density more reasonably so as to make the solution set more uniformly converge to the Pareto optimal front, we design a uniformly crowding distance operator based on the uniformly crowding range and Gini weight, and propose an improved NSGA-Ⅱ algorithm. Finally, the effectiveness of the proposed algorithm is verified by experiments on six multi-objective optimization test functions.

Two phase clustering method for CNF clauses

FAN Quanrun;DUAN Zhenhua

Journal of Xidian University. 2016, 43(3):  55-60.  doi:10.3969/j.issn.1001-2400.2016.03.010

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Aimed at the Boolean clauses clustering, a two phases clustering method for CNF clauses is proposed. At the beginning, each clause is treated as a cluster. In the first phase, by a link based clustering method, the common neighbors between two clusters is used to determine how to merge the clusters. In the second phase, a similarity based clustering method is used. The first phase uses a global view to cluster the clauses, so the global optimum can be achieved in some sense. The second phase uses similarity to merge clusters, so the setting of the number of the final clusters in the algorithm is unnecessary. Experimental results show that the proposed method can lead to better clustering results with fewer common variables.

Interval and probability based analysis of seizure-preventing for synchronous gears of the astromesh deployable satellite antenna

LIU Shuaijie;DUAN Baoyan;YANG Dongwu

Journal of Xidian University. 2016, 43(3):  61-66.  doi:10.3969/j.issn.1001-2400.2016.03.011

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The seizure-preventing for synchronous gears of the Astromesh deployable satellite antenna is studied with random variables and interval variables existing at the same time. The uncertainties with influence on gear pair seizure failure are subdivided into interval variables and random variables, on the basis of which the interval and probability hybrid model is built for the synchronous gear pair seizure failure in the ring truss deployable antenna. The synchronous gear pair anti-seizure reliability is evaluated at different ambient temperatures with this hybrid model. And the results are compared with the reliability evaluated by the probability model in which the uncertainties are all regarded as obeying normal distribution.

Image reconstruction using an adaptive simultaneous algebraic reconstruction technique in computed tomography

QIAO Quanbang;HUANG Liyu;HE Zhijie

Journal of Xidian University. 2016, 43(3):  67-72.  doi:10.3969/j.issn.1001-2400.2016.03.012

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The simultaneous algebraic reconstruction technique(SART) is a vintage algorithm for computed tomography(CT) image reconstruction, but it has many problems such as slow convergence speed, edge blur, and ringing effect. The relaxation parameter is an important factor affecting the performance of the algorithm, and we find that the edge region does not need the same relaxation factor as the uniform region, so an adaptive simultaneous algebraic reconstruction technique based on fuzzy entropy is proposed. After preliminary SART reconstruction, by quoting fuzzy entropy for edge detection of the reconstructed image which is used as prior information, a monotonous increasing function that defines the relaxation factor is constructed based on the neighborhoodhomogeneous measurement(NHM). Therefore, the proposed approach can select the relaxation factor adaptively by the local character of the image. Experimental results show that the new algorithm can solve the problem of edge blurring and suppress the ringing effect effectively in CT image reconstruction.

New modeling method for ray tracing

YANG Xin;WEI Bing

Journal of Xidian University. 2016, 43(3):  73-77.  doi:10.3969/j.issn.1001-2400.2016.03.013

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It is often necessary to divide the spatial domain into grids in the ray tracing method. Based on the unit sphere inscribed icosahedron in this paper, a method of triangulation of the space curved surfaces by dimension reduction calculation is proposed. The process of this method is presented in detail by the triangulation of a unit sphere and two grid numbering schemes are given simultaneously. Then, combined with the direction of the electromagnetic radiation figure, the rays are selected. Finally, the examples of surface triangulation and tube selection are presented, which show the validation and effectiveness of this algorithm.

Higherorder singular value decomposition- and total variation- regularized multiplicative noise removal model

HUO Leigang;FENG Xiangchu;WANG Xudong;HUO Chunlei

Journal of Xidian University. 2016, 43(3):  78-84.  doi:10.3969/j.issn.1001-2400.2016.03.014

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Smoothness, sparsity and self-similarity are the priors widely used in image denoising due to their importance in representing natural images. Motivated by the collaborative roles of higher order singular value decomposition and total variation regularization, a new approach that can simultaneously capture the above priors is proposed in this paper for removing the multiplicative noises. By taking advantages of local adaptiveness, sparsity and self-similarity realized by higher order singular value decomposition, the proposed approach starts with similar-patch-group-wise adaptive denoising on the log-transformed image, followed by the iterative optimization implemented by the total variation constraint which considers the prior of smoothness. Experiments demonstrate the advantages of the proposed approach in removing multiplicative noise and preserving the details near the edges and in the texture area.

Research on the electronic transport characteristics of the three-dimensional graphene/carbon nanotube composite structure

LOU Lifei;PAN Qingbiao;ZHANG Junqin;ZHOU Xiaole

Journal of Xidian University. 2016, 43(3):  85-89.  doi:10.3969/j.issn.1001-2400.2016.03.015

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According to the actual growth way of graphene presence of the carbon source, four kinds of 3d grapheme-carbon nanotubes composite T structure are built, and their electron transport properties studied by combining density functional theory and the non-equilibrium green's function method. First the double probe model is built and the structure optimization is designed in ATK software, and then their transmission spectrums and electronic state density spectrum lines are analyzed. These research results can provide the reference for the 3d interconnect based on carbon nanomaterials.

Hybrid differential coherent bit synchronization algorithm for the weak GNSS signal

LU Weijun;LEI Dengyun;YU Dunshan

Journal of Xidian University. 2016, 43(3):  90-94+154.  doi:10.3969/j.issn.1001-2400.2016.03.016

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The low signal-to-carrier ratio and frequency deviation affect the bit synchronization in the GNSS receiver. In this paper, a hybrid differential coherent bit synchronization algorithm is presented, which uses the short coherent time to improve the signal gain and adopts the large distance differential coherent method to enhance the discrimination between bit edge and others. The results show that the proposed algorithm maintains a good frequency deviation tolerance, and achieves good synchronization performance under 50Hz frequency deviation. Compared with previous methods, the proposed algorithm improves the sensitivity of bit synchronization by 3～7dB.

Locally-restricted regular clustering superpixel algorithm

WANG Yunfei;BI Duyan;LIU Huawei;LIU Ling;ZHAO Xiaolin

Journal of Xidian University. 2016, 43(3):  95-100.  doi:10.3969/j.issn.1001-2400.2016.03.017

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It is difficult to obtain superpixels which are compact and adhere well to image boundary by traditional superpixel algorithms, because of their high complexity. This research proposes a new superpixel algorirhm of Locally-Restricted Regular Clustering (LRRC) for overcoming those difficulties. This algorithm is based on the k-means algorithm, and adopts the LRRC method and a class combination strategy to produce superpixels with equal and regular sizes. In clustering, both pixel color and position features are taken into account, and the logarithm mechanisim is introduced to balance the differences of their values. Through the special color distance filtering process the boundaries of superpixels are smoothed more effectively. Simulation results show that the LRRC algorithm is simple for use, efficient for computation, and can get a high boundary recall and a low under-segmentation error. When the number of partition superpixels is fairly large, the performance of the LRRC algorithm is better than other powerful superpixel algorithms in available.

Design of the D2D multicast transmission scheme in the LTE communication system

WANG Jing;LIU Xiangyang;YANG Yang;WANG Xinmei

Journal of Xidian University. 2016, 43(3):  101-106+136.  doi:10.3969/j.issn.1001-2400.2016.03.018

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In order to improve spectrum efficiency and transmission reliability of the LTE communication system, its terminal users can be divided into the D2D communication cluster. Specially, the multicast transmission of data packets in the LTE system can be realized through two hop transmissions, namely, the base station multicasts data packets to all cluster-heads and each cluster-head in the D2D communication cluster broadcasts the received packets. Considering that the links may be unreliable in the D2D communication cluster, the ARQ retransmission algorithm based on network coding is adopted. By establishing the lost-packet list, the cluster-head operates the lost-packets by network coding, and broadcasts the encoded packets to reduce the number of retransmission. Performance analysis and simulation results show that the proposed scheme can achieve almost the same transmission efficiency as the existing scheme, but has a lower computational complexity. Compared with the traditional multicast retransmission scheme based on network coding in the cellular communication mode, the scheme only retransmits the lost-packets in D2D cluster, to reduce the pachets transmission number of base stations and decrease the spectrum resource consumption of the cellular network effectively at a high packet loss rate.

Registration based compensation method based on adaptive subspace tracking

FENG Weike;ZHANG Yongshun;TONG Ningning

Journal of Xidian University. 2016, 43(3):  107-113.  doi:10.3969/j.issn.1001-2400.2016.03.019

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The registration based compensation (RBC) method is an effective method to compensate the range-dependence of the main-lobe clutter and side-lobe clutter in the same time. However, the compensation performance of the RBC degrades because of the mismatch of prior information and the loss of degree of system freedom. Moreover, the RBC is not very suited for real-time implementation because of the enormous computational complexity and memory usage of eigenvalue decomposition. In this paper, a novel clutter range-dependence compensation method using the modified maximum likelihood adaptive subspace estimation algorithm, which is named the MRBC method for short, is proposed. The eigenvectors matrix and eigenvalues matrix of the clutter covariance matrix are estimated by iterative tracking instead of temporal and spatial smoothing, spectrum calculation and eigenvalue decomposition. Compared with the traditional RBC method, the proposed method can reduce the computational complexity significantly and maintain the performance of clutter range-dependence compensation. In addition, the proposed method can also achieve good performance when the system error exists because of no use of prior information. Experimental simulations demonstrate the validity of this method.

Features extracting method of ground vibrating targets for dual-channel SAR

LIANG Ying;ZHANG Qun;YANG Qiu;GU Fufei

Journal of Xidian University. 2016, 43(3):  114-119.  doi:10.3969/j.issn.1001-2400.2016.03.020

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The returned radar signal includes the vibrating target echo but also the strong ground clutter. However, it is difficult to detect and extract the vibrating features for SAR. For detecting and extracting the features of vibrating targets on the ground, the displaced phase center antenna (DPCA) technique is applied to suppress the ground clutter, which indicates that a time-varying envelope is induced after the DPCA processing, named the slow time envelope (STE). The energy distribution of micro-Doppler (m-D) time-frequency curve is influenced by the STE, and the integrated m-D time-frequency curve cannot be obtained. Further, an extracting method of vibrating features based on STE signatures is proposed. Finally some simulations are given for validating the theoretical derivation and the effectiveness of the proposed extracting method.

Adaptive particle swarm optimization method with stagnancy information

LIU Daohua1;CHEN Liangqiong2;HU Xiuyun1;ZHANG Qian1

Journal of Xidian University. 2016, 43(3):  120-124+160.  doi:10.3969/j.issn.1001-2400.2016.03.021

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To improve the performance of the particle swarm optimization algorithm, the optimal network of the particle age structure with stagnation information is designed, and the information about this network is used to adaptively change the three key parameters of the particle swarm optimization algorithm. At the same time, an adaptive particle swarm optimization method with stagnancy information is proposed and specific optimization steps of this method are given. Four classical low and high dimension benchmark test functions are used to validate the performance of the optimization method, and a comparison study is made with gravitational search algorithm and the traditional particle swarm optimization algorithm without stagnancy information. The comparison study shows that the search efficiency of the proposed method is 2 times higher than that of other methods in the literature in the case of low dimensional multimodal functions. When the dimension of functions is higher than 2, the search efficiency of the proposed method is almost the same as that of other methods, but with the better ability to achieve global solution and local solutions, and the higher solving precision.

Imaging algorithm for highly squinted SAR data processing based on phase disturbing

QU Guangzhou;LIANG Yi

Journal of Xidian University. 2016, 43(3):  125-130.  doi:10.3969/j.issn.1001-2400.2016.03.022

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For quick look imaging, a phase disturbing algorithm (PDA) for focusing synthetic aperture radar (SAR)subaperture data acquired at a high squint angle is proposed. First, the signal model is addressed and then the range processing and azimuth processing are analyzed in detail. The PDA performs the linear range walk correction (LRWC) in the time domain and the range cell curvature correction (RCCC) in the frequency domain to mitigate the range-azimuth coupling. Additionally, a disturbing phase is introduced in the frequency domain to remove the variation of the Doppler chirp rate with the azimuth position caused by LRWC in the time domain,and so an identical reference function can be employed in azimuth processing. Simulated results and raw data processing validate the effectiveness of the proposed algorithm.

Cross-layer adaptive cooperative TDMA protocol for multi-hop wireless networks

HUANG Shaocheng;MA Linhua;CAI Zhao;ZHANG Song;RU Le;TIAN Yu

Journal of Xidian University. 2016, 43(3):  131-136.  doi:10.3969/j.issn.1001-2400.2016.03.023

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Aiming at signal fading in the Rayleigh channel and channel waste or overload caused by the sudden traffic transmission in multi-hop wireless networks, a cross-layer adaptive cooperative time division multiple access protocol(CAC-TDMA) for multi-hop wireless networks is proposed. By taking advantage of the routing layer characteristics that periodically update topology, nodes can get the channel outage probability and position, determine whether they are cooperative relays themselves by no additional consultations overhead, which can decrease the waiting delay and increase channel utilization. To make a numerical analysis of the throughput, packet drop rate and delay of CAC-TDMA, a Markov chain analysis models of CAC-TDMA is constructed. Numerical and simulation results show that the proposed protocol can guarantee better performance than the conventional TDMA, that is, the maximum increase of throughput is 36％ and the maximum decrease of delay is 40％.

Network security threat assessment based on the signaling game

ZHANG Hengwei;YU Dingkun;HAN Jihong;WANG Jindong;KOU Guang

Journal of Xidian University. 2016, 43(3):  137-143.  doi:10.3969/j.issn.1001-2400.2016.03.024

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Nowadays, researches on network security defense based on game theory mostly use completed information or static game theory to establish the attack-defense model. In order to perform security threat assessment in a closer way to the practical situation in a network, this paper proposes a network attack-defense game model based on the signaling game, which is modeled in a dynamic and uncompleted way. After putting forward the solving process of the perfect Bayesian equilibrium of the signaling game, this paper analyzes all kinds of equilibriums existing in the game. Taking the posterior belief as the defender's prediction of the attacker's type, this paper puts forward the assessment algorithm for the network security threat based on the model above, predicts the security threat the defender is facing, and provides the security threat grade for the evaluator. Finally, the feasibility and validity of the model and the method proposed by this paper are testified through the analysis of a network example.

Characteristic analysis of the border effect in precision frequency measurement

OU Xiaojuan;ZHOU Wei;YI Weiwei;ZHANG Xiaoyan;LI Jing

Journal of Xidian University. 2016, 43(3):  144-148.  doi:10.3969/j.issn.1001-2400.2016.03.025

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In the precision frequency measurement, a high measurement resolution can be obtained by the phase processing methods and the border effect plays a vital role in improving the measurement accuracy. This paper  makes a detailed analysis of the generation mechanism of the border effect. By experiments, the application of the characteristics of the border effect is analyzed and validated in the precision frequency measurement. The combinative test experiments with multiplier amplifiers show that the frequency stability can reach 4.8×10^-13/s based on the border effect after the signal is processed by two multiplier amplifier sections. The results further reveal that it can ensure not only the high resolution but also the authenticity of the measurement results in the noise environment relying on the border of the resolution fuzzy area of the detection instruments.

Carrier leakage and I/Q mismatch calibrated technique

雷倩倩

Journal of Xidian University. 2016, 43(3):  149-154.  doi:10.3969/j.issn.1001-2400.2016.03.026

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The carrier leakage and I/Q mismatch calibrated technique based on the digital baseband for the direct conversion transmitter is described. The proposed technique only needs a calibration chain to detect mismatches, and then transmits them to the digital baseband, which completes the calibrated task. The proposed method is very simple in reducing die areas and power dissipation. Under TSMC 013μm CMOS technology simulation, the calibrated error of carrier leakage is less than 15％ and the error of I/Q mismatch is less than 65％．The measurement results indicate that I/Q amplitude mismatch is reflected at twice the input frequency. The calibrated chain gain range is 15dB with a 5dB step, and the bandwidth is 20MHz.

Two dimension migration compensation method for W-band ISAR imaging

WEI Yibo;WANG Hui;LI Ning;YU Weidong

Journal of Xidian University. 2016, 43(3):  155-160.  doi:10.3969/j.issn.1001-2400.2016.03.027

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The problem of migration through the resolution cell (MTRC) in the W-band Inverse Synthetic Aperture radar (ISAR) imaging system is serious. Therefore, a novel two dimensional compensation method is proposed in this paper. Firstly, the cause of migration in ISAR imaging is analyzed. Then, the Keystone transform is used to compensate the MTRC in the range direction. After that, the minimum entropy algorithm is used to estimate the average rotate speed of the target and the rotate speed is used to compensate the cross range direction MTRC of a uniformly rotating target by using the phase correcting method. Finally, the sub-aperture imaging algorithm is used to reduce the cross range MTRC in imaging the maneuvering target. Simulation results show that a high resolution result is achieved and the effectiveness of the two dimensional compensation method is verified.

Convolutional neural networks recognition algorithm based on PCA

SHI Hehuan;XU Yuelei;MA Shiping;LI Yueyun;LI Shuai

Journal of Xidian University. 2016, 43(3):  161-166.  doi:10.3969/j.issn.1001-2400.2016.03.028

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To improve the insufficiency of Synthetic Aperture Radar(SAR) labeled training data for Convolutional Neural Networks(CNN) and the recognition rate for large variations, a novel CNN recognition algorithm is proposed. Firstly, a set of features is extracted from the original data by unsupervised training based on PCA as the initial filter set for CNN. Secondly, in order to accelerate the training speed while avoiding over-fitting, the Rectified Linear Units(ReLU) is adopted as the non-linear function. Thirdly, to strengthen robustness and mitigate the defects of pooling upon features, a probabilistic max-pooling sampling method is introduced and local contrast normalization is exploited on features after the convolutional layer. Experiments demonstrate that our algorithm outperforms the original CNN in recognition rate and achieves better robustness for large variations and complex background.

Kinetic Monte Carlo simulation of GaN epitaxy

FENG Lansheng;GUO Runqiu;ZHANG Jincheng

Journal of Xidian University. 2016, 43(3):  167-171.  doi:10.3969/j.issn.1001-2400.2016.03.029

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A chemical reaction mode about GaN epitaxy in MOCVD is presented. We simulate the growth process of GaN in the vertical-spray MOCVD system on this mode using the KMC mothod. The result shows that adductive reaction mostly occurs at a lower temperature and pyrolytic reaction mostly occurs at a high temperature. And the growth rate increases with increasing temperature. This feature determines the surface morphology of the material. We also include the diffusion and desorption process of the reaction particle by the KMC method. These processes depend mostly on temperature and ultimately affect the surface morphology of the GaN material.

Fast subpixel registration method for InSAR images

XUE Haiwei;FENG Dazheng

Journal of Xidian University. 2016, 43(3):  172-178.  doi:10.3969/j.issn.1001-2400.2016.03.030

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In conventional registration methods, image interpolation is used to extract subpixel offsets which lead to the limitation that the registration accuracy is restricted by the interpolation unit. Moreover, the computational burden is heavy when high accuracy is demanded. In order to reduce the computational load, we propose an efficient offset estimation method for interferometric synthetic aperture radar (InSAR) image subpixel registration. Firstly, a novel cost function continuously varying with offsets is established by integrating the empirical signal-to-noise ratio (SNR) and the interpolation operation. This suggests a more accurate registration since the accuracy of the estimated offsets does not depend on the interpolation unit. Secondly, an efficient bi-iterative algorithm is employed to solve the cost function in the continuous domain. The subpixel offsets associated with the maximum of the cost function can be exactly obtained with low computational complexity. Simulated and real data are tested to illustrate the good performance and computational efficiency of the proposed method.

Passive intermodulation analysis of coupled electro-thermal microwave loads

JIANG Jie;LI Tuanjie;MEI Yujian;WANG Hongjun

Journal of Xidian University. 2016, 43(3):  179-184.  doi:10.3969/j.issn.1001-2400.2016.03.031

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Microwave loads are used to improve the matching performance of circuits and absorb the microwave energy. The microwave loads generate the joule heat to affect the electrical resistivity after consuming microwave energy which may produce the passive intermodulation (PIM). Electro-thermal compling leads to the difference of the time scale which produces PIM. In order to address the problem, the fractional heat conduction model of microwave loads is created by the fractional calculus firstly. Then the circuit model of the fractional heat conduction is established. Eventually, the thermal resistance effect is considered. The expression for the PIM power level caused by the coupled electro-thermal microwave loads is derived. The influences of the material's temperature coefficient of resistance, thermal resistance and thermal capacity to PIM are revealed, which provides the fundamental basis for reducing the PIM from the coupled electro-thermal microwave loads.
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Improved ant colony algorithm for the optimal-quality-path routing problem with multi-constraints

MA Ronggui;CUI Hua;XUE Shijiao;GUO Lu;YUAN Chao

Journal of Xidian University. 2016, 43(3):  185-189.  doi:10.3969/j.issn.1001-2400.2016.03.032

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As the traffic congestion becomes more and more serious, the public evaluation standard for the road quality during driving changes greatly. How to avoid congestion to find the best way to travel has become an important scientific issue and social issue urgent to address in the context of building a smart city. Thus this paper first defines the novel concept of optimal path with multi-constraints and models it. Then, in order to solve the proposed model more efficiently, we improve the state transition rules of the heuristic function and pheromone update operator based on the classical ant colony algorithm by increasing the path optimization algorithm's awareness of real-time path quality information, such as traffic conditions, resulting in the strong dynamic adjustment ability of our proposed path optimization algorithm to path information. Simulation results show that our proposed ant colony algorithm can find the optimal path with multi-constraints more accurately and more quickly than other ant colony algorithms.

Availability evaluation model for the heterogeneous system based on RBD

SUN Jian;ZHANG Xingjun;DONG Xiaoshe

Journal of Xidian University. 2016, 43(3):  190-196.  doi:10.3969/j.issn.1001-2400.2016.03.033

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In order to cope with difficulty of heterogeneous system availability evaluation caused by autonomous node performance and characteristic differences, the paper proposes an availability evaluation model based on the reliability block diagram (RBD). First, we analyze and catalog system heterogeneity from the angle of nodes and tasks, and quantify resource heterogeneity. Then by heterogeneity classification, we build a serial and parallel mixed RBD availability evaluation model, and discuss the availability measurement method of nodes and the whole heterogeneous system. Availability evaluation takes the dual-computer and multi node heterogeneous system for example, and compares evaluation results with the Markov process availability model. Results show that the model we propose can evaluate the heterogeneous system with accuracy, and hence, provide references for research on availability improving and high-availability design of the heterogeneous system.