Table of Content

31 May 2014, Volume 32 Issue 3

Previous Issue    Next Issue

Articles

Image Denoising Based on Anisotropic Diffusion and Sparse Representation in Shearlet Domain

WU Yi-quan1,2,3, LI Li1, TAO Fei-xiang1

2014, 32(3):  221-228.  doi:10.3969/j.issn.0255-8297.2014.03.001

Asbtract ( 1676 )   PDF (6890KB) ( 1344 )  

References | Related Articles | Metrics

To suppress image noise effectively and better preserve edge details, an image denoising method
based on anisotropic diffusion and sparse representation in the shearlet domain is proposed. The noisy image is
first decomposed into a low frequency component and several high frequency components by non-subsampled
shearlet transform (NSST). The main energy of the image information is contained in the low frequency
component, while the edge information and most of noise are contained in high frequency components. The K-singular value decomposition (K-SVD) algorithm is used to remove noise in low frequency component. The kernel anisotropic diffusion (KAD) algorithm is used to reduce noise in each high frequency component. The reconstructed image is obtained by inverse non-subsampled shearlet transform (INSST) for the processed low frequency and high frequency components. Noise in the image is effectively suppressed, and edge details are preserved satisfactorily. Experimental results show that, compared with the denoising methods such as wavelet combining with nonlinear diffusion method, shearlet hard threshold method, K-SVD sparse denoising method and sparse redundant denoising method in wavelet domain, the proposed method has better performance both in noise reduction and detail preservation.  

Communication Engineering

Design of Channel Emulator for Wideband MIMO Systems

XIONG Yan-wei, ZHANG Jian-hua, ZHANG Ping

2014, 32(3):  229-236.  doi:10.3969/j.issn.0255-8297.2014.03.002

Asbtract ( 1948 )   PDF (5575KB) ( 1571 )  

References | Related Articles | Metrics

4G technologies are focused on delivering high level throughput by using MIMO technology and wider signal bandwidth. To evaluate the MIMO system performance highly related to the accurate representation of the channel condition, over-the-air (OTA) test is performed with a channel emulator as an important part. In this paper, a channel emulator for wideband MIMO system is designed. Compressed sensing is used to sample analog signals as the bandwidth becomes wider. Frequency domain approaches are used to implement the emulator to reduce complexity for higher order arrays.

Signal and Information Processing

Cognitive MIMO System Based on Protograph LDPC Codes in Television Band

WANG Kai-yao, XIAO Yang

2014, 32(3):  237-245. 

Asbtract ( 1601 )   PDF (10748KB) ( 2551 )  

References | Related Articles | Metrics

In TV band, adopting the current cognitive radio schemes, the cognitive user (CU) will face the problem of TV signals. In order to solve this problem, this paper proposes a novel interference cancellation scheme based on protograph LDPC codes and virtual MIMO for cognitive radio system in television band.
Protograph LDPC codes are applied to virtual MIMO cognitive radio system in the proposed scheme, and by encoding transmitting data and MIMO space-time processing, it can cancel TV signal interference and channel noise. The core idea of the proposed scheme is that, depending on the difference of channel fading between the CUs and TV station’s transmitter, the TV signal interference and channel noise are looked as a new interference at the CU receiver. By decoding received signal using protograph LDPC, the CU receiver can cancel the TV signal interference from the TV station. In an optimal situation, the proposed approach can increase about 0.620.76 times of communication capacity for the proposed cognitive radio system. Comparing with the approach of directly extracting user information, the proposed scheme obtained about 12 dB coding gain in Rayleigh flat-fading channel, and it can cancel the TV signal interference efficiently.

Communication Engineering

Mechanism of P2P File Distribution Based on Deterministic Network Coding

HAO Kun1,2, JIN Zhi-gang1

2014, 32(3):  246-250.  doi:10.3969/j.issn.0255-8297.2014.03.004

Asbtract ( 1342 )   PDF (7000KB) ( 840 )  

References | Related Articles | Metrics

 This paper proposes a P2P file distribution model based on deterministic network coding (DLNCCD).This coding method can be applied to the specific multicast uniform network topology to reduce complexity of network coding, improve decoding efficiency, and ensure maximum network coding gain. The
experimental results show that the total distribution time can reduce by 10%15%, and the throughput can improve by 17%21%, and the average download time can reduce by about 20%, Therefore the performance of the file distribution system is improved.

Network Coding Based LDPC-Coded Cooperation

ZHANG Shun-wai, YANG Feng-fan, TANG Lei

2014, 32(3):  251-256.  doi:10.3969/j.issn.0255-8297.2014.03.005

Asbtract ( 1601 )   PDF (3771KB) ( 1102 )  

References | Related Articles | Metrics

This paper proposes a cooperation scheme for network coding based on irregular binary systematic LDPC codes. The relay cooperates with two users via network coding simultaneously to improve average throughput. Outage probability of the proposed scheme is analyzed for the case that the relay just forwards parity-check bits. To efficiently decode three signals from the two users and the relay, a joint iterative decoding algorithm is used at the destination based on the joint Tanner graph. Simulation results show that the proposed network coding based LDPC-coded cooperation scheme significantly lowers outage probability compared with noncooperation schemes. In case of high SNR, the scheme can achieve obvious bit-error-ratio (BER) performance gain.

Signal and Information Processing

Shallow Sea Channel Estimation With H1 Adaptive Filtering

DONG Zheng, GONG Ke-xian, GE Lin-dong

2014, 32(3):  257-262.  doi:10.3969/j.issn.0255-8297.2014.03.006

Asbtract ( 1316 )   PDF (9101KB) ( 700 )  

References | Related Articles | Metrics

 Shallow sea is a difficult channel for acoustic communications. Noise in shallow sea acoustic communications may be described by the S S distribution, and the channel modeled as a sparse double selective fading channel. The H1 adaptive filtering is specially designed for none-Gaussian noise, and therefore can be used for channel estimation in an S S noise environment. This paper proposes an algorithm to solve the channel estimation problem based on the H1 adaptive filtering. In addition, to solve the performance degradation problem due to serious individual pulse noise, a signal preprocessing method is proposed. The results show that the performance is improved because of the preprocessing. It is shown that the performance of the H1
adaptive filtering is better than sIPNLMS both in a sparse multipath channel and in a sparse double selective channel.

Cultural Algorithm with Cellular Space Structure

LI Ming|YIN Xiao-yuan|CHEN Hao

2014, 32(3):  263-273.  doi:10.3969/j.issn.0255-8297.2014.03.007

Asbtract ( 1612 )   PDF (3061KB) ( 819 )  

References | Related Articles | Metrics

To solve the problems in the cultural algorithm has a number of problems, for example, lack of a region concept in the population space, lack of cultural evolution in the belief space, and defects such as low accuracy and being easy to fall into a local optimum. This paper proposes a new cultural algorithm based on cellular space structure. It can simulate a double-layer evolutionary system of culture algorithm by embedding a cellular space grid structure in the framework of computing population space and belief space. For the population space, the evolutionary individuals are distributed in the lower cellular space grid. The grid is divided into many areas so that individuals in each area evolve independently by using differential evolution algorithm. For the belief space, the evolution information is put into the upper grid corresponding to the population space, and the evolution of culture is realized using a diffusion mechanism of culture. Experimental results show that the algorithm is effective in convergence accuracy and global search capability, and has advantages in dealing with complex high-dimensional optimization problems.

Reverse Time Migration Imaging and SPIHT

ZHANG Xiao-dan1, ZHANG Zhi-yu2, XU Jin1, ZHU Yao-lin1

2014, 32(3):  274-280.  doi:10.3969/j.issn.0255-8297.2014.03.008

Asbtract ( 1317 )   PDF (11083KB) ( 753 )  

References | Related Articles | Metrics

Reverse time migration (RTM) is a precise migration methods based on the full-wave equation,however, RTM takes too much computing time. This paper aims to save the computing time by analyzing the RTM and applying set partitioning in hierarchical tree (SPIHT) based on integer wavelet transform (IWT)
of LS to save memory consumption, thus reducing computing time. The Marmousi model is used in the RTM-SPHIT method. The migration results show that the method can solve the problem of computing time consumption with good imaging accuracy.

Block Compressed Sensing Sampling and Reconstruction Using Spectral Prediction for Hyperspectral Images

JIA Ying-biao, FENG Yan, YUAN Xiao-ling, WEI Jiang

2014, 32(3):  281-286.  doi:10.3969/j.issn.0255-8297.2014.03.009

Asbtract ( 1770 )   PDF (1871KB) ( 1075 )  

References | Related Articles | Metrics

Compressed sensing (CS) provides a new method for data acquisition. Ahyperspectral images CS
methodology is proposed in this paper. In the proposed framework, hyperspectral images are divided into
several groups, and each group consists of a reference band followed by some common bands. Random measurements of the individual spectral bands are obtained using block CS independently. In image reconstruction,the reference bands are reconstructed with the smoothed projected Landweber algorithm, and the common bands with a new reconstruction algorithm. The algorithm is implemented as follows: 1) Obtain predicted values of the common bands using the spectral bidirectional prediction. 2) Calculate measurement differences using block observation on the predicted values. 3) Reconstruct the images and their corresponding prediction differences in an iterative fashion. This method can improve reconstruction quality as it has fully considered the spectral and spatial correlations. Experimental results reveal that reconstruction performance of the proposed method is substantially superior to that by applying 2-D image reconstruction independently and that of a multiple-vector CS variant method.  

Control and System

Collaborative Path-Planning of Multiple UAV in Radar Threatening Environment

GAO Chen, ZHEN Zi-yang, GONG Hua-jun

2014, 32(3):  287-292.  doi:10.3969/j.issn.0255-8297.2014.03.010

Asbtract ( 1715 )   PDF (6511KB) ( 1284 )  

References | Related Articles | Metrics

 To solve the problem of collaborative path planning of multiple unmanned aerial vehicles (UAV) under radar threatening environment, an intelligent method based on Voronoi diagram and ant colony optimization (ACO) algorithm is proposed. According to known radar threat sources, a weighted Voronoi diagram
is created to discretize the flying space into a grid. ACO is then used to obtain a set of selectable paths for each UAV. The parameters are properly chosen to relax the optimality of ACO so that multi-solutions can be found. A coordination function is created, and the estimated team arrival time (ETA) is taken as the time constraint to pick out the final path of each UAV. The path is smoothed for actual flight. Simulation results show that the proposed method can satisfy the requirements of time coordination and overall optimal.

Modeling and Behavior Analysis of Hybrid System Using Timed Hierarchical CPN

LI Sheng-chang1, SONG A-ni2, WANG Ming-zhe1

2014, 32(3):  293-300.  doi:10.3969/j.issn.0255-8297.2014.03.011

Asbtract ( 1226 )   PDF (13074KB) ( 881 )  

References | Related Articles | Metrics

 Modeling and behavior analysis for a large hybrid system is challenging because of complexity of the system. A modeling method based on timed hierarchical colored Petri net (THCPN) is proposed in this paper. Using the idea of a discrete event driven system, the continuous part is embedded into the model by extension transition. Thus, both discrete and continuous parts of the hybrid system can be modeled using professional tools in the respective fields. Hybrid interactive simulation can be implemented with communication interface. This way, data consistency and time synchronization are ensured. In analyzing the hybrid model, a structure analysis method of Petri net is performed to get different behavior patterns of the hybrid system. Thus, a multi-attribute simulation analysis of different behavior patterns can be conducted. Feasibility of the method is shown by a missile defense system.

Control of a New Type Multi-rotor Aircraft with RBFNN and Backstepping

YANG Cheng-shun1,2, YANG Zhong1, GE Le1,2, HUANG Xiao-ning2, ZHANG Qiang3

2014, 32(3):  301-310.  doi:10.3969/j.issn.0255-8297.2014.03.012

Asbtract ( 1667 )   PDF (8619KB) ( 822 )  

References | Related Articles | Metrics

Modeling and trajectory tracking control for a multi-rotor unmanned aerial vehicle (UAV) is studied. Nonlinear kinematics and dynamics models of the aircraft are established. A robust adaptive trajectory tracking control scheme based on fully tuned radial basis function neural network (FTRBFNN) and command
filtered backstepping is proposed for the multi-rotor aircraft. In the scheme, a position error PID controller of the aircraft is developed to eliminate deviation of the flight trajectory from the desired trajectory, and construct attitude angle commands for the attitude control loop. FTRBFNN is then used to estimate composite disturbance of the rotational dynamics. To avoid calculating pseudo control signal derivative analytically, and decrease dependence on the analytic model in the standard backstepping design, a command filtered backstepping technique is used to design the attitude controller. The technique uses a filter to calculate derivatives of the virtual control signal, instead of using analytical differentiation. It thus significantly simplifies
backstepping implementation and saves control energy. Correctness and effectiveness of the proposed robust adaptive trajectory tracking scheme are verified through simulation experiment.

Counteracting Crosswind Sliding Mode Control of Ultra-low Altitude Airdrop Based on Feedback Linearization

LIU Ri, SUN Xiu-xia, LI Da-dong, DONG Wen-han

2014, 32(3):  311-318.  doi:10.3969/j.issn.0255-8297.2014.03.013

Asbtract ( 1659 )   PDF (7183KB) ( 797 )  

References | Related Articles | Metrics

 Translation of the inner cargo coupled with the crosswind threats flight safety and affects the mission of airdrop. To solve the problem, a controller combining feedback linearization with variable structure is proposed. The system is decoupled and linearized using a differential geometry feedback linearization technique. Thus, the inner loop for altitude angle control is designed by using the variable structure theory so that system robustness is ensured. The flight control system is completed by combining with the outer loop PID control for path-hold. Simulation results confirm that a controller with strong robustness can satisfy the airdrop indexes.

Robust Control of Missile Launch Vehicle Erecting Device Based on Disturbance Observer

ZHU Cheng, CHEN Mou

2014, 32(3):  319-324.  doi:10.3969/j.issn.0255-8297.2014.03.014

Asbtract ( 1961 )   PDF (6555KB) ( 1009 )  

References | Related Articles | Metrics

 To deal with the loss of stability and quickness in the vertical device of a missile launch vehicle, this paper models the kinematics and hydraulic system. With the established model, precise control of the vertical angel is designed using the backstepping control technique. To model uncertainties and unknown external disturbances, a radial basis function (RBF) neural network disturbance observer is developed. Control precision of the system is improved by using output of the RBF neural network disturbance observer. Simulation results show that good dynamic performance and strong robustness can be obtained under backstepping control of missile launch vehicle erecting device based on the neural network disturbance observer.

Force-Geometric Error Modeling of CNC Machine Tools Using PSO-SVM

YANG Hong-tao, GENG Jin-hua, DING Xiao-rui, YU Cao-feng, YU Bing

2014, 32(3):  325-330.  doi:10.3969/j.issn.0255-8297.2014.03.015

Asbtract ( 1824 )   PDF (7717KB) ( 950 )  

References | Related Articles | Metrics

To improve modeling precision of CNC geometric error and error compensation, the main cutting force is simulated and measured using a dynamometer. Errors in the pitching and deflection angles are measured with a laser interferometer. Trained with practically measured error data, the force-geometric error
predicting model based on PSO-SVM is established with the key parameters optimized using the particle swarm optimization algorithm (PSO). Verification experiments show that difference between the measured error and the maximum deflection angle error using the PSO-SVM model is 0.6 μrad, and that with the maximum error  of pitching angle error is 0.21 μrad. Compared with the force-geometric error predicting model based on BP neural networks and SVM whose parameters is optimized using a conventional method, the prediction precision of the PSO-SVM error model is greatly improved. Therefore the proposed model can compensate geometric error of CNC machine tools in real-time with high-precision.