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Systems Engineering and Electronics, Journal of

Issue 6 • Date Dec. 2012

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Displaying Results 1 - 25 of 26
  • [Front cover]

    Page(s): c1
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    Freely Available from IEEE
  • Inside front cover.pdf

    Page(s): c2
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  • Contents

    Page(s): 1 - 2
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  • IDMA based MAI mitigation scheme with low complexity and low latency

    Page(s): 791 - 801
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1461 KB)  

    High complexity and high latency are key problems for multiuser detection (MUD) to be applied to a mobile station in cellular networks. To tackle these problems, an interleave division multiple access (IDMA) based multiple access scheme, grouped spread IDMA (GSIDMA), is proposed. In a GSIDMA system, lower complexity and latency for mobile stations can be achieved by appropriately dividing active users into different groups. The system model of GSIDMA is constructed and followed by analysing on its system capacity, complexity and latency, and bit error rate (BER) performance. The extrinsic information transfer (EXIT) chart is used to analyze the convergence behavior of the iteration process. The grouping method and interleavers-reuse issue for GSIDMA are also discussed preliminarily. The analyses and simulation results indicate that the complexity and latency of the proposed scheme are much lower than those of IDMA, whereas its BER performance is close to the latter. The properties of low complexity and low latency make it more feasible for the practical implementation. View full abstract»

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  • Adaptive monopulse beamforming with partial parallel structure

    Page(s): 802 - 814
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (3919 KB)  

    A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance (LCMV) criterion for adaptive monopulse systems is proposed. The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly. An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam, respectively. The optimal weight vector can be obtained after convergence. The required computational complexity is evaluated for the proposed technique, which is on the order of O(N) and less than that of the conventional LCMV method. The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced. This scheme is easy to be implemented on a distributed computer/digital signal processor (DSP) system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array. Then, the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations. Compared with some recent adaptive monopulse estimation methods, a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method. View full abstract»

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  • Repeated sending file delivery protocol in satellite networking communication

    Page(s): 815 - 823
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1436 KB)  

    Satellite networking communications in navigation satellite system and space-based deep space exploration have the features of a long delay and high bit error rate (BER). Through analyzing the advantages and disadvantages of the Consultative Committee for the Space Data System (CCSDS) file delivery protocol (CFDP), a new improved repeated sending file delivery protocol (RSFDP) based on the adaptive repeated sending is put forward to build an efficient and reliable file transmission. According to the estimation of the BER of the transmission link, RSFDP repeatedly sends the lost protocol data units (PDUs) at the stage of the retransmission to improve the success rate and reduce time of the retransmission. Theoretical analyses and results of the Opnet simulation indicate that the performance of RSFDP has significant improvement gains over CFDP in the link with a long delay and high BER. The realizing results based on the space borne filed programmable gate array (FPGA) platform show the applicability of the proposed algorithm. View full abstract»

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  • Worst-case tolerance analysis on array antenna based on chaos-genetic algorithm

    Page(s): 824 - 830
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (953 KB)  

    This paper studies the effect of amplitude-phase errors on the antenna performance. Via builting on a worst-case error tolerance model, a simple and practical worst error tolerance analysis based on the chaos-genetic algorithm (CGA) is proposed. The proposed method utilizes chaos to optimize initial population for the genetic algorithm (GA) and introduces chaotic disturbance into the genetic mutation, thereby improving the ability of the GA to search for the global optimum. Numerical simulations demonstrate that the accuracy and stability of the worst-case analysis of the proposed approach are superior to the GA. And the proposed algorithm can be used easily for the error tolerant design of antenna arrays. View full abstract»

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  • New targets number estimation method under colored noise background

    Page(s): 831 - 837
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1159 KB)  

    A multiple targets detection method based on spatial smoothing (MTDSS) is proposed to solve the problem of the source number estimation under the colored noise background. The forward and backward smoothing based on auxiliary vectors which are received data on some specific elements is computed. By the spatial smoothing with auxiliary vectors, the correlated signals are decorrelated, and the colored noise is partially alleviated. The correlation matrix formed from the cross correlations between subarray data and auxiliary vectors is computed. By exploring the second-order statistics property of the covariance matrix, a threshold based on Gerschgorin radii of the smoothing correlation matrix is set to estimate the number of sources. Simulations and experimental results validate that MTDSS has an effective performance under the condition of the colored noise background and coherent sources, and MTDSS is robust with the correlated factor of signals and noise. View full abstract»

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  • Novel detection method for infrared small targets using weighted information entropy

    Page(s): 838 - 842
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1113 KB)  

    This paper presents a method for detecting the small infrared target under complex background. An algorithm, named local mutation weighted information entropy (LMWIE), is proposed to suppress background. Then, the grey value of targets is enhanced by calculating the local energy. Image segmentation based on the adaptive threshold is used to solve the problems that the grey value of noise is enhanced with the grey value improvement of targets. Experimental results show that compared with the adaptive Butterworth high-pass filter method, the proposed algorithm is more effective and faster for the infrared small target detection. View full abstract»

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  • Response characteristics of sonar receiver under intense sound pulse

    Page(s): 843 - 848
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2875 KB)  

    For anti-jamming and anti-countermeasure techniques of the sonar receiver, the response characteristics of the automatic gain control (AGC) circuit and the survivability of the prime circuit under strong interference are analyzed by simulations and experiments. An AGC simulation model based on the voltage control amplifier VCA810 prototype is proposed. Then static and dynamic simulations are realized with single frequency signal and linear frequency modulated (LFM) signal commonly used in the active sonar. Based on intense sound pulse (ISP) interference experiments, the real-time response characteristics of each module of the receiver are studied to verify the correctness of the model as well as the simulation results. Simulation and experiment results show that, under 252 dB/20 μs ISP interference, the specific sonar receiver will produce sustained cut top oscillation above 30 ms, which may affect the receiver and block the regular sonar signal. View full abstract»

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  • ISAR target recognition based on non-negative sparse coding

    Page(s): 849 - 857
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2487 KB)  

    Aiming at technical difficulties in feature extraction for the inverse synthetic aperture radar (ISAR) target recognition, this paper imports the concept of visual perception and presents a novel method, which is based on the combination of non-negative sparse coding (NNSC) and linear discrimination optimization, to recognize targets in ISAR images. This method implements NNSC on the matrix constituted by the intensities of pixels in ISAR images for training, to obtain non-negative sparse bases which characterize sparse distribution of strong scattering centers. Then this paper chooses sparse bases via optimization criteria and calculates the corresponding non-negative sparse codes of both training and test images as the feature vectors, which are input into k neighbors classifier to realize recognition finally. The feasibility and robustness of the proposed method are proved by comparing with the template matching, principle component analysis (PCA) and nonnegative matrix factorization (NMF) via simulations. View full abstract»

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  • Target detection using CDMA based passive bistatic radar

    Page(s): 858 - 865
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (6960 KB)  

    Recently, the code division multiple access (CDMA) waveform exists in the large area across the world. However, when using the CDMA system as the illuminator of opportunity for the passive bistatic radar (PBR), there exists interference not only from the base station used as the illuminator of opportunity but also from other base stations with the same frequency. And because in the CDMA system, the signal transmitted by each base station is different, using the direct signal of one base station can not cancel the interference from other base stations. A CDMA-based PBR using an 8-element linear array antenna as both the reference antenna and surveillance antenna is introduced. To deal with the interference in this PBR system, an adaptive temporal cancellation algorithm is used to remove the interference from the base station used as the illuminator of opportunity firstly. And then a robust adaptive beamformer is used to suppress the interference from other base stations. Finally, the preliminary experiment results demonstrate the feasibility of using CDMA signals as a radar waveform. View full abstract»

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  • Narrow-band tomographic radar imaging of precession cone targets

    Page(s): 866 - 874
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (3499 KB)  

    The principle and method of the narrow-band tomo-graphic radar imaging (NBTRI) of the precession cone target are studied. Firstly, the motion model and electromagnetic scattering characteristics of the precession cone target are introduced. Secondly, based on the traditional NBTRI algorithm, a novel narrowband tomography clean radar imaging (NBTCRI) algorithm is proposed to enhance the image quality of NBTRI results. In addition, the resolution performance of the NBTRI algorithm is analyzed. Finally, based on the ideal scattering point model, this paper discusses the relationship between the precession angle and the estimated target size from NBTRI results. By using the target's chamber data, NBTRI and NBTCRI results of the precession cone target are further analyzed, which indicates the effectiveness of the proposed method. View full abstract»

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  • Pre-processing for time domain image formation in SS-BSAR system

    Page(s): 875 - 880
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2203 KB)  

    A pre-processing procedure is designed for a space-surface bistatic synthetic aperture radar (SS-BSAR) system when a time domain image formation algorithm is employed. Three crucial technical issues relating to the procedure are fully discussed. Firstly, unlike image formation algorithms operating in the frequency domain, a time domain algorithm requires the accurate global navigation satellite system (GNSS) time and position. This paper proposes acquisition of this information using a time-and-spatial transfer with precise ephemeris and interpolation. Secondly, synchronization errors and compensation methods in SS-BSAR are analyzed. Finally, taking the non-ideal factors in the echo and the compatibility of image formation algorithms into account, a matched filter based on the minimum delay is constructed. Experimental result using real data suggest the pre-processing is functioning properly. View full abstract»

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  • Integration-centric approach to system readiness assessment based on evidential reasoning

    Page(s): 881 - 890
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1811 KB)  

    An integration-centric approach is proposed to handle inadequate information in the system readiness level (SRL) assessment using the evidential reasoning (ER) algorithm. Current SRL assessment approaches cannot be applied to handle inadequate information as the input. The ER-based approach is proposed to synthesize inadequate input information and an integration-centric perspective is applied to reduce the computational complexity. Two case studies are performed to validate the efficiency of the proposed approach. And these studies are also performed to study how the inadequate information will affect the assessment result. And the differences caused by the system's structure. The importance of the system's structure in the SRL assessment is demonstrated and the contributions made in this study are summarized as conclusions. View full abstract»

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  • Multi-attribute decision making method for air target threat evaluation based on intuitionistic fuzzy sets

    Page(s): 891 - 897
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (635 KB)  

    The function of the air target threat evaluation (TE) is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to address the issue of the TE in which the tactic features of the detected target are treated as evaluation attributes. Meanwhile, the intuitionistic fuzzy set (IFS) is employed to deal with information uncertainty in the TE process. Furthermore, on the basis of the entropy weight and inclusion-comparison probability, a hybrid TE method is developed. In order to accommodate the demands of naturalistic decision making, the proposed method allows air defense commanders to express their intuitive opinions besides incorporating into the threat features of the detected target. An illustrative example is provided to indicate the feasibility and advantage of the proposed method. View full abstract»

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  • Distributed consensus algorithm for networked Euler-Lagrange systems with self-delays and uncertainties

    Page(s): 898 - 905
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1135 KB)  

    A distributed coordinated consensus problem for multiple networked Euler-Lagrange systems is studied. The communication between agents is subject to time delays, unknown parameters and nonlinear inputs, but only with their states available for measurement. When the communication topology of the system is connected, an adaptive control algorithm with self-delays and uncertainties is suggested to guarantee global full-state synchronization that the difference between the agent's positions and velocities asymptotically converges to zero. Moreover, the distributed sliding-mode law is given for chaotic systems with nonlinear inputs to compensate for the effects of nonlinearity. Finally, simulation results show the effectiveness of the proposed control algorithm. View full abstract»

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  • Robust iterative learning control for nonlinear systems with measurement disturbances

    Page(s): 906 - 913
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    The iterative learning control (ILC) has been demonstrated to be capable of considerably improving the tracking performance of systems which are affected by the iteration-independent disturbance. However, the achievable performance is greatly degraded when iteration-dependent, stochastic disturbances are presented. This paper considers the robustness of the ILC algorithm for the nonlinear system in presence of stochastic measurement disturbances. The robust convergence of the P-type ILC algorithm is firstly addressed, and then an improved ILC algorithm with a decreasing gain is proposed. Theoretical analyses show that the proposed algorithm can guarantee that the tracking error of the nonlinear system tends to zero in presence of measurement disturbances. The analysis is also supported by a numerical example. View full abstract»

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  • Attitude sensor fault diagnosis based on Kalman filter of discrete-time descriptor system

    Page(s): 914 - 920
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (771 KB)  

    To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary state vector, the attitude measurement system subjected to the attitude sensor fault is modeled by the discrete-time descriptor system. The condition of estimability of such systems is given. And then a Kalman filter of the discrete-time descriptor system is established based on the methodology of the maximum likelihood estimation. With the descriptor Kalman filter, the state vector of the original system and sensor fault can be estimated simultaneously. The proposed method is able to estimate an abrupt sensor fault as well as the incipient one. Moreover, it is also effective in the multiple faults scenario. Simulations are conducted to confirm the effectiveness of the proposed method. View full abstract»

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  • Enhanced self-adaptive evolutionary algorithm for numerical optimization

    Page(s): 921 - 928
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1941 KB)  

    There are many population-based stochastic search algorithms for solving optimization problems. However, the universality and robustness of these algorithms are still unsatisfactory. This paper proposes an enhanced self-adaptive evolutionary algorithm (ESEA) to overcome the demerits above. In the ESEA, four evolutionary operators are designed to enhance the evolutionary structure. Besides, the ESEA employs four effective search strategies under the framework of the self-adaptive learning. Four groups of the experiments are done to find out the most suitable parameter values for the ESEA. In order to verify the performance of the proposed algorithm, 26 state-of-the-art test functions are solved by the ESEA and its competitors. The experimental results demonstrate that the universality and robustness of the ESEA outperform its competitors. View full abstract»

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  • Wavelet inverse scale space for image restoration

    Page(s): 929 - 935
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1489 KB)  

    This paper proposes a model for image restoration by combining the wavelet shrinkage and inverse scale space (ISS) method. The ISS is applied to the wavelet representation to modify the retained wavelet coefficients, and the coefficients smaller than the threshold are set to zero. The curvature term of the ISS can remove the edge artifacts and preserve sharp edges. For the multiscale interpretation of the ISS and the multiscale property of the wavelet representation, small details are preserved. This paper illustrates that the wavelet ISS model can be deduced from the wavelet based on a total variation minimization problem. A stopping criterion is obtained from this minimization in the sense of the Bregman distance in the wavelet domain. Numerical examples show the improvement for the image denoising with the proposed method in the sense of the signal to noise ratio and with fewer details remained in the residue. View full abstract»

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  • Importance measure of system reliability upgrade for multi-state consecutive k-out-of-n systems

    Page(s): 936 - 942
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (786 KB)  

    Importance measures in reliability systems are used to identify weak components in contributing to a proper function of the system. Traditional importance measures mainly concerned the changing value of the system reliability caused by the change of the reliability of the component, and seldom considered the joint effect of the probability distribution, improvement rate of the object component. This paper studies the rate of the system reliability upgrading with an improvement of the component reliability for the multi-state consecutive k-out-of-n system. To verify the multi-state consecutive k-out-of-n system reliability upgrading by improving one component based on its improvement rate, an increasing potential importance (IPI) and its physical meaning are described at first. Secondly, the relationship between the IPI and Birnbaum importance measures are discussed. And the IPI for some different improvement actions of the component is further discussed. Thirdly, the characteristics of the IPI are analyzed. Finally, an application to an oil pipeline system is given. View full abstract»

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  • Simulation method for reliability of TT&C mission with high redundancy and small time horizon

    Page(s): 943 - 948
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (721 KB)  

    The tracking, telemetry and command (TT&C) mission is extremely reliable for its characters of small time horizon and high redundancy. The combined forcing and failure biasing (CFFB) method that is usually used for simulating the unreliability of the highly dependable mission system seems not so efficient for the TT&C mission. The concept about the importance of failure transition is proposed based on the logical relationship between TT&C mission and its involved resources. Then, the importance is used for readjusting the transition rate of the failure transition when using the forcing and failure biasing during the simulation. Examples show that the improved CFFB method can evidently increase the occurrence of the TT&C mission failure event and decrease the sample variance. More redundancy of the TT&C mission leads to the improved CFFB method more efficient. View full abstract»

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  • Author index

    Page(s): 949 - 951
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    Freely Available from IEEE
  • Subject index

    Page(s): 952 - 956
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    Freely Available from IEEE

Aims & Scope

Journal of Systems Engineering and Electronics reports the latest developments and achievements in both theoretical and practical aspects of systems engineering, electronics and related research areas.

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Professor Rong Shi
Journal of Systems Engineering and Electronics