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Systems Engineering and Electronics, Journal of

Popular Articles (December 2014)

Includes the top 50 most frequently downloaded documents for this publication according to the most recent monthly usage statistics.
  • 1. Method for array gain and phase uncertainties calibration based on ISM and ESPRIT

    Page(s): 223 - 228
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1439 KB)  

    A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensors method (ISM), two well-calibrated sensors are added into the original array. By applying the principle of estimation of signal parameters via rotational invariance techniques (ESPRIT), the direction-of-arrivals (DOAs) and uncertainties can be estimated simultaneously through eigen-decomposition. Compared with the conventional ones, this new method has less computational complexity while has higher estimation precision, what's more, it can overcome the problem of ambiguity. Both theoretical analysis and computer simulations show the effectiveness of the proposed method. View full abstract»

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  • 2. Accuracy improvement of GPS/MEMS-INS integrated navigation system during GPS signal outage for land vehicle navigation

    Page(s): 256 - 264
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1524 KB)  

    To improve the reliability and accuracy of the global positioning system (GPS)/micro electromechanical system (MEMS)-inertial navigation system (INS) integrated navigation system, this paper proposes two different methods. Based on wavelet threshold denoising and functional coefficient autoregressive (FAR) modeling, a combined data processing method is presented for MEMS inertial sensor, and GPS attitude information is also introduced to improve the estimation accuracy of MEMS inertial sensor errors. Then the positioning accuracy during GPS signal short outage is enhanced. To improve the positioning accuracy when a GPS signal is blocked for long time and solve the problem of the traditional adaptive neuro-fuzzy inference system (ANFIS) method with poor dynamic adaptation and large calculation amount, a self-constructive ANFIS (SCANFIS) combined with the extended Kalman filter (EKF) is proposed for MEMS-INS errors modeling and predicting. Experimental road test results validate the efficiency of the proposed methods. View full abstract»

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  • 3. QPSO-based algorithm of CSO joint infrared super-resolution and trajectory estimation

    Page(s): 405 - 411
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1431 KB)  

    The midcourse ballistic closely spaced objects (CSO) create blur pixel-cluster on the space-based infrared focal plane, making the super-resolution of CSO quite necessary. A novel algorithm of CSO joint super-resolution and trajectory estimation is presented. The algorithm combines the focal plane CSO dynamics and radiation models, proposes a novel least square objective function from the space and time information, where CSO radiant intensity is excluded and initial dynamics (position and velocity) are chosen as the model parameters. Subsequently, the quantum-behaved particle swarm optimization (QPSO) is adopted to optimize the objective function to estimate model parameters, and then CSO focal plane trajectories and radiant intensities are computed. Meanwhile, the estimated CSO focal plane trajectories from multiple space-based infrared focal planes are associated and filtered to estimate the CSO stereo ballistic trajectories. Finally, the performance (CSO estimation precision of the focal plane coordinates, radiant intensities, and stereo ballistic trajectories, together with the computation load) of the algorithm is tested, and the results show that the algorithm is effective and feasible. View full abstract»

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  • 4. Innovations two-stage dual control

    Page(s): 78 - 82
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (782 KB)  

    A novel dual control method is proposed for the stochastic systems with unknown parameters, which converts the unsolvable dynamic programming problem into a tractable two-step ahead minimum variance control problem in a stochastic suboptimal view. Innovation variance is used to improve the learning effect, and the instant weight is introduced to reduce the influence of the future output estimation error on the system. Simulation results show the satisfactory performance of the new controller. View full abstract»

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  • 5. Optimal redundancy allocation for reliability systems with imperfect switching

    Page(s): 332 - 339
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (725 KB)  

    The problem of stochastically allocating redundant components to increase the system lifetime is an important topic of reliability. An optimal redundancy allocation is proposed, which maximizes the expected lifetime of a reliability system with subsystems consisting of components in parallel. The constraints are minimizing the total resources and the sizes of subsystems. In this system, each switching is independent with each other and works with probability p. Two optimization problems are studied by an incremental algorithm and dynamic programming technique respectively. The incremental algorithm proposed could obtain an approximate optimal solution, and the dynamic programming method could generate the optimal solution. View full abstract»

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  • 6. Reduced K-best sphere decoding algorithm based on minimum route distance and noise variance

    Page(s): 10 - 16
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (415 KB)  

    This paper focuses on reducing the complexity of K-best sphere decoding (SD) algorithm for the detection of uncoded multiple input multiple output (MIMO) systems. The proposed algorithm utilizes the threshold-pruning method to cut nodes with partial Euclidean distances (PEDs) larger than the threshold. Both the known noise value and the unknown noise value are considered to generate the threshold, which is the sum of the two values. The known noise value is the smallest PED of signals in the detected layers. The unknown noise value is generated by the noise power, the quality of service (QoS) and the signal-to-noise ratio (SNR) bound. Simulation results show that by considering both two noise values, the proposed algorithm makes an efficient reduction while the performance drops little. View full abstract»

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  • 7. Adaptive tracking controller using BP neural networks for a class of nonlinear systems

    Page(s): 598 - 604
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (911 KB)  

    An BP neural-network-based adaptive control (NNAC) design method is described whose aim is to control a class of partially unknown nonlinear systems. Making use of the online identification of BP neural networks, the results of the identification could be used into the parameters of the controller. Not only the strong robustness with respect to uncertain dynamics and nonlinearities can be obtained, but also the output tracking error between the plant output and the desired reference output can asymptotically converge to zero by Lyapunov theory in the process of this design method. And a simulation example is also presented to evaluate the effectiveness of the design. View full abstract»

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  • 8. Design and realization of synchronization circuit for GPS software receiver based on FPGA

    Page(s): 20 - 26
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1519 KB)  

    With research on the carrier phase synchronization and symbol synchronization algorithm of demodulation module, a synchronization circuit system is designed for GPS software receiver based on field programmable gate array (FPGA), and a series of experiment is done on the hardware platform. The result shows the all-digital synchronization and demodulation of GPS intermediate frequency (I F) signal can be realized and applied in embedded real-time GPS software receiver system. It is verified that the decision-directed joint tracking algorithm of carrier phase and symbol timing for received signals from GPS is reasonable. In addition, the loop works steadily and can be used for receiving GPS signals using synchronous demodulation. The synchronization circuit for GPS software receiver designed based on FPGA has the features of low cost, miniaturization, low power and realtime. Surely, it will become one of the development directions for GPS and even GNSS embedded real-time software receiver. View full abstract»

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  • 9. Self-alignment of full skewed RSINS: Observability analysis and full-observable Kalman filter

    Page(s): 104 - 114
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (417 KB)  

    Traditional orthogonal strapdown inertial navigation system (SINS) cannot achieve satisfactory self-alignment accuracy in the stationary base: taking more than 5 minutes and all the iner-tial sensors biases cannot get full observability except the up-axis accelerometer. However, the full skewed redundant SINS (RSINS) can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and all the inertial sensors biases are analyzed with the global perspective method: any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS (sub-SINS); the system state can be uniquely confirmed by the coupling connections of all the sub-SINSs; the attitude errors and random constant biases of all the inertial sensors are observable. However, the random noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the full-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, velocity, attitude errors of all the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy full skewed RSINS is simulated: the horizontal attitudes (pitch, roll) errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the full skewed RSINS, the self-alignment accuracy is greatly improved, meanwhile the self-alignment time is widely shortened. View full abstract»

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  • 10. Asymptotic and stable properties of general stochastic functional differential equations

    Page(s): 138 - 143
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (246 KB)  

    The asymptotic and stable properties of general stochastic functional differential equations are investigated by the multiple Lyapunov function method, which admits non-negative upper bounds for the stochastic derivatives of the Lyapunov functions, a theorem for asymptotic properties of the LaSalle-type described by limit sets of the solutions of the equations is obtained. Based on the asymptotic properties to the limit set, a theorem of asymptotic stability of the stochastic functional differential equations is also established, which enables us to construct the Lyapunov functions more easily in application. Particularly, the well-known classical theorem on stochastic stability is a special case of our result, the operator LV is not required to be negative which is more general to fulfil and the stochastic perturbation plays an important role in it. These show clearly the improvement of the traditional method to find the Lyapunov functions. A numerical simulation example is given to illustrate the usage of the method. View full abstract»

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  • 11. Collaborative optimization of maintenance and spare ordering of continuously degrading systems

    Page(s): 63 - 70
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (300 KB)  

    A collaborative optimization model for maintenance and spare ordering of a single-unit degrading system is proposed in this paper based on the continuous detection. A gamma distribution is used to model the material degradation. The degrading decrement after the imperfect maintenance action is assumed as a random variable normal distribution. This model aims to obtain the optimal maintenance policy and spare ordering point with the expected cost rate within system lifecycle as the optimization objective. The rationality and feasibility of the model are proved through a numerical example. View full abstract»

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  • 12. Leader-following consensus protocols for formation control of multi-agent network

    Page(s): 991 - 997
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (901 KB)  

    Two protocols are presented, which can make agents reach consensus while achieving and preserving the desired formation in fixed topology with and without communication time-delay for multi-agent network. First, the protocol without considering the communication time-delay is presented, and by using Lyapunov stability theory, the sufficient condition of stability for this multi-agent system is presented. Further, considering the communication time-delay, the effectiveness of the protocol based on Lyapunov-Krasovskii function is demonstrated. The main contribution of the proposed protocols is that, as well as the velocity consensus is considered, the formation control is concerned for multi-agent systems described as the second-order equations. Finally, numerical examples are presented to illustrate the effectiveness of the proposed protocols. View full abstract»

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  • 13. Shape control on probability density function in stochastic systems

    Page(s): 144 - 149
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (319 KB)  

    A novel strategy of probability density function (PDF) shape control is proposed in stochastic systems. The controller is designed whose parameters are optimally obtained through the improved particle swarm optimization algorithm. The parameters of the controller are viewed as the space position of a particle in particle swarm optimization algorithm and updated continually until the controller makes the PDF of the state variable as close as possible to the expected PDF. The proposed PDF shape control technique is compared with the equivalent linearization technique through simulation experiments. The results show the superiority and the effectiveness of the proposed method. The controller is excellent in making the state PDF follow the expected PDF and has the very small error between the state PDF and the expected PDF, solving the control problem of the PDF shape in stochastic systems effectively. View full abstract»

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  • 14. Multi-population and diffusion UMDA for dynamic multimodal problems

    Page(s): 777 - 783
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (468 KB)  

    In dynamic environments, it is important to track changing optimal solutions over time. Univariate marginal distribution algorithm (UMDA) which is a class algorithm of estimation of distribution algorithms attracts more and more attention in recent years. In this paper a new multi-population and diffusion UMDA (MDUMDA) is proposed for dynamic multimodal problems. The multi-population approach is used to locate multiple local optima which are useful to find the global optimal solution quickly to dynamic multi modal problems. The diffusion model is used to increase the diversity in a guided fashion, which makes the neighbor individuals of previous optimal solutions move gradually from the previous optimal solutions and enlarge the search space. This approach uses both the information of current population and the part history information of the optimal solutions. Finally experimental studies on the moving peaks benchmark are carried out to evaluate the proposed algorithm and compare the performance of MDUMDA and multi-population quantum swarm optimization (MQSO) from the literature. The experimental results show that the MDUMDA is effective for the function with moving optimum and can adapt to the dynamic environments rapidly. View full abstract»

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  • 15. Method of neural network modulation recognition based on clustering and Polak-Ribiere algorithm

    Page(s): 742 - 747
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (410 KB)  

    To improve the recognition rate of signal modulation recognition methods based on the clustering algorithm under the low SNR, a modulation recognition method is proposed. The characteristic parameter of the signal is extracted by using a clustering algorithm, the neural network is trained by using the algorithm of variable gradient correction (Polak-Ribiere) so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram. Simulation results show that the recognition rate based on this algorithm is enhanced over 30% compared with the methods that adopt clustering algorithm or neural network based on the back propagation algorithm alone under the low SNR. The recognition rate can reach 90% when the SNR is 4 dB, and the method is easy to be achieved so that it has a broad application prospect in the modulating recognition. View full abstract»

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  • 16. Radial acceleration estimation of multiple high maneuvering targets

    Page(s): 183 - 193
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (8208 KB)  

    The acceleration of a high maneuvering target in signal processing is helpful to enhance the performance of the tracker and facilitate the classification of targets. At present, most of the research on acceleration estimation is carried out in cases of a single target with time-frequency analysis methods such as fractional Fourier transform (FRFT), Hough-ambiguity transform (HAT), and Wigner-Ville distribution (WVD), which need to satisfy enough time duration and sampling theorem. Only one reference proposed a method of acceleration estimation for multiple targets based on modified polynomial phase transform (MPPT) in the linear frequency modulation (LFM) continuous-wave (CW) radar. The method of acceleration estimation for multiple targets in the pulse Doppler (PD) radar has not been reported so far. Compressive sensing (CS) has the advantage of sampling at a low rate and short duration without sacrificing estimation performance. Therefore, this paper proposes a new method of acceleration estimation for multiple maneuvering targets with the unknown number based on CS with pulse Doppler signals. Simulation results validate the effectiveness of the proposed method under several conditions with different duration, measurement numbers, signal to noise ratios (SNR), and regularization parameters, respectively. Simulation results also show that the performance of the proposed method is superior to that of FRFT and HAT in the condition of multiple targets. View full abstract»

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  • 17. Blind channel estimation for multiple antenna OFDM system subject to unknown carrier frequency offset

    Page(s): 721 - 727
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (368 KB)  

    The problem of channel estimation for multiple antenna orthogonal frequency division multiplexing (OFDM) systems subject to unknown carrier frequency offset (CFO) is addressed. Multiple signal classification (MUSIC)-like algorithm, which generally has been used for direction estimation or frequency estimation, is used for channel estimation in multiple antenna OFDM systems. A reduced dimensional (RD)-MUSIC based algorithm for channel estimation is proposed in multiple antenna OFDM systems with unknown CFO. The Cram??r-Rao bound (CRB) of channel estimation in multiple antenna OFDM systems with unknown CFO is derived. The proposed algorithm has a superior performance of channel estimation compared with the Capon method and the least squares method. View full abstract»

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  • 18. Single foggy image restoration based on spatial correlation analysis of dark channel prior

    Page(s): 688 - 696
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1998 KB)  

    Focusing on the degradation of foggy images, a restoration approach from a single image based on spatial correlation of dark channel prior is proposed. Firstly, the transmission of each pixel is estimated by the spatial correlation of dark channel prior. Secondly, a degradation model is utilized to restore the foggy image. Thirdly, the final recovered image, with enhanced contrast, is obtained by performing a post-processing technique based on just-noticeable difference. Experimental results demonstrate that the information of a foggy image can be recovered perfectly by the proposed method, even in the case of the abrupt depth changing scene. View full abstract»

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  • 19. Stability of stochastic switched epidemic systems with discrete or distributed time delay

    Page(s): 660 - 670
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1172 KB)  

    Stochastic switched epidemic systems with a discrete or distributed time delay are constructed and investigated. By the Lyapunov method and It??'s differential rule, the existence and uniqueness of global positive solution of each system is proved. And stability conditions of the disease-free equilibrium of the systems are obtained. Numerical simulations are presented to illustrate the results. View full abstract»

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  • 20. Simulation environments: Challenges for advancement

    Page(s): 12 - 24
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1735 KB)  

    A brief review of the basic terminology on simulation, simulation life-cycle activities such as model-based activities, behavior-oriented activities, and quality assurance activities is given. Then, the challenges and opportunities for the advancement of the state-of-the-art in simulation environments are discussed under the following headings: modelling environments, simulation environments, mixed simulation environments, and comprehensive simulation environments. View full abstract»

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  • 21. Multiobjective evolutionary algorithm for dynamic nonlinear constrained optimization problems

    Page(s): 204 - 210
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2098 KB)  

    A new method to solve dynamic nonlinear constrained optimization problems (DNCOP) is proposed. First, the time (environment) variable period of DNCOP is divided into several equal subperiods. In each subperiod, the DNCOP is approximated by a static nonlinear constrained optimization problem (SNCOP). Second, for each SNCOP, inspired by the idea of multiobjective optimization, it is transformed into a static bi-objective optimization problem. As a result, the original DNCOP is approximately transformed into several static bi-objective optimization problems. Third, a new multiobjective evolutionary algorithm is proposed based on a new selection operator and an improved nonuniformity mutation operator. The simulation results indicate that the proposed algorithm is effective for DNCOP. View full abstract»

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  • 22. Study on frequency selective surfaces with square loop slots

    Page(s): 11 - 16
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (888 KB)  

    To meet the need of curved FSS radome design, the theoretical and experimental investigations have been made on frequency selective surfaces with square loop slots. Expressions of basis function and transmission coefficient T are given. Factors are discussed which affect significantly the transmission characteristics. The measured T is greater than −0.51dB for normal incidence and T is greater than −1.0dB at oblique incidence of 60°. The measured results are quite satisfactory. View full abstract»

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  • 23. Effective path planning method for low detectable aircraft

    Page(s): 784 - 789
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1906 KB)  

    To utilizing the characteristic of radar cross section (RCS) of the low detectable aircraft, a special path planning algorithm to eluding radars by the variable RCS is presented. The algorithm first gives the RCS changing model of low detectable aircraft, then establishes a threat model of a ground-based air defense system according to the relations between RCS and the radar range coverage. By the new cost functions of the flight path, which consider both factors of the survival probability and the distance of total route, this path planning method is simulated based on the Dijkstra algorithm, and the planned route meets the flight capacity constraints. Simulation results show that using the effective path planning algorithm, the low detectable aircraft can give full play to its own advantage of stealth to achieve the purpose of silent penetration. View full abstract»

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  • 24. Robust fault diagnosis with disturbance rejection and attenuation for systems with multiple disturbances

    Page(s): 135 - 140
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (965 KB)  

    The fault diagnosis problem is investigated for a class of nonlinear neutral systems with multiple disturbances. Time-varying faults are considered and multiple disturbances are supposed to include the unknown disturbance modeled by an exo-system and norm bounded uncertain disturbance. A nonlinear disturbance observer is designed to estimate the modeled disturbance. Then, the fault diagnosis observer is constructed by integrating disturbance observer with disturbance attenuation and rejection performances. The augmented Lyapunov functional approach, which involves the tuning parameter and slack variable, is applied to make the solution of inequality more flexible. Finally, applications for a two-link robotic manipulator system are given to show the efficiency of the proposed approach. View full abstract»

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  • 25. Novel imaging methods of stepped frequency radar based on compressed sensing

    Page(s): 47 - 56
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (561 KB)  

    The theory of compressed sensing (CS) provides a new chance to reduce the data acquisition time and improve the data usage factor of the stepped frequency radar system. In light of the sparsity of radar target reflectivity, two imaging methods based on CS, termed the CS-based 2D joint imaging algorithm and the CS-based 2D decoupled imaging algorithm, are proposed. These methods incorporate the coherent mixing operation into the sparse dictionary, and take random measurements in both range and azimuth directions to get high resolution radar images, thus can remarkably reduce the data rate and simplify the hardware design of the radar system while maintaining imaging quality. Experiments from both simulated data and measured data in the anechoic chamber show that the proposed imaging methods can get more focused images than the traditional fast Fourier transform method. Wherein the joint algorithm has stronger robustness and can provide clearer inverse synthetic aperture radar images, while the decoupled algorithm is computationally more efficient but has slightly degraded imaging quality, which can be improved by increasing measurements or using a robuster recovery algorithm nevertheless. View full abstract»

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  • 26. Fast consensus seeking for multi-agent systems

    Page(s): 534 - 539
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2075 KB)  

    For multi-agent systems based on the local information, the agents automatically converge to a common consensus state and the convergence speed is determined by the algebraic connectivity of the communication network. To study fast consensus seeking problems of multi-agent systems in undirected networks, a consensus protocol is proposed which considers the average information of the agents' states in a certain time interval, and a consensus convergence criterion for the system is obtained. Based on the frequency-domain analysis and algebra graph theory, it is shown that if the time interval is chosen properly, then requiring the same maximum control effort the proposed protocol reaches consensus faster than the standard consensus protocol. Simulations are provided to demonstrate the effectiveness of these theoretical results. View full abstract»

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  • 27. Identification of linear continuous-time system using wavelet modulating filters

    Page(s): 270 - 277
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1158 KB)  

    An approach to identification of linear continuous-time system is studied with modulating functions. Based on wavelet analysis theory, the multi-resolution modulating functions are designed, and the corresponding filters have been analyzed. Using linear modulating filters, we can obtain an identification model that is parameterized directly in continuous-time model parameters. By applying the results from discrete-time model identification to the obtained identification model, a continuous-time estimation method is developed. Considering the accuracy of parameter estimates, an instrumental variable (IV) method is proposed, and the design of modulating integral filter is discussed. The relationship between the accuracy of identification and the parameter of modulating filter is investigated, and some points about designing Gaussian wavelet modulating function are outlined. Finally, a simulation study is also included to verify the theoretical results. View full abstract»

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  • 28. Prediction method of vessel maintenance outlay based on the BP neural network

    Page(s): 61 - 70
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1942 KB)  

    With the development of technology, the performance of vessel equipment is improved, the structure is more complicated, the automation level is enhanced, the source needed by maintenance is increased and the outlay is rising day by day. For these questions, this paper analyzes the factors that affect the outlay of equipment maintenance, and describes the computational principle of the BP (back propagation) artificial neural network and its applications in the maintenance of naval ship and craft. Finally, a dynamic investment prediction model of outlay for the military equipment maintenance is designed. It is important for decreasing the entire ilfe period outlay and drawing up the maintenance plan and programming to analyze the position and action of maintenance outlay in entire life period outlay. View full abstract»

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  • 29. DS-CDMA system outer loop power control and improvement for multi-service

    Page(s): 453 - 460
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2680 KB)  

    When a new user accesses the CDMA system, the load will change drastically, and therefore, the advanced outer loop power control (OLPC) technology has to be adopted to enrich the target signal interference ratio (SIR) and improve the system performance. The existing problems about DS-CDMA outer loop power control for multi-service are introduced and the power control theoretical model is analyzed. System simulation is adopted on how to obtain the theoretical performance and parameter optimization of the power control algorithm. The OLPC algorithm is improved and the performance comparisons between the old algorithm and the improved algorithm are given. The results show good performance of the improved OLPC algorithm and prove the validity of the improved method for multi-service. View full abstract»

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  • 30. Coordinate registration algorithms for over-the-horizon radar

    Page(s): 725 - 730
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1740 KB)  

    Different from the other conventional radars, the over the horizon radar (OTHR) faces complicated nonlinear coordinate transform due to electromagnetic wave propagation and reflection in ionospheres. A significant problem is the phenomenon of multi-path propagation. Considering it, the coordinate registration algorithms of planar measurement model and spherical measurement model are respectively derived in detail. Noticeably, a new transforming expression of apparent azimuth and an integrated form of transforming expressions from measurement vector to ground state vector in coordinate registration algorithm of spherical measurement model are proposed. And then simulations are made to verify the correctness of the proposed algorithms and expression. Besides this, the transforming error rate of slant range, Doppler and apparent azimuth of the two kinds of models are given respectively. Then the quantitative analysis of error rate is also given. It can be drawn a conclusion that the coordinate registration algorithms of planar measurement model and spherical measurement model are both correct. View full abstract»

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  • 31. Person-independent expression recognition based on person-similarity weighted expression feature

    Page(s): 118 - 126
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1263 KB)  

    A new method to extract person-independent expression feature based on higher-order singular value decomposition (HOSVD) is proposed for facial expression recognition. Based on the assumption that similar persons have similar facial expression appearance and shape, the person-similarity weighted expression feature is proposed to estimate the expression feature of test persons. As a result, the estimated expression feature can reduce the influence of individuals caused by insufficient training data, and hence become less person-dependent. The proposed method is tested on Cohn-Kanade facial expression database and Japanese female facial expression (JAFFE) database. Person-independent experimental results show the superiority of the proposed method over the existing methods. View full abstract»

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  • 32. Quorum systems for intrusion-tolerance based on trusted timely computing base

    Page(s): 168 - 174
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (877 KB)  

    Quorum systems have been used to solve the problem of data consistency in distributed fault-tolerance systems. But when intrusions occur, traditional quorum systems have some disadvantages. For example, synchronous quorum systems are subject to DOS attacks, while asynchronous quorum systems need a larger system size (at least 3ƒ+ 1 for generic data, and ƒ fewer for self-verifying data). In order to solve the problems above, an intrusion-tolerance quorum system (ITQS) of hybrid time model based on trust timely computing base is presented (TTCB). The TTCB is a trust secure real-time component inside the server with a well defined interface and separated from the operation system. It is in the synchronous communication environment while the application layer in the server deals with read-write requests and executes update-copy protocols asynchronously. The architectural hybridization of synchrony and asynchrony can achieve the data consistency and availability correctly. We also build two kinds of ITQSes based on TTCB, i.e., the symmetrical and the asymmetrical TTCB quorum systems. In the performance evaluations, we show that TTCB quorum systems are of smaller size, lower load and higher availability. View full abstract»

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  • 33. Modified joint probabilistic data association with classification-aided for multitarget tracking

    Page(s): 434 - 439
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1324 KB)  

    Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are similar for different closely spaced targets, there is ambiguity in using the kinematic information alone; the correct association probability will decrease in conventional joint probabilistic data association algorithm and track coalescence will occur easily. A modified algorithm of joint probabilistic data association with classification-aided is presented, which avoids track coalescence when tracking multiple neighboring targets. Firstly, an identification matrix is defined, which is used to simplify validation matrix to decrease computational complexity. Then, target class information is integrated into the data association process. Performance comparisons with and without the use of class information in JPDA are presented on multiple closely spaced maneuvering targets tracking problem. Simulation results quantify the benefits of classification-aided JPDA for improved multiple targets tracking, especially in the presence of association uncertainty in the kinematic measurement and target maneuvering. Simulation results indicate that the algorithm is valid. View full abstract»

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  • 34. Dwell scheduling algorithm for multifunction phased array radars based on the scheduling gain

    Page(s): 479 - 485
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1878 KB)  

    A real-time dwell scheduling model, which takes the time and energy constraints into account is founded from the viewpoint of scheduling gain. Scheduling design is turned into a nonlinear programming procedure. The real-time dwell scheduling algorithm based on the scheduling gain is presented with the help of two heuristic rules. The simulation results demonstrate that compared with the conventional adaptive scheduling method, the algorithm proposed not only increases the scheduling gain and the time utility but also decreases the task drop rate. View full abstract»

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  • 35. Local spatial properties based image interpolation scheme using SVMs

    Page(s): 618 - 623
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (866 KB)  

    Image interpolation plays an important role in image process applications. A novel support vector machines (SVMs) based interpolation scheme is proposed with increasing the local spatial properties in the source image as SVMs input patterns. After the proper neighbor pixels region is selected, trained support vectors are obtained by training SVMs with local spatial properties that include the average of the neighbor pixels gray values and the gray value variations between neighbor pixels in the selected region. The support vector regression machines are employed to estimate the gray values of unknown pixels with the neighbor pixels and local spatial properties information. Some interpolation experiments show that the proposed scheme is superior to the linear, cubic, neural network and other SVMs based interpolation approaches. View full abstract»

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  • 36. Comparison between two concepts of angular glint: General considerations

    Page(s): 635 - 642
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (365 KB)  

    Angular glint can be interpreted as a distortion of the radar echo signal phase front, or alternatively, a tilt of the direction of energy flow from the radial direction. As the complementarities and support of argumentation in our previous work, a general discussion about two concepts of angular glint is made based on electromagnetic theory to demonstrate that these two concepts are equivalent when geometrical optics approximation is used and the receiving antenna is linearly polarized. View full abstract»

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  • 37. Volterra series based predistortion for broadband RF power amplifiers with memory effects

    Page(s): 666 - 671
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (303 KB)  

    RF power amplifiers (PAs) are usually considered as memoryless devices in most existing predistortion techniques. However, in broadband communication systems, such as WCDMA, the PA memory effects are significant, and memory less predistortion cannot linearize the PAs effectively. After analyzing the PA memory effects, a novel predistortion method based on the simplified Volterra series is proposed to linearize broadband RF PAs with memory effects. The indirect learning architecture is adopted to design the predistortion scheme and the recursive least squares algorithm with forgetting factor is applied to identify the parameters of the predistorter. Simulation results show that the proposed predistortion method can compensate the nonlinear distortion and memory effects of broadband RF PAs effectively. View full abstract»

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  • 38. Posterior Cramer-Rao lower bounds for multitarget bearings-only tracking

    Page(s): 1127 - 1132
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (279 KB)  

    Usually, only the Cramer-Rao lower bound (CRLB) of single target is taken into consideration in the state estimate of passive tracking systems. As for the case of multitarget, there are few works done due to its complexity. The recursion formula of the posterior Cramer-Rao lower bound (PCRLB) in multitarget bearings-only tracking with the three kinds of data association is presented. Meanwhile, computer simulation is carried out for data association. The final result shows that the accuracy probability of data association has an important impact on the PCRLB. View full abstract»

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  • 39. On the improvement of the mutual coupling compensation in DOA estimation

    Page(s): 1 - 6
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (890 KB)  

    A new and exact calculation method for the mutual impedance matrix of receiving arrays is proposed. The mutual impedance matrix is derived from electromagnetic boundary conditions and can be used to relate the coupling free open-circuit voltages, instead of the conventional ones, to the measured voltages. A remarkable improvement on compensation for the coupling effects is shown in the direction finding applications, while a simple relationship between measured terminal voltages and the coupling free voltages is remained. View full abstract»

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  • 40. Posterior Cramer-Rao lower bounds for bearing-only tracking

    Page(s): 27 - 32
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (844 KB)  

    In the state estimation of passive tracking systems, the traditional approximate expression for the Cramer-Rao lower bound (CRLB) does not take two factors into consideration, that is, measurement origin uncertainty and state noise. Such treatment is only valid in ideal situation but it is not feasible in actual situation. In this article, considering the two factors, the posterior Cramer-Rao lower bound (PCRLB) recursion expression for the error of bearing-only tracking is derived. Then, further analysis is carried out on the PCRLB. According to the final result, there are four main parameters that play a role in the performance of the PCRLB, that is, measurement noise, detection probability, state noise and clutter density, amongst which the first two have greater impact on the performance of the PCRLB than the others. View full abstract»

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  • 41. Grover quantum searching algorithm based on weighted targets

    Page(s): 363 - 369
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (304 KB)  

    The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example. View full abstract»

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  • 42. Novel l2-l controller design for LPV discrete time-delay systems

    Page(s): 128 - 133
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (796 KB)  

    One of the first attempts to derive energy-to-peak performance criteria and state-feedback controller design problem for linear parameter-varying discrete time systems with time delay is provided. Firstly, we present a parameterdependent l2-l performance criterion using a parameter-dependent Lyapunov function. Upon the conditions addressed, an improved parameter-dependent l2-l performance criterion is established by the introduction of a slack variable, which exhibits a kind of decoupling between Lyapunov functions and system matrices. This kind of decoupling enables us to obtain more easily tractable conditions for analysis and synthesis problems. Then, the corresponding parameter-dependent state-feedback controller design is investigated upon these performance criteria, with sufficient conditions obtained for the existence of admissible controllers in terms of parameterized linear matrix inequalities. Finally, a numerical example is provided to illustrate the feasibility and advantage of the proposed controller design procedure. View full abstract»

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  • 43. Adaptive modified hough transform track initiator for HFSWR tracking of fast and small targets

    Page(s): 316 - 320
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (938 KB)  

    High frequency surface wave radar (HFSWR) is well proved to have over the horizon (OTH) detection capability to weak aerial targets, such as concealed airplanes or cruise missiles. The most important problem of detection of fast and small targets using HFSWR is earlier warning, i. e. enlargement of detection range of targets. Therefore, the detection threshold should be decreased as low as possible, but numerous false alarms are brought about at the same time. On this condition, conventional track initiation techniques, which normally require the probability of false alarm to be at the level of 10–6, will initiate enormous false tracks and lead to abnormal operation of tracking system. An adaptive modified hough transform (AMHT) track initiator is proposed accordingly and the relation of detection range to the performance of track initiator is analyzed in this paper. Simulations are performed to confirm the capability of track initiation to fast and small targets in dense clutter by AMHT track initiator. The tolerable probability of false alarm of detector can reach the level of 10−3. And it performs better than track initiator based on modified hough transform (MHT). View full abstract»

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  • 44. Grey Markov chain and its application in drift prediction model of FOGs

    Page(s): 388 - 393
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1041 KB)  

    A novel grey Markov chain predictive model is discussed to reduce drift influence on the output of fiber optical gyroscopes (FOGs) and to improve FOGs' measurement precision. The proposed method possesses advantages of grey model and Markov chain. It makes good use of dynamic modeling idea of the grey model to predict general trend of original data. Then according to the trend, states are divided so that it can overcome the disadvantage of high computational cost of state transition probability matrix in Markov chain. Moreover, the presented approach expands the applied scope of the grey model and makes it be fit for prediction of random data with bigger fluctuation. The numerical results of real drift data from a certain type FOG verify the effectiveness of the proposed grey Markov chain model powerfully. The Markov chain is also investigated to provide a comparison with the grey Markov chain model. It is shown that the hybrid grey Markov chain prediction model has higher modeling precision than Markov chain itself, which prove this proposed method is very applicable and effective. View full abstract»

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  • 45. New algorithm for infrared small target image enhancement based on wavelet transform and human visual properties

    Page(s): 268 - 273
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1232 KB)  

    The key to the wavelet based denoising techniques is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet domain Inclusive-OR denoising algorithm (WDIDA), which distinguishes the wavelet coefficients belonging to image or noise by considering their phases and modulus maxima simultaneously. Using this new algorithm, the denoising effects are improved and the computation time is reduced. Furthermore, in order to enhance the edges of the image but not magnify noise, a contrast nonlinear enhancing algorithm is presented according to human visual properties. Compared with traditional enhancing algorithms, the algorithm that we proposed has a better noise reducing performance, preserving edges and improving the visual quality of images. View full abstract»

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  • 46. Survey of the research on dynamic weapon-target assignment problem

    Page(s): 559 - 565
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1398 KB)  

    The basic concepts and models of weapon-target assignment (WTA) are introduced and the mathematical nature of the WTA models is also analyzed. A systematic survey of research on WTA problem is provided. The present research on WTA is focused on models and algorithms. In the research on models of WTA, the static WTA models are mainly studied and the dynamic WTA models are not fully studied in deed. In the research on algorithms of WTA, the intelligent algorithms are often used to solve the WTA problem. The small scale of static WTA problems has been solved very well, however, the large scale of dynamic WTA problems has not been solved effectively so far. Finally, the characteristics of dynamic WTA are analyzed and directions for the future research on dynamic WTA are discussed. View full abstract»

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  • 47. Novel algorithm for distributed replicas management based on dynamic programming

    Page(s): 669 - 672
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (698 KB)  

    Replicas can improve the data reliability in distributed system. However, the traditional algorithms for replica management are based on the assumption that all replicas have the uniform reliability, which is inaccurate in some actual systems. To address such problem, a novel algorithm is proposed based on dynamic programming to manage the number and distribution of replicas in different nodes. By using Markov model, replicas management is organized as a multi-phase process, and the recursion equations are provided. In this algorithm, the heterogeneity of nodes, the expense for maintaining replicas and the engaged space have been considered. Under these restricted conditions, this algorithm realizes high data reliability in a distributed system. The results of case analysis prove the feasibility of the algorithm. View full abstract»

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  • 48. Distribution-based CFAR detectors in SAR images

    Page(s): 717 - 721
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1087 KB)  

    As traditional two-parameter constant false alarm rate (CFAR) target detection algorithms in SAR images ignore target distribution, their performances are not the best or near best. As the resolution of SAR images increases, small targets present more pixels in SAR images. So the target distribution is of much significance. Distribution-based CFAR detection algorithm is presented. We unite the pixels around the test cell, and estimate the distribution of test cell by them. Generalized Likelihood Ratio Test (GLRT) is used to deduce the detectors. The performance of the distribution-based CFAR (DBCFAR) detectors is analyzed theoretically. False alarms of DBCFAR detection are fewer than those of CFAR at the same detection rate. Finally experiments are done and the results show the performance of DBCFAR is out of conventional CFAR. False alarms of DBCFAR detection are concentrated while those of CFAR detection are dispersive. View full abstract»

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  • 49. Unscented Kalman filter for SINS alignment

    Page(s): 327 - 333
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (898 KB)  

    In order to improve the filter accuracy for the nonlinear error model of strapdown inertial navigation system (SINS) alignment, Unscented Kalman Filter (UKF) is presented for simulation with stationary base and moving base of SINS alignment. Simulation results show the superior performance of this approach when compared with classical suboptimal techniques such as extended Kalman filter in cases of large initial misalignment. The UKF has good performance in case of small initial misalignment. View full abstract»

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  • 50. Image completion algorithm based on texture synthesis

    Page(s): 385 - 391
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (3570 KB)  

    A new algorithm is proposed for completing the missing parts caused by the removal of foreground or background elements from an image of natural scenery in a visually plausible way. The major contributions of the proposed algorithm are: (1) for most natural images, there is a strong orientation of texture or color distribution. So a method is introduced to compute the main direction of the texture and complete the image by limiting the search to one direction to carry out image completion quite fast; (2) there exists a synthesis ordering for image completion. The searching order of the patches is defined to ensure the regions with more known information and the structures should be completed before filling in other regions; (3) to improve the visual effect of texture synthesis, an adaptive scheme is presented to determine the size of the template window for capturing the features of various scales. A number of examples are given to demonstrate the effectiveness of the proposed algorithm. View full abstract»

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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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Meet Our Editors

Editor-in-Chief
Professor Rong Shi
Journal of Systems Engineering and Electronics