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.
The controllability and observability of networked control systems are studied. Aiming at the networked control system with time-varying delay, the sufficient and necessary conditions for complete controllability and complete observability of the system are presented, respectively. Because of Markov characteristic of the network-induced delay, in terms of stochastic theory, a sufficient and necessary condition for completely mean value controllability of networked control systems is obtained. Further, the conditions that the controllability and observability of networked control systems are equivalent to the initial time-invariant system are given. Controllability and observability realization indexes are also discussed, respectively. The numerical example demonstrates the effectiveness of the proposed theory.
In the future lunar exploration programs of China, soft landing, sampling and returning will be realized. For lunar explorers such as Rovers, Landers and Ascenders, the inertial navigation system (INS) will be used to obtain high-precision navigation information. INS propagates position, velocity and attitude by integration of sensed accelerations, so initial alignment is needed before INS can work properly. However, traditional ground-based initial alignment methods cannot work well on the lunar surface because of its low rotation rate (0.55?/h). For solving this problem, a new autonomous INS initial alignment method assisted by celestial observations is proposed, which uses star observations to help INS estimate its attitude, gyroscopes drifts and accelerometer biases. Simulations show that this new method can not only speed up alignment, but also improve the alignment accuracy. Furthermore, the impact factors such as initial conditions, accuracy of INS sensors, and accuracy of star sensor on alignment accuracy are analyzed in details, which provide guidance for the engineering applications of this method. This method could be a promising and attractive solution for lunar explorer’s initial alignment.
A modified pseudo-noise (PN) code regeneration method is proposed to improve the clock tracking accuracy without impairing the code acquisition time performance. Thus, the method can meet the requirement of high accuracy ranging measurements in short time periods demanded by radio-science missions. The tracking error variance is derived by linear analysis. For some existing PN codes, which can be acquired rapidly, the tracking error variance performance of the proposed method is about 2.6 dB better than that of the JPL scheme (originally proposed by Jet Propulsion Laboratory), and about 1.5 dB better than that of the traditional double loop scheme.
The problem of robustifying linear quadratic regulators (LQRs) for a class of uncertain affine nonlinear systems is considered. First, the exact linearization technique is used to transform an uncertain nonlinear system into a linear one and an optimal LQR is designed for the corresponding nominal system. Then, based on the integral sliding mode, a design approach to robustifying the optimal regulator is studied. As a result, the system exhibits global robustness to uncertainties and the ideal sliding mode dynamics is the same as that of the optimal LQR for the nominal system. A global robust optimal sliding mode control (GROSMC) is realized. Finally, a numerical simulation is demonstrated to show the effectiveness and superiority of the proposed algorithm compared with the conventional optimal LQR.
To improve the error performance and the resource utilization of cooperative systems, the optimum resource allocation, i.e., power allocation and partner choice, for an adaptive decode-and-forward (DF) cooperative diversity system based on quadrature modulation is investigated. The closed-form expression of the bit error rate (BER) system performance is derived and an optimal power allocation (OPA) algorithm is proposed to optimize the power allocation between the local and relayed signals under the minimum BER criterion. Based on the OPA algorithm, a partner choice strategy is proposed to determine the partner locations specified by various cooperation gains. Simulation results show that the proposed resource optimization algorithms are superior to the unoptimized algorithms by significantly reducing the BER and improving the cooperative gain, which is useful to simplify the practical partner choice process.
An indoor location system based on multilayer artificial neural network (ANN) with area division is proposed. The characteristics of recorded signal strength (RSS), or signal to noise ratio (SNR) from each available access points (APs), are utilized to establish the radio map in the off-line phase. And in the on-line phase, the two or three dimensional coordinates of mobile terminals (MTs) are estimated according to the similarity between the new recorded RSS or SNR and fingerprints pre-stored in radio map. Although the feed-forward ANN with three layers is sufficient to describe any nonlinear mapping relationship between inputs and outputs with finite discontinuous points, the efficient inputs for better training performances are difficult to be determined because of complex and dynamic indoor environment. Then, the discussion of distance relativity for different signal characteristics and optimal strategies for multi-mode phenomenon avoidance is presented. And also, the feasibility and effectiveness of this method are verified based on the experimental comparison with normal ANN without area division, K-nearest neighbor (KNN) and probability methods in typical office environment.
Calibration is a processing procedure for across-track interferometric synthetic aperture radar (InSAR) to achieve an accurate three-dimensional location. A calibration technique, called weighted joint calibration, for the generation of wide-area geocoded digital elevation models (DEMs) is proposed. It calibrates multiple InSAR scenes simultaneously, and allows reducing the number of required ground control points (GCPs) by using tie points (TPs). This approach may ensure the continuity of threedimensional location among adjacent scenes, which is necessary for mosaic and fusion of data coming from different scenes. In addition, it introduces weights to calibration to discriminate GCPs and TPs with different coherences and locations. This paper presents the principles and methodology of this weighted joint calibration technique and illustrates its successful application in airborne In-SAR data.
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.
A trajectory shaping guidance law based on virtual angle (TSGLBVA) is proposed for a re-entry vehicle with the constraints of terminal impact angles and their time derivatives. In the view of differential properties of the maneuvering trajectory, a virtual angle and a virtual radius are defined. Also, the shaping trajectory of the vehicle is established by the polynomials of the virtual angle. Then, four optimized parameters are selected according to the theorem of parameters transformation presented in this paper. Finally, a convergent variant of the Nelder-Mead algorithm is adopted to obtain the reference trajectory, and a trajectory feedback tracking guidance law is designed. The simulation results demonstrate that the TSGLBVA ensures the re-entry vehicle to impact a target precisely from a specified direction with small terminal load factor command, as well as to obtain a maximum or constrained terminal velocity according to various requirements.
Data envelopment analysis (DEA) is a mathematical programming approach to appraise the relative efficiencies of peer decision-making unit (DMU), which is widely used in ranking DMUs. However, almost all DEA-related ranking approaches are based on the self-evaluation efficiencies. In other words, each DMU chooses the weights it prefers to most, so the resulted efficiencies are not suitable to be used as ranking criteria. Therefore this paper proposes a new approach to determine a bundle of common weights in DEA efficiency evaluation model by introducing a multi-objective integer programming. The paper also gives the solving process of this multi-objective integer programming, and the solution is proven a Pareto efficient solution. The solving process ensures that the obtained common weight bundle is acceptable by a great number of DMUs. Finally a numeral example is given to demonstrate the approach.
A novel H∞ tracking-based decentralized indirect adaptive output feedback fuzzy controller for a class of uncertain large-scale nonlinear systems is developed. By virtue of the proper filtering of the observation error dynamics, the observer-based decentralized indirect adaptive fuzzy control scheme is presented for a class of large-scale nonlinear systems using the combination of H∞ tracking technique, a fuzzy adaptive observer and fuzzy inference systems. The output feedback and adaptation mechanisms are both robust and implementable indeed owing to their freedom from the unavailable observation error vector. All the signals of the closed-loop largescale system are guaranteed to stay uniformly bounded and the output errors take on H∞ tracking performance. Simulation results substantiate the effectiveness of the proposed scheme.
The angular glint in the near field plays an important role on radar tracking errors. To predict it more efficiently for electrically large targets, a new method based on graphical electromagnetic computing (GRECO) is proposed. With the benefit of the graphic card, the GRECO prediction method is faster and more accurate than other methods. The proposed method at the first time considers the special case that the targets cannot be completely covered by radar beams, which makes the prediction of radar tracking errors more self-contained in practical circumstances. On the other hand, the process of the scattering center extraction is omitted, resulting in possible angular glint prediction in real time. Comparisons between the simulation results and the theoretical ones validate its correctness and value to academic research and engineering applications.
A class of latent ancestral graph for modelling the dependence structure of structural vector autoregressive(VAR) model affected by latent variables is proposed.The graphs are mixed graphs with possibly two kind of edges,namely directed and bidirected edges.The vertex set denotes random variables at dif- ferent times.In Gaussian case,the latent ancestral graph leads to a simple parameterization model.A modified iterative conditional fitting algorithm is presented to obtain maximum likelihood esti- mation of the parameters.Furthermore,a log-likelihood criterion is used to select the most appropriate models.Simulations are performed using illustrative examples and results are provided to demonstrate the validity of the methods.
This paper deals with the problem of stability for systems with delay varying in an interval. A new Lyapunov functional, which makes use of the information of both the lower and upper bounds of the interval time-varying delay, is proposed to derive some new stability criteria. Furthermore, the relationship of the time-varying delay and its lower bound and upper bound is taken into account. As a result, some less conservative delay-dependent stability criteria are obtained without ignoring any useful information in the derivative of Lyapunov functional, which are established in the forms of linear matrix inequalities. Numerical examples are provided to show that the obtained results are better than existing ones.
The differential chaotic shift keying (DCSK) communication in multiple input multiple output (MIMO) multipath fading channels is considered. A simple MIMO-DCSK communication scheme based on orthogonal multi-codes (OMCs) and equal gain combination (EGC) is proposed, in which OMCs are used to spread the same information bit at each transmitting antenna and the information bit is detected by EGC at receiving antenna. The OMCs are constructed from one chaotic sequence by means of othogonal space-time block coding (OSTBC). The output signal-to-noise ratio (SNR) after EGC is given based on central limit theory (CLT), and it can effectively exploit the spatial diversity of the underlying MIMO system. Simulation results show that the full spatial diversity gain is achieved without channel estimation in the MIMO-DCSK communication scheme and it performs better than MC-EGC for a large number of transmitting antennas.
To validate the potential space-time adaptive processing (STAP) algorithms for airborne bistatic radar clutter suppression under nonstationary and non-Gaussian clutter environments, a statistically non-Gaussian, spacetime clutter model in varying bistatic geometrical scenarios is presented. The inclusive effects of the model contain the range dependency of bistatic clutter spectrum and clutter power variation in range-angle cells. To capture them, a new approach to coordinate system conversion is initiated into formulating bistatic geometrical model, and the bistatic non-Gaussian amplitude clutter representation method based on a compound model is introduced. The veracity of the geometrical model is validated by using the bistatic configuration parameters of multi-channel airborne radar measurement (MCARM) experiment. And simulation results manifest that the proposed model can accurately shape the space-time clutter spectrum tied up with specific airborne bistatic radar scenario and can characterize the heterogeneity of clutter amplitude distribution in practical clutter environments.
The frequency-modulated continuous-wave (FMCW) synthetic aperture radar (SAR) is a light-weight, cost-effective, high-resolution imaging radar, which is suitable for a small flight platform. The signal model is derived for FMCW SAR used in unmanned aerial vehicles (UAV) reconnaissance and remote sensing. An appropriate algorithm is proposed. The algorithm performs the range cell migration correction (RCMC) for continuous non-chirped raw data using the energy invariance of the scaling of a signal in the scale domain. The azimuth processing is based on step transform without geometric resampling operation. The complete derivation of the algorithm is presented. The algorithm performance is shown by simulation results.
The uncertainty of observers’ positions can lead to significantly degrading in source localization accuracy. This paper proposes a method of using self-location for calibrating the positions of observer stations in source localization to reduce the errors of the observer positions and improve the accuracy of the source localization. The relative distance measurements of the two coordinative observers are used for the linear minimum mean square error (LMMSE) estimator. The results of computer simulations prove the feasibility and effectiveness of the proposed method. With the general estimation errors of observers’ positions, the MSE of the source localization with self-location calibration, which is significantly lower than that without self-location calibration, is approximating to the Cramer-Rao lower bound (CRLB).
The problem of the robust D-stability analysis for linear systems with parametric uncertainties is addressed. For matrix polytopes, new conditions via the affine parameter-dependent Lyapunov function of uncertain systems are developed with the benefit of the scalar multi-convex function. To be convenient for applications, such conditions are simplified into new linear matrix inequality (LMI) conditions, which can be solved by the powerful LMI toolbox. Numerical examples are provided to indicate that this new approach is less conservative than previous results for Hurwitz stability, Schur stability and D-stability of uncertain systems under certain circumstances.
This paper studies delay dependent robust stability and the stabilization problem of nonlinear perturbed systems with time varying delay. A new set of sufficient conditions for the stability of open as well as close loop systems are obtained in the sense of Lyapunov-Krasovskii. To reduce the conservatism, the work exploits the idea of splitting the delay interval into multiple equal regions so that less information on the time delay can be imposed to derive the results. The derived criterion not only improves the upper bounds of the time delay but also does not require the derivative of the delay to be known at prior. Easily testable sufficient criteria are presented in terms of linear matrix inequalities. It is shown that the derived conditions are very less conservative while comparing the maximum allowable upper bound of delay with the existing results in literature.
A method for maneuvering target tracking based on in- ductive factor of posture information is proposed.A distinguished characteristic of video frequency tracking is that it can capture the target posture changes from its picture easily,and the posture change means the motive model of the target will change.This information is very important to predict the trace of maneuvering target.Based on this idea,the quantified values of the target pos- ture change are obtained using Hough algorithm,this key values are defined as inductive factor of posture information,and then,the multiple grey trace predict models are established and the degrees of fuzzy subordinate values for every model are calculated with the inductive factor,the maneuvering extent values are determined by a new analysis method of stochastic differential equations for each model used to modify the degree of fuzzy subordinate values, these constitute the weighted values for every grey predict collec- tion.Finally,the synthesis predicting weighted result is obtained. The experimental results show that the new method is superior to the conventional algorithm.
This paper proposes an efficient scheme to reduce the pre-correlation bandwidth effect in the global navigation satellite system (GNSS) receiver filtering process. It is mainly based on the application of a spectral transformation to the satellite-emitted signal that effectively reduces its band. At the receiver's end, this operation causes the spreading of noise over a much wider band than that used by the radio frequency stage. Consequently, the resulting auto-correlation function in the acquisition process acquires properties that enhance considerably the performance of the receiver in the presence of the multipath and noise disturbing phenomena. The simulation results demonstrate that the proposed method is a plausible solution for both multipath and noise problems in the GNSS applications for any limited value of the pre-correlation bandwidth in the receiver filter.
Methods of the comprehensive evaluation have been studied for many years. However, the change speed of evaluated objects was rarely considered by the existing evaluation methods. An evaluation matrix is proposed to remedy this deficiency. Firstly, the change speed state (CSS) of the evaluated objects is analyzed based on double inspiriting control lines (DICLs), and a matrix of the CSS is constructed. Then, 72 elements in the matrix are analyzed, and formulas describing each CSS are given. The efficiency of the proposed evaluation matrix is proved when the CSS merges with the change speed trend (CST) in the dynamic comprehensive evaluation. Finally, a computing example shows that the proposed evaluation matrix is feasible in the dynamic comprehensive evaluation with the speed feature.
A pre-processing procedure is designed for a spacesurface 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.
Space-time adaptive processing (STAP) has been proven to be one of the best techniques capable of detecting weak moving targets in strong clutter environment and has been widely applied in airborne ground moving target indication (GMTI) radar. This paper applies an amplitude and phase estimation (APES) approach to two aspects of the STAP algorithm. Firstly, APES is applied to accurately describe the clutter characteristic in angle-Doppler domain. Then, APES is incorporated into the standard STAP algorithm to improve its performance without increasing transmitting/receiving channel and pulse number. The experimental examples show that the detection performance can be improved by using the APES technique, as well as the high computational complexity can be avoided.
The design of robust H∞ filtering problem of polytopic uncertain linear time-delay systems is addressed. The uncertain parameters are supposed to reside in a polytope. A parameterdependent Lyapunov function approach is proposed for the design of filters that ensure a prescribed H∞ performance level for all admissible uncertain parameters, which is different from the quadratic framework that entails fixed matrices for the entire uncertainty domain. This idea is realized by carefully selecting the structure of the matrices involved in the products with system matrices. An extended H∞ sufficient condition for the existence of robust estimators is formulated in terms of linear matrix inequalities, which can be solved via efficient interior-point algorithms.
To investigate a class of nonlinear network control system, a robust fault diagnosis method is presented based on the robust state observer. To access the objective that the designed robust filter is maximally tolerant to disturbances and sensitive to fault, the robustness and stability properties of the fault diagnosis scheme are established rigorously. Using the residual vector, a fault tolerant controller is established in order to guarantee the stability of the closed-loop system, and the controller law can be obtained by solving a set of linear matrix inequalities. Then, some relevant sufficient conditions for the existence of a solution are given by applying Lyapunov stability theory. Finally, a simulation example is performed to show the effectiveness of the proposed approach.
Due to low parameter sensitivity for balanced realizations, balanced structure becomes a good candidate for an statespace adaptive infinite impluse response (IIR) filter. Here, using coefficients of the transfer function as the adaptive filtering parameters, a balanced adaptive IIR filtering algorithm is proposed for output-error minimization. The algorithm in the internally balanced realization guarantees that the adaptive IIR filter always minimizes the ratio of maximum-to-minimum eigenvalue of the Grammian matrices at the each iteration. Simulation results are provided to corroborate the proposed algorithm.
A novel adaptive detection scheme both for point-like and distributed targets in the presence of Gaussian disturbance in the partially homogeneous environment (PHE) is proposed. The novel detection scheme is based on the orthogonal projection technique. Both the case of known covariance matrix structure and the case of unknown covariance matrix structure are considered. For the former case, the closed-form statistical property of the novel detectors is derived. When the covariance matrix is unknown, the corresponding detectors have higher probabilities of detection (PDs) than their natural competitors. Moreover, they ensure constant false alarm rate (CFAR) property.
Adopting“simultaneous transmitting, simultaneous receiving”operational scheme, instantaneous polarization radar (IPR) can measure target polarization scattering matrix (PSM) using only once target echoes in two orthogonal polarization channels. Firstly, signal model and signal process are advanced under narrowband condition. Secondly, measurement performances of two typical IPR waveforms are analyzed in detail. At last, field experiments are carried out using X-band IPR system designed by National University of Defense Technology (NUDT), China. Compared with results obtained by alternative polarization measurement scheme, following results can be obtained: the difference of relative amplitude measurement results is smaller than 2 dB and that of relative phase measurement results is smaller than 10?, verifying the validity of instantaneous polarization measurement scheme.
A new method to design a quantum controller which directly controls the probability density function (PDF) of quantum systems is proposed. Based on the quantum model from the PDF perspective, two specific control algorithms are proposed with uniform and non-uniform fields, respectively. Then a detailed control algorithm with convergence analysis is given for the small error case. By appropriately estimating the selected Lyapunov function, more accurate control effect is achieved. The proposed scheme provides a constructive method to find appropriate parameters for controller design.
For a large-scale adaptive array, the heavy computational load and the high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. An efficient parallel digital beamforming (DBF) algorithm based on the least mean square algorithm (PLMS) is proposed. An appropriate method is found to partition the least mean square (LMS) algorithm into a number of operational modules, which can be easily executed in a distributed-parallel-processing fashion. As a result, the proposed PLMS algorithm provides an effective solution that can alleviate the bottleneck of high-rate data transmission and reduce the computational cost. PLMS requires less computational load than that of the conventional parallel algorithms based on the recursive least square (RLS) algorithm, as well as it is easier to be implemented to do real time adaptive array processing. Moreover, low sidelobe of the beam pattern is obtained by constraining the static steering vector with Tschebyscheff coefficients. Finally, a scheme of the PLMS algorithm using distributed-parallel-processing system is also proposed. The simulation results demonstrate that the PLMS algorithm has the same interference cancellation performance as that of the conventional LMS algorithm. Moreover, the PLMS algorithm can obtain the same good beamforming performance, regardless how the algorithm is partitioned. It is expected that the proposed algorithm will be used in a large-scale adaptive array system to deal with real time adaptive digital beamforming processing.
This paper deals with system engineering and design methodology for super low altitude satellites in the view of the computational mission analysis. Due to the slight advance of imaging instruments, such as the focus of camera and the image element of charge coupled device (CCD), it is an innovative and economical way to improve the camera’s resolution to enforce the satellite to fly on the lower altitude orbit. DFH-3, the mature satellite bus developed by Chinese Academy of Space Technology, is employed to define the mass and power budgets for the computational mission analysis and the detailed engineering design for super low altitude satellites. An effective iterative algorithm is proposed to solve the ergodic representation of feasible mass and power budgets at the flight altitude under constraints. Besides, boundaries of mass or power exist for every altitude, where the upper boundary is derived from the maximum power, while the minimum thrust force holds the lower boundary before the power reaching the initial value. What’s more, an analytical algorithm is employed to numerically investigate the coverage percentage over the altitude, so that the nominal altitude could be selected from all the feasible altitudes based on both the mass and power budgets and the repetitive ground traces. The local time at the descending node is chosen for the nominal sun-synchronous orbit based on the average evaluation function. After determining the key orbital elements based on the computational mission analysis, the detailed engineering design on the configuration and other subsystems, like power, telemetry telecontrol and communication (TT&C), and attitude determination and control system (ADCS), is performed based on the benchmark bus, besides, some improvements to the bus are also implemented to accommodate the flight at a super low altitude. Two operation strategies, drag-free closed-loop mode and on/off open-loop mode, are presented to maintain the satellite’s altitude. Finally, a flight planning schedule for the satellite is demonstrated from its launch into the initial altitude at the very beginning to its decay to death in the end.
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