A finite domain time difference (FDTD) and second-derivative combined method is proposed for the evaluation of phase center in the Fresnel region of complex structure millimeter antennas. This method adopts FDTD’s near to far field transformation to obtain the fields in Fresnel region and then applies the second-derivative ethod to calculate the phase center. The adoption of FDTD efficiently overcomes the difficulties arising from the existing calculation methods’requirements for the radiation analytical formula of some complex antennas, which makes the existing second-derivative method more applicable in engineering. Also, FDTD increases the precision owing to the superposition field calculation from its extrapolation. The correctness of this proposed method is certified with typical examples and the phase center in the Fresnel region of a microwave radiometry calibration corrugate horn antenna is evaluated with the key features.

This paper introduces the research work on the extension of multilevel fast multipole algorithm (MLFMA) to 3D complex structures including coating object, thin dielectric sheet, composite dielectric and conductor, cavity. The impedance boundary condition is used for scattering from the object coated by thin lossy material. Instead of volume integral equation, surface integral equation is applied in case of thin dielectric sheet through resistive sheet boundary condition. To realize the fast computation of scattering from composite homogeneous dielectric and conductor, the surface integral equation based on equivalence principle is used. Compared with the traditional volume integral equation, the surface integral equation reduces greatly the number of unknowns. To compute conducting cavity with electrically large aperture, an electric field integral equation is applied. Some numerical results are given to demonstrate the validity and accuracy of the present methods.

It is known in the computational electromagnetics (CEM) that the node element has a relative wellconditioned matrix, but suffers from the spurious solution problem; whereas the edge element has no spurious solutions, but usually produces an ill-conditioned matrix. Particularly, when the mesh is over dense, the iterative solution of the matrix equation from edge element converges very slowly. Based on the node element and edge element, a node-edge element is presented, which has no spurious solutions and better-conditioned matrix. Numerical experiments demonstrate that the proposed node-edge element is more efficient than now-widely used edge element.

Blind separation of sparse sources (BSSS) is discussed. The BSSS method based on the conventional K-means clustering is very fast and is also easy to implement. However, the accuracy of this method is generally not satisfactory. The contribution of the vector x(t) with different modules is theoretically proved to be unequal, and a weighted K-means clustering method is proposed on this grounds. The proposed algorithm is not only as fast as the conventional K-means clustering method, but can also achieve considerably accurate results, which is demonstrated by numerical experiments.

An EBCOT-based method is proposed to reduce the priority of background coefficients in the ROI code block without compromising algorithm complexity. The region of interest is encoded to a higher quality level than background, and the target searching time in video-guided penetrating missile can be shortened. Three kinds of coding schemes based on EBCOT are discussed. Experimental results demonstrate that the proposed method hows higher compression efficiency, lower complexity, and good reconstructed ROI image quality in the lower channel capacity.

This letter presents two preprocessing techniques for narrow-band interference (NBI) rejection in Time-Division-Duplex (TDD) CDMA systems. In the proposed methods, at the transmitter, by using Karhaunen-Loeve Transform and Discrete Fourier Transform, the transmitted power is set to zero in the directions of the eigenvectors that will be severely contaminated by NBI; and therefore less part of the transmitted energy will be polluted by NBI in channel. The processing is transferred from receiver to transmitter, and thus the complexity of the receiver is significantly reduced. It is assumed that channel state information can be estimated at the transmitter because in symmetric TDD systems each receiver in turn also acts as a transmitter.

This article deals with two important issues in digital filter implementation: roundoff noise and limit cycles. A novel class of robust state-space realizations, called normal realizations, is derived and characterized. It is seen that these realizations are free of limit cycles. Another interesting property of the normal realizations is that they yield a minimal error propagation gain. The optimal realization problem, defined as to find those normal realizations that minimize roundoff noise gain, is formulated and solved analytically. A design example is presented to demonstrate the behavior of the optimal normal realizations and to compare them with several well-known digital filter realizations in terms of minimizing the roundoff noise and the error propagation.

To cope with the scenario where both uncorrelated sources and coherent sources coexist, a novel algorithm to direction of arrival (DOA) estimation for symmetric uniform linear array is presented. Under the condition of stationary colored noise field, the algorithm employs a spatial differencing method to eliminate the noise covariance matrix and uncorrelated sources, then a Toeplitz matrix is constructed for the remained coherent sources. After preprocessing, a propagator method (PM) is employed to find the DOAs without any eigendecomposition. The number of sources resolved by this approach can exceed the number of array elements at a lower computational complexity. Simulation results demonstrate the effectiveness and efficiency of the proposed method.

The satellite constellation classes, which are suitable for the medium earth orbit tracking and data relay satellite system (MEO-TDRSS) of China, are investigated. On the basis of the functionality and the traffic distribution characteristic of MEO-TDRSS, the coverage performance and inter-satellite link properties of four different constellation schemes are compared by simulations. Simulation results indicate that the rosette and common-track constellations, whose satellites are distributed on the celestial sphere more uniformly, are appropriate for the implementation of MEO-TDRSS of China.

To make the modulation classification system more suitable for signals in a wide range of signal to noise rate (SNR), a feature extraction method based on signal wavelet packet transform modulus maxima matrix (WPTMMM) and a novel support vector machine fuzzy network (SVMFN) classifier is presented. The WPTMMM feature extraction method has less computational complexity, more stability, and has the preferable advantage of robust with the time parallel moving and white noise. Further, the SVMFN uses a new definition of fuzzy density that incorporates accuracy and uncertainty of the classifiers to improve recognition reliability to classify nine digital modulation types (i.e. 2ASK, 2FSK, 2PSK, 4ASK, 4FSK, 4PSK, 16QAM, MSK, and OQPSK). Computer simulation shows that the proposed scheme has the advantages of high accuracy and reliability (success rates are over 98% when SNR is not lower than 0dB), and it adapts to engineering applications.

Bistatic SAR possesses characteristic of the azimuth space-variant when the velocities of transmitter and receiver are not equal. The geometric model of BiSAR with the parallel trajectories and the nonequal platform velocities is presented. Analyzing the motion relationship of transmitter and receiver, the formula of azimuth spacevariant is derived in time domain. Via Taylor polynomial expansions, the azimuth space-variant is factorized by four terms: zero-order, first-order, second-order, and third-order term. And, their impacts on impulse response are illuminated. Some characteristics about azimuth space-variant of airborne BiSAR case are exhibited by simulation experiments, and these simulated results are coincident with the formulae of azimuth space-variant.

Synthetic aperture radar (SAR) systems have become an important tool for fine-resolution mapping and other remote sensing operations. The multi-channel SAR ground moving-target indication (GMTI) must process its data to produce not only the image of surveillance area but also the information of the ground moving-targets. The topic of moving-target detection in clutter has been extensively studied, and there are many methods that are used to detect moving targets, such as displaced phase center antenna (DPCA) method, along-track interfero-metric (ATI) phase, space-time adaptive processing (STAP), or some other metrics. A canonical framework is proposed that encompasses all the multi-channel SAR-GMT methods, namely, DPCA and ATI. The statistical test metric for multi-channel SAR-GMTI is established in a simple form, via the definition of the complex central Wishart distribution, to deduce the statistics of the test metric, and the probability distribution of the test metric for multichannel SAR-GMTI has the complex central Wishart distribution of 1×1 case, namely the χ2 distribution. The theory foundation offers the possibility to construct the united multi-channel SAR-GMTI detector, and derives the constant false alarm rate (CFAR) detector tests for separating moving targets from clutter.

A complete method of synchronization technology of bistatic radar using global position system (GPS) is presented. The pulse per second signal (1PPS) is elaborately modified to increase the time synchronization precision and keep loop locking. A very high time synchronization precision is achieved. Using the modified 1PPS to discipline the local OCXO, the reference frequency signal achieves both high long term stability (LTS) and short term stability (STS) properties. An algorithm, named phase abrupt change CFAR is presented to restrain the 1PPS phase abrupt change and keep loop locking. The experimental results indicate that this time and frequency synchronization method is effective and the time synchronization precision of the synchronization system can be improved from ±100 ns to ±25 ns. In addition, the phase noise is improved to 20 dB.

For group decision-making problems with linguistic assessment information, a new method based on two-tuple and WC-OWA operator is proposed, in which the criteria’s weights and the decision-makers’ preference information might take the form of linguistic grade, or might be between two continuous linguistic grades, or might be linguistic interval, or might be default. In this method, all linguistic values are transformed into two-tuple, and an aggregative decision-making matrix is obtained by using interval operation. The group aggregative values of each criterion on alternatives are computed by using a WC-OWA operator, the aggregative values on alternatives are worked out, and transformed into two-tuple. And the rank of the alternatives is obtained by using the order property of two-tuple. An example shows the feasibility and effectiveness of the proposed method.

A weapon target assignment (WTA) model satisfying expected damage probabilities with an ant colony algorithm is proposed. In order to save armament resource and attack the targets effectively, the strategy of the weapon assignment is that the target with greater threat degree has higher priority to be intercepted. The effect of this WTA model is not maximizing the damage probability but satisfying the whole assignment result. Ant colony algorithm has been successfully used in many fields, especially in combination optimization. The ant colony algorithm for this WTA problem is described by analyzing path selection, pheromone update, and tabu table update. The effectiveness of the model and the algorithm is demonstrated with an example.

Based on rough similarity degree of rough sets and close degree of fuzzy sets, the definitions of rough similarity degree and rough close degree of rough fuzzy sets are given, which can be used to measure the similar degree between two rough fuzzy sets. The properties and theorems are listed. Using the two new measures, the method of clustering in the rough fuzzy system can be obtained. After clustering, the new fuzzy sample can be recognized by the principle of maximal similarity degree.

China’s aerospace enterprises carry on the multinational operation and participate in the international competition and the international division of labor and cooperation positively. This article first analyzs China aerospace enterprises’ binary multinational business control objective and constructes its model. Then the article analyzes the tangible and intangible control mechanism of China aerospace enterprises’ binary multinational operation respectively. Finally, the article constructs the model of China aerospace enterprises’ binary multinational operation mechanisms.

Resource allocation (RA) is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such as maximizing the profits, minimizing the costs, or achieving the best qualities. A complex multiobjective RA is addressed, and a multiobjective mathematical model is used to find solutions efficiently. Then, an improved particle swarm algorithm (mO PSO) is proposed combined with a new particle diversity controller policies and dissipation operation. Meanwhile, a modified Pareto methods used in PSO to deal with multiobjectives optimization is presented. The effectiveness of the provided algorithm is validated by its application to some illustrative example dealing with multiobjective RA problems and with the comparative experiment with other algorithm.

The robust reliable H∞ control problem for discrete-time Markovian jump systems with actuator failures is studied. A more practical model of actuator failures than outage is considered. Based on the state feedback method, the resulting closed-loop systems are reliable in that they remain robust stochastically stable and satisfy a certain level of H∞ disturbance attenuation not only when all actuators are operational, but also in case of some actuator failures. The solvability condition of controllers can be equivalent to a feasibility problem of coupled linear matrix inequalities (LMIs). A numerical example is also given to illustrate the design procedures and their effectiveness.

The stabilization and trajectory tracking problems of autonomous airship’s planar motion are studied. By defining novel configuration error and velocity error, the dynamics of error systems are derived. By applying Lyapunov stability method, the state feedback control laws are designed and the close-loop error systems are proved to be uniformly asymptotically stable by Matrosov theorem. In particular, the controller does not need knowledge on system parameters in the case of set-point stabilization, which makes the controller robust with respect to parameter uncertainty. Numerical simulations illustrate the effectiveness of the controller designed.

Conventional artificial fish has some shortages on the interaction with environment, other fish, and the animator. This article proposes a multi-tier interaction control model of artificial fish, realizes the interaction model through integration of virtual reality technology and Markov sequence, and provides a virtual marine world to describe the interaction between artificial fish and the virtual environment and the interaction between the artificial fish and the animator. Simulation results show that the interaction model owns not only the basic characteristics of virtual biology, but also has high trueness interaction function.

This article is concerned with the modeling and control problems of the flexible spacecraft. First, the state observer is designed to estimate the vibration mode on the basis of free vibration models. Then, an optimal guaranteed cost controller is proposed to stabilize system attitude and damp the vibration of the flexible beam at the same time. Numerical simulation examples show the feasibility and validity of the proposed method.

Under the complicated electromagnetism circumstance, the model of data fusion control and guidance of surface-to-air missile weapon systems is established. Such ways and theories as Elman-NN, radar tracking and filter’s data fusion net based on the group method for data-processing (GMRDF) are applied to constructing the model of data fusion. The highly reliable state estimation of the tracking targets and the improvement in accuracy of control and guidance are obtained. The purpose is optimization design of data fusion control and guidance of surface-to-air missile weapon systems and improving the fighting effectiveness of surface-to-air missile weapon systems.

The robust H∞ control for networked control systems with both stochastic network-induced delay and data packet dropout is studied. When data are transmitted over network, the stochastic data packet dropout process can be described by a two-state Markov chain. The networked control systems with stochastic network-induced delay and data packet dropout are modeled as a discrete time Markov jump linear system with two operation modes. The sufficient condition of robust H∞ control for networked control systems stabilized by state feedback controller is presented in terms of linear matrix inequality. The state feedback controller can be constructed via the solution of a set of linear matrix inequalities. An example is given to verify the effectiveness of the method proposed.

In aerial robots’ visual navigation, it is essential yet very difficult to detect the attitude and position of the robots operated in real time. By introducing a new parametric model, the problem can be reduced from almost unmanageable to be partly solved, though not fully, as per the requirement. In this parametric approach, a multi-scale least square method is formulated first. By propagating as well as improving the parameters down from layer to layer of the image pyramid, a new global feature line can then be detected to parameterize the attitude of the robots. Furthermore, this approach paves the way for segmenting the image into distinct parts, which can be realized by deploying a Bayesian classifier on the picture cell level. Comparison with the Hough transform based method in terms of robustness and precision shows that this multi-scale least square algorithm is considerably more robust to noises. Some discussions are also given.

A novel robust fault diagnosis scheme, which possesses fault estimate capability as well as fault diagnosis property, is proposed. The scheme is developed based on a suitable combination of the adaptive multiple model (AMM) and unknown input observer (UIO). The main idea of the proposed scheme stems from the fact that the actuator Lock-in-Place fault is unknown (when and where the actuator gets locked are unknown), and multiple models are used to describe different fault scenarios, then a bank of unknown input observers are designed to implement the disturbance de-coupling. According to Lyapunov theory, proof of the robustness of the newly developed scheme in the presence of faults and disturbances is derived. Numerical simulation results on an aircraft example show satisfactory performance of the proposed algorithm.

A kind of networked control system is studied; the networked control system with noise disturbance is modeled based on information scheduling and control co-design. Augmented state matrix analysis method is introduced, and robust fault-tolerant control problem of networked control systems with noise disturbance under actuator failures is studied. The parametric expression of the controller under actuator failures is given. Furthermore, the result is analyzed by simulation tests, which not only satisfies the networked control systems stability, but also decreases the data information number in network channel and makes full use of the network resources.

Based on KKT complementary condition in optimization theory, an unconstrained non-differential optimization model for support vector machine is proposed. An adjustable entropy function method is given to deal with the proposed optimization problem and the Newton algorithm is used to figure out the optimal solution. The proposed method can find an optimal solution with a relatively small parameter p, which avoids the numerical overflow in the traditional entropy function methods. It is a new approach to solve support vector machine. The theoretical analysis and experimental results illustrate the feasibility and efficiency of the proposed algorithm.

A fuzzy particle swarm optimization (PSO) on the basis of elite archiving is proposed for solving multi-objective optimization problems. First, a new perturbation operator is designed, and the concepts of fuzzy global best and fuzzy personal best are given on basis of the new operator. After that, particle updating equations are revised on the basis of the two new concepts to discourage the premature convergence and enlarge the potential search space; second, the elite archiving technique is used during the process of evolution, namely, the elite particles are introduced into the swarm, whereas the inferior particles are deleted. Therefore, the quality of the swarm is ensured. Finally, the convergence of this swarm is proved. The experimental results show that the nondominated solutions found by the proposed algorithm are uniformly distributed and widely spread along the Pareto front.

Motivated by the projects constrained by space capacity and resource transporting time, a project scheduling problem with capacity constraint was modeled. A hybrid algorithm is proposed, which uses the ideas of bi-level scheduling and project decomposition technology, and the genetic algorithm and tabu search is combined. Topological reordering technology is used to improve the efficiency of evaluation. Simulation results show the proposed algorithm can obtain satisfied scheduling results in acceptable time.

Evolutionary computation techniques have mostly been used to solve various optimization problems, and it is well known that graph isomorphism problem (GIP) is a nondeterministic polynomial problem. A simulated annealing (SA) algorithm for detecting graph isomorphism is proposed, and the proposed SA algorithm is well suited to deal with random graphs with large size. To verify the validity of the proposed SA algorithm, simulations are performed on three pairs of small graphs and four pairs of large random graphs with edge densities 0.5, 0.1, and 0.01, respectively. The simulation results show that the proposed SA algorithm can detect graph isomorphism with a high probability.

The Wigner-Ville distribution (WVD) and the cross Wigner-Ville distribution (XWVD) have been shown to be efficient in the estimation of instantaneous frequency (IF). But the statistical result of the IF estimation from XWVD peak is much better than using WVD peak. The reason is given from a statistical point of view. Theoretical studies show that XWVD of the analyzed signal can be estimated from XWVD of the noise-contaminated signal. The estimation is unbiased, and the variance is equal to that of noise. In this case, WVD cannot be estimated from WVD of the noise-contaminated signal. Therefore, higher SNR is required when WVD is used to analyze signals.

To improve the positioning accuracy in GPS point positioning, the geometric dilution of precision (GDOP) including HDOP, VDOP, TDOP, PDOP is commonly considered. The properties of the DOP for the GPS satellite navigation system are studied and the coordinate system is improved in order to decrease the amount of variables. In the end, by simulation and discussing the results, the corresponding conclusions are presented.