The performance of adaptive beamforming techniques is limited by the nonhomogeneous clutter scenario. An augmented Krylov subspace method is proposed, which utilizes only a single snapshot of the data for adaptive processing. The novel algorithm puts together a data preprocessor and adaptive Krylov subspace algorithm, where the data preprocessor suppresses discrete interference and the adaptive Krylov subspace algorithm suppresses homogeneous clutter. The novel method uses a single snapshot of the data received by the array antenna to generate a cancellation matrix that does not contain the signal of interest (SOI) component, thus, it mitigates the problem of highly nonstationary clutter environment and it helps to operate in real-time. The benefit of not requiring the training data comes at the cost of a reduced degree of freedom (DOF) of the system. Simulation illustrates the effectiveness in clutter suppression and adaptive beamforming. The numeric results show good agreement with the proposed theorem.

A simplified closed-form analytic solution for UWB impulse signal transmitting through a finitely conducting slab is proposed. The approach first requires evaluating the impulse response of the slab and then convolving it with the specified incident field waveform. To obtain the impulsive transmitting field, either for vertical or horizontal polarization, approximations to the refraction coefficients and propagation loss are made, which can be proved to be accurate enough, comparing with their frequency domain solutions. Thereby, it permits simplified closed-form expressions in the time domain for both terms. The resulting transient response for the transmitting impulse field is then given by convolution of the time domain refraction coefficients and time domain propagation loss. A numerical example of an incident monocycle transmitting through a slab using this technique, is presented, to illustrate the effective use of the method.

A novel and efficient method for decomposing a signal into a set of intrinsic mode functions (IMFs) and a trend is proposed. Unlike the original empirical mode decomposition (EMD), which uses spline fits to extract variations from the signal by separating the local mean from the fluctuations in the decomposing process, this new method being proposed takes advantage of the theory of variable finite impulse response (FIR) filtering where filter coefficients and breakpoint frequencies can be adjusted to track any peak-to-peak time scale changes. The IMFs are results of a multiple variable frequency response FIR filtering when signals pass through the filters. Numerical examples validate that in contrast with the original EMD, the proposed method can fine-tune the frequency resolution and suppress the aliasing effectively.

Sonar images have complex background, low contrast, and deteriorative edges; these characteristics make it difficult for researchers to dispose the sonar objects. The multi-resolution analysis represents the signals in different scales efficiently, which is widely used in image processing. Wavelets are successful in disposing point discontinuities in one dimension, but not in two dimensions. The finite Ridgelet transform (FRIT) deals efficiently with the singularity in high dimension. It presents three improved denoising approaches, which are based on FRIT and used in the sonar image disposal technique. By experiment and comparison with traditional methods, these approaches not only suppress the artifacts, but also obtain good effect in edge keeping and SNR of the sonar image denoising.

The ambiguity resolution in the field of GPS is investigated in detail. A new algorithm to resolve the ambiguity is proposed. The algorithm first obtains the floating resolution of the ambiguity aided with triple difference measurement. Decorrelation of searching space is done by reducing the ambiguity covariance matrix’s dimension to overcome the possible sick factorization of the matrix brought by Z-transformation. In simulation, the proposed algorithm is compared with least-squares ambiguity decorrelation adjustment (LAMBDA). The result shows that the proposed algorithm is better than LAMBDA because of lesser resolving time, which approximately reduces 20% resolving time. Thus, the proposed algorithm adapts to the high dynamic real-time applications.

A new method is proposed to analyze multi-component linear frequency modulated (LFM) signals, which eliminates cross terms in conventional Wigner-Ville distribution (WVD). The approach is based on Radon transform and Hilbert-Huang transform (HHT), which is a recently developed method adaptive to non-linear and non-stationary signals. The complicated signal is decomposed into several intrinsic mode functions (IMF) by the empirical mode decomposition (EMD), which makes the consequent instantaneous frequency meaningful. After the instantaneous frequency and Hilbert spectrum are computed, multi-component LFM signals detection and parameter estimation are obtained using Radon transform on the Hilbert spectrum plane. The simulation results show its feasibility and effectiveness.

The traditional HB-weighted time-delay estimation (TDE) method degenerates under the impulsive noise environment. Two new time-delay estimation methods are proposed based on fractional lower order statistics (FLOS) according to the impulsive characteristics of fractional lower order α-stable noises. Theoretic analysis and computer simulations indicate that the proposed covariation based HB weighted (COV-HB) algorithm can suppress impulsive noises in one received signal for 1 < α <2, whereas the other proposed fractional lower order covariancebased HB weighted (FLOC-HB) algorithm has robust performance under arbitrary impulsive noise conditions for the whole range of 0 < α  <2.

Carrier frequency offset (CFO) in MIMO-OFDM systems can be decoupled into two parts: fraction frequency offset (FFO) and integer frequency offset (IFO). The problem of IFO estimation is addressed and a new IFO estimator based on the Bayesian philosophy is proposed. Also, it is shown that the Bayesian IFO estimator is optimal among all the IFO estimators. Furthermore, the Bayesian estimator can take advantage of oversampling so that better performance can be obtained. Finally, numerical results show the optimality of the Bayesian estimator and validate the theoretical analysis.

Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are constructed with sequential conditional probability in HSI color space. Then, dynamic programming is used to seek the best color mapping relation with the minimum cost path between target image histogram and source image histogram. Finally, video tracking technique is performed to correct multi-view video. Experimental results show that the proposed method can obtain better subjective and objective performance in color correction.

Speckle filtering is an indispensable pre-processing step for applications of polarimetric synthetic aperture radar (POLSAR), such as terrain classification, target detection, etc. As one of the most typical methods, the polarimetric whitening filter (PWF) can be used to produce a minimum-speckle image by combining the complex elements of the scattering matrix, but polarimetric information is lost after the filtering process. A polarimetric filter based on subspace decomposition which was proposed by Gu et al specializes in retrieving principle scattering characteristics, but the corresponding mean value of an image after filtering is not kept well. A new filter is proposed for improving the disadvantage based on subspace decomposition. Under the constraint that a weighted combination of the polarimetric SAR images equals to the output of the PWF, the Euclidean distance between an unfiltered parameter vector and a signal space vector is minimized so that noises can be reduced. It is also shown that the proposed method is equivalent to the subspace filter in the case of no constraint. Experimental results with the NASA/JPL airborne polarimetric SAR data demonstrate the effectiveness of the proposed method.

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.

The feasibility of making two antennas work within a shared aperture conformal to a platform like an aircraft or a missile is investigated. The shared aperture is enclosed by a deep cavity, which is covered by a columniform dielectric radome. A modified quadrifilar helix antenna (QHA) with extended volute arms and a vertical monopole with a ring shaped ground are arranged in this co-aperture for global position system (GPS) orientation and telemetry, respectively. The effects of the cavity on these two antennas and the mutual coupling between these two antennas are studied through large numbers of experiments. The results show that the QHA has a strong influence on the monopole; however, these two antennas of the overall arrangement can perform simultaneously well within the aperture. The QHA has a right hand circular polarization (RHCP) and a broad beam normal to the radome topside, meanwhile the monopole can be used to produce a main lobe in the grazing direction above the aperture in some certain cases of the vertical location of the QHA in the cavity.

The Dezert-Smarandache theory (DSmT) is a useful method for dealing with uncertainty problems. It is more efficient in combining conflicting evidence. Therefore, it has been successfully applied in data fusion and object recognition. However, there exist shortcomings in its combination rule. An efficient combination rule is presented, that is, the evidence’s conflicting probability is distributed to every proposition based on remaining the focal elements of conflict. Experiments show that the new combination rule improves the reliability and rationality of the combination results. Although evidences conflict another one highly, good combination results are also obtained.

The consistency measurement and weight estimation approach of the hybrid uncertain comparison matrix in the analytic hierarchy process (AHP) are studied. First, the decision-making satisfaction membership function is defined based on the decision making’s allowable error. Then, the weight model based on the maximal satisfactory consistency idea is suggested, and the consistency index is put forward. Moreover, the weight distributing value model is developed to solve the decision making misleading problem since the multioptimization solutions in the former model. Finally, the weights are ranked based on the possibility degree approach to obtain the ultimate order.

To improve the effect of destroying time-sensitive target (TST), a method of operational effectiveness evaluation is presented and some influential factors are analyzed based on the combat flow of system for destroying TST. Considering the possible operation modes of the system, a waved operation mode and a continuous operation mode are put forward at first. At the same time, some relative formulas are modified. In examples, the influential factors and operation modes are analyzed based on the system effectiveness. From simulation results, some design and operation strategies of the system for destroying time sensitive targets are concluded, which benefit to the improvement of the system effectiveness.

Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower’s functions are separable with respect to the follower’s variables, and the other is that the follower’s functions are convex if the follower’s variables are not restricted to integers. A genetic algorithm based on an exponential distribution is proposed for the aforementioned problems. First, for each fixed leader’s variable x, it is proved that the optimal solution y of the follower’s mixed-integer programming can be obtained by solving associated relaxed problems, and according to the convexity of the functions involved, a simplified branch and bound approach is given to solve the follower’s programming for the second class of problems. Furthermore, based on an exponential distribution with a parameter λ, a new crossover operator is designed in which the best individuals are used to generate better offspring of crossover. The simulation results illustrate that the proposed algorithm is efficient and robust.

In the implementation of quality function deployment (QFD), the determination of the target values of engineering characteristics is a complex decision process with multiple variables and multiple objectives that should trade off, and optimize all kinds of conflicts and constraints. A fuzzy linear programming model (FLP) is proposed. On the basis of the inherent fuzziness of QFD system, triangular fuzzy numbers are used to represent all the relationships and correlations, and then, the functional relationships between the customer needs and engineering characteristics and the functional correlations among the engineering characteristics are determined with the information in the house of quality (HoQ) fully used. The fuzzy linear programming (FLP) model aims to find the optimal target values of the engineering characteristics to maximize the customer satisfaction. Finally, the proposed method is illustrated by a numerical example.

Singular rough sets (S-rough sets) have three classes of forms: one-directional S-rough sets, dual of onedirectional S-rough sets, and two-directional S-rough sets. Dynamic, hereditary, mnemonic, and hiding properties are the basic characteristics of S-rough sets. By using the S-rough sets, the concepts of f-hiding knowledge, F-hiding knowledge, hiding degree, and hiding dependence degree are given. Then, both the hiding theorem and the hiding dependence theorem of hiding knowledge are proposed. Finally, an application of hiding knowledge is discussed.

A parametric method for the gain-scheduled controller design of a linear time-varying system is given. According to the proposed scheduling method, the performance between adjacent characteristic points is preserved by the invariant eigenvalues and the gradually varying eigenvectors. A sufficient stability criterion is given by constructing a series of Lyapunov functions based on the selected discrete characteristic points. An important contribution is that it provides a simple and feasible approach for the design of gain-scheduled controllers for linear time-varying systems, which can guarantee both the global stability and the desired closed-loop performance of the resulted system. The method is applied to the design of a BTT missile autopilot and the simulation results show that the method is superior to the traditional one in sense of either global stability or system performance.

A new method on the interval stability of networked control systems (NCSs) with random delay and data packet dropout is studied. Combining interval systems and NCSs, a graphic condition on judging interval stability is presented in terms of the weighted diagraph theory in graph theory. Furthermore, utilizing the graph-theoretic algorithm, the delay-depended controller gains are obtained. Aiming at the same delay and data packed dropout, several controller gains are obtained, simultaneously. The example and simulation illustrate the effectiveness of the proposed method.

The robust H∞ control problem for a class of uncertain Takagi-Sugeno fuzzy systems with timevarying state delays is studied. The uncertain parameters are supposed to reside in a polytope. Based on the delay-dependent Lyapunov functional method, a new delay-dependent robust H∞ fuzzy controller, which depends on the size of the delays and the derivative of the delays, is presented in term of linear matrix inequalities (LMIs). For all admissible uncertainties and delays, the controller guarantees not only the asymptotic stability of the system but also the prescribed H∞ attenuation level. In addition, the effectiveness of the proposed design method is demonstrated by a numerical example.

The equivalent sample theory and its application in analysis of networked control system (NCS) are presented. After analyzing NCS’s scheduling in master-slave mode, the characteristics of time delay and sample are summarized. Looking on master station visiting the slave station as a special sample process, the theory of equivalent sample is presented. And based on it, the stability of a kind of NCS is analyzed. The criterion to determine the upper bound of transmission delay is introduced, which guarantees the stability. Finally, an example with simulation shows the availability and usability of this analysis method.

An indirect adaptive fuzzy control scheme is developed for a class of nonlinear discrete-time systems. In this method, two fuzzy logic systems are used to approximate the unknown functions, and the parameters of membership functions in fuzzy logic systems are adjusted according to adaptive laws for the purpose of controlling the plant to track a reference trajectory. It is proved that the scheme can not only guarantee the boundedness of the input and output of the closed–loop system, but also make the tracking error converge to a small neighborhood of the origin. Simulation results indicate the effectiveness of this scheme.

The convergence and stability analysis for two end-to-end rate-based congestion control algorithms with unavoidable random loss in packets are presented, which can be caused by, for example, errors on wireless links. The convergence rates of these two algorithms are analyzed by linearizing them around their equilibrium points, since they are globally stable and can converge to their unique equilibrium points. Some sufficient conditions for local stability in the presence of round-trip delay are obtained based on the general Nyquist criterion of stability. The stability conditions can be considered to be more general. If random loss in the first congestion control algorithm is not considered, they reduce to the local stability conditions which have been obtained in some literatures. Furthermore, sufficient conditions for local stability of a new congestion control algorithm have also been obtained if random loss is not considered in the second congestion control algorithm.

A new controller design problem of networked control systems with packet dropping is proposed. Depending on the place that the observer is put in the system, the network control systems with packet dropping are modeled as stochastic systems with the random variables satisfying the Bernoulli random binary distribution. The observer-based controller is designed to stabilize the networked system in the sense of mean square, and the prescribed H∞ disturbance attenuation level is achieved. The controller design problem is formulated as the feasibility of the convex optimization problem, which can be solved by a linear matrix inequality (LMI) approach. Numerical examples illustrate the effectiveness of the proposed methods.

On the basis of the relationship between the Hamiltonian of spin 1/2 quantum system under control and the energy level structure and transitions, a radio frequency pulse sequence is designed using intuitive and half counter-intuitive sequences of pulse to transfer the population of the 3-qubit system coherently. The effectiveness of the designed control sequence is verified through the system simulation experiment of the evolution of state. In principle, the design method of the control pulse sequence proposed can be generalized to use in the quantum systems of higher dimension.

The problem of decentralized adaptive fuzzy control for a class of time-delayed interconnected nonlinear systems with unknown backlash-like hystersis is discussed. On the basis of the principle of variable structure control (VSC) and by using the fuzzy systems with linear adjustable parameters that are used to approximate plant unknown functions, a novel decentralized adaptive fuzzy control strategy with a supervisory controller is developed. A general method, which is modeled the backlash-like hysteresis, is proposed and removes the assumption that the boundedness of disturbance, and the slope of the backlash-like hystersis are known constants. Furthermore, the interconnection term is supposed to be pth-order polynomial in time-delayed states. In addition, the plant dynamic uncertainty and modeling errors are adaptively compensated by adjusting the parameters and gains on-line for each subsystems. By theoretical analysis, it is shown that the closed-loop fuzzy control systems are globally stable, with tracking error converging to zero. Simulation results demonstrate the effectiveness of the approach.

With the sharp increase of China’s in-orbit spacecraft and the constraint TT&C resources, a mathematical model for optimal TT&C resource allocation is proposed, and the TT&C facility remote monitoring function is designed to achieve the multitask operation pattern under the unified management of the network management center. With this pattern, the TT&C network management and the spacecraft management are separated, which is quite different from the previous pattern. Further, a novel spacecraft TT&C technique based on spacecraft control language is developed, and the telecommanding pattern is designed to address the spacecraft operation problems. The engineering application shows that this pattern fundamentally improves the TT&C network capability, increases the resource efficiency, and satisfies the efficient, accurate, and flexible operation of spacecraft.

Currently, the article analyzes the CAN bus’s rule of priority’s arbitration bit by bit without destroy. It elicits the conclusion that if static priority based on the affirmatory system model is used, the lower priority’s messages will be delayed considerably more, even some data will be lost when the bus’s bandwidth is widely used. The scheduling cannot be modified neither during the system when static priority is used. The dynamic priority promoting method and the math model of SQSA and SQMA are presented; it analyzes the model’s rate of taking in and sending out in large quantities, the largest delay, the problems and solutions when using SQMA. In the end, it is confirmed that the method of improving dynamic priority has good performances on the network rate of taking in and sending out in large quantities, the average delay, and the rate of network usage by emulational experiments.

A study on the zero-forcing beamforming (ZFBF) scheme with antenna selection at user terminals in downlink multi-antenna multi-user systems is presented. Simulation results show that the proposed ZFBF scheme with receiver antenna selection (ZFBF-AS) achieves considerable throughput improvement over the ZFBF scheme with single receiver antenna. The results also show that, with multi-user diversity, the ZFBF-AS scheme approaches the throughput performance of the ZFBF scheme using all receiver antennas (ZFBF-WO-AS) when the base station adopts semi-orthogonal user selection (SUS) algorithm, and achieves larger throughput when the base station adopts the Round-robin scheduling algorithm. Compared with ZFBF-WO-AS, the proposed ZFBF-AS scheme can reduce the cost of user equipments and the channel state information requirement at the transmitter (CSIT) as well as the multiuser scheduling complexity at the transmitter.

The path protection approach is widely investigated as a survivability solution for GMPLS networks, which has the advantage of efficient capacity utilization. However, there is a problem of the path protection approach that searching a disjoint backup path for a primary path is often unsuccessful. In order to resolve this problem, an integrated dynamic shared protection (IDSP) algorithm is proposed. The main idea of the proposed algorithm is that the path protection approach is first used to establish a backup path for the primary path; if the establishment is unsuccessful, then the primary path is dynamically divided into segments whose hop count are not fixed but not more than the limitation calculated by the equations introduced. In this proposal, backup bandwidth sharing is allowed to improve the capacity utilization ratio, which makes the link cost function quite different from previous ones. Simulation experiments are presented to demonstrate the efficiency of the proposed method compared with previous methods. Numerical results show that IDSP can not only achieve low protection failure probability but can also gain a better tradeoff between the protection overbuild and the average recovery time.

With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evolutionary programming (CSEP) algorithm. This method brings up the manner of that a cognitive agent inherits a paradigm in clustering to enable the cognitive agent to acquire a chaotic mutation operator in the betrayal. As proven in the experiment, this method can not only effectively increase web clustering efficiency, but it can also practically improve the precision of web clustering.

Knowledge discovery from data directly can hardly avoid the fact that it is biased towards the collected experimental data, whereas, expert systems are always baffled with the manual knowledge acquisition bottleneck. So it is believable that integrating the knowledge embedded in data and those possessed by experts can lead to a superior modeling approach. Aiming at the classification problems, a novel integrated knowledge-based modeling methodology, oriented by experts and driven by data, is proposed. It starts from experts identifying modeling parameters, and then the input space is partitioned followed by fuzzification. Afterwards, single rules are generated and then aggregated to form a rule base, on which a fuzzy inference mechanism is proposed. The experts are allowed to make necessary changes on the rule base to improve the model accuracy. A real-world application, welding fault diagnosis, is presented to demonstrate the effectiveness of the methodology.

Due to the advantages of ant colony optimization (ACO) in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the concept for tour and the length of tour are redefined. Additionally, the directional information is incorporated into the proposed method because it is one of the most important factors that affects the performance of data association. Kalman filter is employed to estimate target states. Computer simulation results show that the proposed method could carry out data association in an acceptable CPU time, and the correct data association rate is higher than that obtained by the data association (DA) algorithm not combined with directional information.

In the multistage reliability growth tests with instant and delayed fix modes, the failure data can be assumed to follow Weibull processes with different parameters at different stages. For the Weibull process within astage, by the proper selection of prior distribution form and the parameters, a concise posterior distribution form is obtained, thus simplifying the Bayesian analysis. In the multistage tests, the improvement factor is used to convert the posterior of one stage to the prior of the subsequent stage. The conversion criterion is carefully analyzed to determine the distribution parameters of the subsequent stage’s variable reasonably. Based on the mentioned results, a new synthetic Bayesian evaluation program and algorithm framework is put forward to evaluate the multistage reliability growth tests with instant and delayed fix modes. The example shows the effectiveness and flexibility of this method.

The unmanned reconnaissance aerial vehicle (URAV) plays an important role in battlefield monitoring and information acquiring because of its advantage of zero casualties, and has thus attracted considerable attention of the world. The URAV was developed rapidly in our country, however, no scientific assessment methods have yet been provided owing to different fight requirements of armed forces. Considering the demand of the missile artillery on the martial information, the model of information requirement of combat force, the reconnaissance ability of URAV, the survivability of URAV, and the task reliability of URAV were constructed, respectively. By synthesizing the mathematic models above, the model of developing demand was constructed on the URAV equipment. It simulated and calculated some URAV equipment developing scales, and explored a way of settling the problem of URAV equipment developing demand.