Traditional multi-band frequency selective surface (FSS) approaches are hard to achieve a perfect resonance response in a wide band due to the limit of the onset grating lobe frequency determined by the array. To solve this problem, an approach of combining elements in different period to build a hybrid array is presented. The results of series of numerical simulation show that multi-periodicity combined element FSS, which are designed using this approach, usually have much weaker grating lobes than the traditional FSS. Furthermore, their frequency response can be well predicted through the properties of their member element FSS. A prediction method for estimating the degree of expected grating lobe energy loss in designing multi-band FSS using this approach is provided.

According to the Doppler sensitive of the phase coded pulse compression signal, a Doppler estimating and compensating method based on phase is put forward to restrain the Doppler sidelobes, raise the signal-to-noise ratio and improve measuring resolution. The compensation method is used to decompose the echo to amplitude and phase, and then compose the new compensated echo by the amplitude and the nonlinear component of the phase. Furthermore the linear component of the phase can be used to estimate the Doppler frequency shift. The computer simulation and the real data processing show that the method has accurately estimated the Doppler frequency shift, successfully restrained the energy leakage on spectrum, greatly increased the echo signal-to-noise ratio and improved the detection performance of the radio system in both time domain and frequency domain.

To improve the performance of a multiuser MIMO-OFDM system with imperfect channel status information, a downlink adaptive resource allocation algorithm which combines space-time block coding and beam forming (STBC-BF) is proposed. The algorithm allocates the subcarriers with a shared manner. A zero forcing processing with joint Rx-Tx is used to suppress the co-channel interference (CCI) and to construct uncorrelatedchannels for STBC. An adaptive power allocation for the STBC equivalent channels can increase signal to interference and noise ratio at the receiver. Simulation results show that under the condition of an imperfect CSI, the proposed algorithm improves the system performance and reduces the number of BS transmit antennas required.

In the reconstructed phase space, based on the Karhunen-Lo`eve transformation (KLT), the new local linear prediction method is proposed to predict chaotic time series. A noise-free chaotic time series and a noise addedchaotic time series are analyzed. The simulation results show that the KLT-based local linear prediction method can effectively make one-step and multi-step prediction for chaotic time series, and the one-step and multi-step prediction accuracies of the KLT-based local linear prediction method are superior to that of the traditional local linear prediction.

In memory polynomial predistorter design, the coefficient estimation algorithm based on normalized least mean square is sensitive to initialization parameters. A predistorter based on generalized normalized gradient descent algorithm is proposed. The merit of the GNGD algorithm is that its learning rate provides compensation for the independent assumptions in the derivation of NLMS, thus its stability is improved. Computer simulation shows that the proposed predistorter is very robust. It can overcome the sensitivity of initialization parameters and get a better linearization performance.

Matrix perturbation theory is utilized to investigate high-rank line of sight multiple input multiple output channels in a microwave relay system. The upper and lower bounds of channel capacity are derived based on space time block codes technique and singular values decomposition. A useful constraint for designing LOS MIMO channels is developed by the use of the condition number of the MIMO channel matrix. The theoretical analysis
of channel capacity is confirmed by the simulation. The results show that the proposed method is able to give a physical explanation of the high-rank LOS MIMO channel matrix characteristics.

To obtain frequency-temperature compensation in a sapphire loaded cavity for hydrogen maser, a dielectric named SrTiO3 is employed whose temperature coefficient of permittivity is opposite to that of sapphire. Based on theoretical analysis and computer simulation, a TE011 mode of a sapphire loaded cavity associated with two small rings of SrTiO3 with different thickness is solved, and the useful parameters that influence the temperature coefficient of cavity are calculated. Finally an experiment is brought forward and its results are very close to the computing results. When the thickness of SiTiO3 dielectric is 7 mm and the diameter is 17 mm in configuration b, the temperature coefficient of cavity is decreased from −58.8 kHz/K to −8.2 kHz/K and the quality factor is 40248.

To detect high frequency (HF) first-order sea echo spectra contaminated with ships, ionosphere interference, and other, a new characteristic-knowledge-aided detection method is proposed. With 2-D image features in range-Doppler spectrum, the trend of first-order sea echoes is extracted as indicative information by a multi-scale filter. Detection rules for both single and splitting first-order sea echoes are given based on the characteristic knowledge combining the indicative information with the global characteristics such as amplitude, symmetry, continuity,etc. Compared with the classical algorithms, the proposed method can detect and locate the first-order sea echo in the HF band more accurately especially in the environment with targets/clutters smearing. Experiments with real data verify the validity of the algorithm.

The influence of the distorted plane of the active phased array antenna on the electromagnetic performance is of great significance to the research on and development of the high-performance antennas. On the bent and bowl-shape distortion, the model is established of the relationship between the electromagnetic performance and the position error of the radiated elements. The method is presented of analyzing the far-field pattern of the distorted rectangular active phased array antenna. The analysis results of a planar phased array antenna with different distortions grades prove the validity of the model. Therefore, by the method, the antenna designers may set the reasonable requirement on the structural tolerance in manufacturing antenna.

Traditional DEA-based ranking techniques have some pitfalls such as ignoring the inherent differences among decision making units (DMUs), or lacking a common weight-based ranking, etc. To overcome these obstacles, the paper first examines the possible differences among all DMUs such as the technical efficiency difference, the preference structure difference and the within-group position difference. Based upon the above differences this paper induces an integrated ranking measurement which helps to give a fair and full ranking for all DMUs under evaluation. Following the three types of differences, this approach behaves greatly elaborately, accurately and reasonably. Finally, the results from the Olympics achievement evaluation approve the acceptability of this approach.

The principle and method of both radar target imaging and velocity measurement simultaneously based on step frequency waveforms is presented. Velocity compensation is necessary in order to obtain the good High resolution range profile since this waveform is greatly sensitive to the Doppler shift. The velocity measurement performance of the four styles is analyzed with two pulse trains consisted of positive and negative step frequency waveforms. The velocity of targets can be estimated first coarsely by using the pulse trains with positive-positive step frequency combination, and then fine by positive-negative combination. Simulation results indicate that the method can accomplish the accurate estimation of the velocity with efficient computation and good anti-noise performance and obtain the good HRRP simultaneously.

To deal with the non-Gaussian noise in standard 2-D SAR images, the deramped signal in imaging plane, and the possible symmetric distribution of complex noise, the fourth-order cumulant of complex process is introduced into SAR tomography. With the estimated AR parameters of ARMA model of noise through Yule-Walker equation, the signal series of height is pre-filtered. Then, through ESPRIT, the spectrum is obtained and the aperture in height direction is synthesized. Finally, the SAR tomography imaging of scene is achieved. The results of processing on signal with non-Gaussian noise demonstrate the robustness of the proposed method. The tomography imaging of the scenes shows that the higher-order spectrum analysis is feasible in the application.

To study simultaneous location of different kinds of facilities, a new model of flow interception problem with multi-type of flows is proposed, with the consideration of multi-purpose flows and the influence of facilities on each other. To be more practical, the objective is to maximize the benefits from flow-by customers instead of maximizing flows in the past. Since this problem is NP-hard and there is no optimal solution for large network, greedy and improved greedy heuristic algorithms are proposed. A computational example is presented to show that the optimal location decisions are proved to be strongly dependent on the influence coefficients and average profits by one customer and different types of facilities are almost co-located. Finally the results of sensitivity analysis are reported.

This paper designs a 3 mm radiometer and validate with experiments based on the principle of passive millimeter wave (PMMW) imaging. The poor spatial resolution, which is limited by antenna size, should be improved by post data processing. A conjugate-gradient (CG) algorithm is adopted to circumvent this drawback. Simulation and real data collected in laboratory environment are given, and the results show that the CG algorithm improves the spatial resolution and convergent rate. Further, it can reduce the ringing effects which are caused by regularizing the image restoration. Thus, the CG algorithm is easily implemented for PMMW imaging.

A mathematical model to determine the optimal production lot size for a deteriorating production system under an extended product inspection policy is developed. The last-K product inspection policy is considered so that the nonconforming items can be reduced, under which the last K products in a production lot are inspected and the nonconforming items from those inspected are reworked. Consider that the products produced towards the end of a production lot are more likely to be nonconforming, is proposed an extended product inspection policy for a deteriorating production system. That is, in a production lot, product inspections are performed among the middle K1 items and after inspections, all of the last K2 products are directly reworked without inspections. Our objective here is the joint optimization of the production lot size and the corresponding extended inspection policy such that the expected total cost per unit time is minimized. Since there is no closed form expression for our optimal policy, the existence for the optimal production inspection policy and an upper bound for the optimal lot size are obtained. Furthermore, an efficient solution procedure is provided to search for the optimal policy. Finally, numerical examples are given to illustrate the proposed model and indicate that the expected total cost per unit time of our product inspection model is less than that of the last-K inspection policy.

By using two-directional S-rough sets, the concepts of (f, ¯ f)-interference generation and (f, ¯ f)- interference law generation of knowledge, F-interference generation and F-interference law generation of two-directional S-rough sets are proposed. Based on the concepts above, the relation theorems between F- interference loss and F-interference degree, the relation theorems between F-interference loss law and F-interference degree law, the discernibility theorems between F-interference and F-interference law are presented. At last, the recognition criterion of F-interference law and its application are given.

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.

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 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.

The design and performance analysis of networked control systems with random network delay in the forward channel is proposed, which are described in a state-space form. A new control scheme is used to overcome the effects of network transmission delay, which is termed networked predictive control (NPC). Furthermore, three different ways to choose control input are discussed and the performances are analyzed, respectively. Both real-time simulations and practical experiments show the effectiveness of the control scheme.

Based on the strategy of information feedback from followers to the leader, flocking control of a group of agents with a leader is studied. The leader tracks a pre-defined trajectory and at the same time the leader uses the feedback information from followers to the leader to modify its motion. The advantage of this control scheme is that it reduces the tracking errors and improves the robustness of the team cohesion to followers’ faults. The results of simulation are provided to illustrate that information feedback can improve the performance of the system.

The exponential passive filtering problem for a class of nonlinear Markov jump systems with uncertainties and time-delays is studied. The uncertain parameters are assumed unknown but norm bounded, and the nonlinearities satisfy the quadratic condition. Based on the passive filtering theory, the sufficient condition for the existence of the mode-dependent passive filter is given by analyzing the reconstructed observer system. By using the appropriate Lyapunov-Krasovskii function and applying linear matrix inequalities, the design scheme of the passive filter is derived and described as an optimization one. The presented exponential passive filter makes the error dynamic systems exponentially stochastically stable for all the admissible uncertainties, time-delays and nonlinearities, has the better abilities of state tracking and satisfies the given passive norm index. Simulation results demonstrate the validity of the proposed approach.

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.

The non-minimum phase feature of tail-controlled missile airframes is analyzed. Three selection strategies for desired performance indexes are presented. An acceleration autopilot design methodology based on output feedback and optimization is proposed. Performance and robustness comparisons between the two-loop and classical three-loop topologies are made. Attempts to improve the classical three-loop topology are discussed. Despite the same open-loop structure, the classical three-loop autopilot shows distinct characteristics from a two-loop autopilot with PI compensator. Both the two-loop and three-loop topologies can stabilize a static unstable missile. However, the finite actuator resource is the crucial factor dominating autopilot function.

To accelerate the training of support vector domain description (SVDD), confidence support vector domain description (CSVDD) is proposed based on the observation that the description boundary is determined by a small subset of training data called support vectors. Namely, the number of training samples in the userdefined sphere is calculated and taken as the confidence measure, according to which the training samples are ranked in ascending order. Those former ranked ones are selected as the boundary targets for the SVDD training. Simulations on UCI data demonstrate the effectiveness and superiority of CSVDD: the number of training targets and the training time are reduced without any loss of accuracy.

Moving object extraction and classification are important problems in automated video surveillance systems. A background model based on region segmentation is proposed. An adaptive single Gaussian background model is used in the stable region with gradual changes, and a nonparametric model is used in the variable region with jumping changes. A generalized agglomerative scheme is used to merge the pixels in the variable region and fill in the small interspaces. A two-threshold sequential algorithmic scheme is used to group the background samples of the variable region into distinct Gaussian distributions to accelerate the kernel density computation speed of the nonparametric model. In the feature-based object classification phase, the surveillance scene is first partitioned according to the road boundaries of different traffic directions and then re-segmented according to their scene localities. The method improves the discriminability of the features in each partition. AdaBoost method is applied to evaluate the relative importance of the features in each partition respectively and distinguish whether an object is a vehicle, a single human, a human group, or a bike. Experimental results show that the proposed method achieves higher performance in comparison with the existing method.

A novel optimization algorithm called stochastic focusing search (SFS) for the real-parameter optimization is proposed. The new algorithm is a swarm intelligence algorithm, which is based on simulating the act of human randomized searching, and the human searching behaviors. The algorithm’s performance is studied using a challenging set of typically complex functions with comparison of differential evolution (DE) and three modified particle swarm optimization (PSO) algorithms, and the simulation results show that SFS is competitive to solve most parts of the benchmark problems and will become a promising candidate of search algorithms especially when the existing algorithms have some difficulties in solving certain problems.

The concept of F-knowledge is presented by employing S-rough sets. By engrafting and penetrating between the F-knowledge generated by S-rough sets and the RSA algorithm, the security transmission and recognition of multi-agent F-knowledge are proposed, which includes the security transmission of multi-agent F-knowledge with positive direction secret key and the security transmission of multi-agent F-knowledge with reverse direction secret key. Finally, the recognition criterion and the applications of F-knowledge are presented. The security of F-knowledge is a new application research direction of S-rough sets in information systems.

A simple and effective greedy algorithm for image approximation is proposed. Based on the matching pursuit approach, it is characterized by a reduced computational complexity benefiting from two major modifications. First, it iteratively finds an approximation by selecting M atoms instead of one at a time. Second, the inner product computations are confined within only a fraction of dictionary atoms at each iteration. The modifications are implemented very efficiently due to the spatial incoherence of the dictionary. Experimental results show that compared with full search matching pursuit, the proposed algorithm achieves a speed-up gain of 14.4∼36.7 times while maintaining the approximation quality.

Many difficult engineering problems cannot be solved by the conventional optimization techniques in practice. Direct searches that need no recourse to explicit derivatives are revived and become popular since the new century. In order to get a deep insight into this field, some notes on the direct searches for non-smooth optimization problems are made. The global convergence vs. local convergence and their influences on expected solutions for simulation-based stochastic optimization are pointed out. The sufficient and simple decrease criteria for step acceptance are analyzed, and why simple decrease is enough for globalization in direct searches is identified. The reason to introduce the positive spanning set and its usage in direct searches is explained. Other topics such as the generalization of direct searches to bound, linear and non-linear constraints are also briefly discussed.

To realize the requirement of diagnostic sequence optimization in the process of design for testability, the authors put forward an optimization method based on quantum-behaved particle swarm optimization (QPSO) algorithm. By a precedence ordering coding, the diagnostic sequence optimization can be translated into a precedence ordering problem in the multidimensional space of swarm. It can get the optimizing order quickly by using the
powerful and quick search capability of QPSO algorithm, and the order is the diagnostic sequence for the system. The realization of the method is simpler than other methods, and the results are more excellent than others, and it has been applied in the engineering practice.

Disassembly sequence planning (DSP) plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassembly sequence planning problems efficiently, a product disassembly hybrid graph model, which describes the connection, non-connection and precedence relationships between the product parts, is established based on the characteristic of disassembly. Further, the optimization model is provided to optimize disassembly sequence. And the solution methodology based on the genetic/simulated annealing algorithm with binary-tree algorithm is given. Finally, an example is analyzed in detail, and the result shows that the model is correct and efficient.