A novel direction of arrival (DOA) estimation method is proposed when uncorrelated, correlated, and coherent sources coexist under color noise field. The uncorrelated and correlated sources are firstly estimated using the conventional spatial spectrum estimation method, then the noise and uncorrelated sources in Toeplitz structure are eliminated using differencing, finally by exploiting the property of oblique projection, the contributions of correlated sources are then eliminated from the covariance matrix and only the coherent sources remain. So the coherent sources can be estimated by the technique of modified spatial smoothing. The number of sources resolved by this approach can exceed the number of array elements without repeatedly estimating correlated sources. Simulation results demonstrate the effectiveness and efficiency of our proposed method.

To evaluate the ranging performance of impulse radio ultra wideband (IR-UWB) signals, an experiment is performed in a typical indoor environment. In order to mitigate the ranging error caused by theoretical algorithm and practical circuits, one way-time difference of the arrival (OW-TDOA) ranging method and corresponding approaches are proposed and carried out according to the structure of UWB transceivers. Generalized maximum likelihood (GML) estimator based on energy detection is applied for the time of arrival estimation. The obtained results show that this UWB ranging system can achieve a relative high ranging accuracy in a multipath environment (e.g. about 5 cm at ranges up to 6 m), which is practical and meaningful for many sensor applications.

Motion estimation is an important and intensive task in video coding applications. Since the complexity of integer pixel search has been greatly reduced by the numerous fast ME algorithm, the computation overhead required by fractional pixel ME has become relatively significant. To reduce the complexity of the fractional pixel ME algorithm, a directionality-based fractional pixel ME algorithm is proposed. The proposed algorithm efficiently explores the neighborhood positions which with high probability to be the best matching around the minimum one and skips over other unlikely ones. Thus, the proposed algorithm can complete the search by examining only 3 points on appropriate condition instead of 17 search points in the search algorithm of reference software. The simulation results show that the proposed algorithm successfully optimizes the fractional-pixel motion search on both half and quarter-pixel accuracy and improves the processing speed with low PSNR penalty.

An improved scheme with cooperative diversity based on distributed space-time block coding (WCDDSTBC) is proposed, which effectively achieves diversity gains and improves the performance of the system by sharing some single-antenna users’ antennas to form a virtual antenna array and combining with distributed spacetime block coding (DSTBC) mode. Then the relation between the system BER and the interuser BER for WCDDSTBC scheme is theoretically derived and the closed-form expression of BER forWCD-DSTBC system is obtained. The simulation results show that the proposedWCD-DSTBC scheme achieves distinct gains over the non-cooperative multi-carrier CDMA (MC-CDMA) system. When system BER is 1e−3 and interuser BER is 1e−3, about 2.5 dB gain can be gotten. When interuser channel state information (CSI) outgoes the users’ individual CSI, about 3 dB gain is also achieved.

For multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, a joint timing synchronization and frequency offset acquisition algorithm based on fractional Fourier transform (FRFT) is proposed. The linear frequency modulation signals superimposed on the data signals are used as the training signals. By performing FRFT on the received signals and searching the peak value of the FRFT results, the receiver can realize timing synchronization and frequency offset acquisition simultaneously. Compared with the existing methods, the proposed algorithm can provide better timing synchronization performance and larger frequency offset acquisition range even under multi-path channels with low signal to noise ratio. Theoretical analysis and simulation results prove this point.

In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.

Spurious signals in direct digital frequency synthesizers (DDFSs) are partly caused by amplitude quantization and phase truncation, which affect their application to many wireless telecommunication systems. These signals are deterministic and periodic in the time domain, so they appear as line spectra in the frequency domain. Two types of spurious signals due to amplitude quantization are exactly formulated and compared in the time and frequency domains respectively. Then the frequency spectra and power levels of the spurious signals due to amplitude quantization in the absence of phase-accumulator truncation are emphatically analyzed, and the effects of the DDFS parameter variations on the spurious signals are thoroughly studied by computer simulation. And several important conclusions are derived which can provide theoretical support for parameter choice and spurious performance evaluation in the application of DDFSs.

Two variants of systematic resampling (S-RS) are proposed to increase the diversity of particles and thereby improve the performance of particle filtering when it is utilized for detection in Bell Laboratories Layered Space-Time (BLAST) systems. In the first variant, Markov chain Monte Carlo transition is integrated in the S-RS procedure to increase the diversity of particles with large importance weights. In the second one, all particles are first partitioned into two sets according to their importance weights, and then a double S-RS is introduced to increase the diversity of particles with small importance weights. Simulation results show that both variants can improve the bit error performance efficiently compared with the standard S-RS with little increased complexity.

Based on the analysis of impulse response properties, a scattering model of ultra wideband (UWB) radar targets is developed to estimate the target parameters exactly. With this model, two algorithms of multiple signal classification (MUSIC), and matrix pencil (MP), are introduced to calculate the scattering center parameters of targets and their performances are compared. The simulation experiments show that there are no differences in the estimation precision of MUSIC and MP methods when the signal-to-noise ratio (SNR) is larger than 13 dB. However, the MP method has a better performance than that of MUSIC method when the SNR is smaller than 13 dB. Besides, the time consuming of MP method is less than that of MUSIC method. Therefore, the MP algorithm is preferred for the parametric estimation of UWB radar targets.

A new deghosting method based on the generalized triangulation is presented. First, two intersection points corresponding to the emitter position are obtained by utilizing two azimuth angles and two elevation angles from two jammed 3-D radars (or 2-D passive sensors). Then, hypothesis testing based deghosting method in the multiple target scenarios is proposed using the two intersection points. In order to analyze the performance of the proposed method, the correct association probability of the true targets and the incorrect association probability of the ghost targets are defined. Finally, the Monte Carlo simulations are given for the proposed method compared with the hinge angle method in the cases of both two and three radars. The simulation results show that the proposed method has better performance than the hinge angle method in three radars case.

A direction-of-arrival (DOA) estimation algorithm based on direct data domain (D3) approach is presented. This method can accuracy estimate DOA using one snapshot modified data, called the temporal and spatial two-dimensional vector reconstruction (TSR) method. The key idea is to apply the D3 approach which can extract the signal of given frequency but null out other frequency signals in temporal domain. Then the spatial vector reconstruction processing is used to estimate the angle of the spatial coherent signal source based on extract signal data. Compared with the common temporal and spatial processing approach, the TSR method has a lower computational load, higher real-time performance, robustness and angular accuracy of DOA. The proposed algorithm can be directly applied to the phased array radar of coherent pulses. Simulation results demonstrate the performance of the proposed technique.

To preserve the sharp features and details of the synthetic aperture radar (SAR) image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform (NSBT) domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges are detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least
square-Gaussian scale mixture (BLS-GSM).

As one of the basic inventory cost models, the (Q, r) inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of “effective lead time” and “lead time demand”, which may lead to an imprecise inventory cost. Through the real-time statistic of the inventory quantities, this paper considers the precise (Q, r) inventory cost model of dual supplier procurement by using an infinitesimal dividing method. The traditional modeling method of the inventory cost for dual supplier procurement includes complex procedures. To reduce the complexity effectively, the presented method investigates the statistics properties in real-time of the inventory quantities with the application of the infinitesimal dividing method. It is proved that the optimal holding and shortage costs of dual supplier procurement are less than those of single supplier procurement respectively. With the assumption that both suppliers have the same distribution of lead times, the convexity of the cost function per unit time is proved. So the optimal solution can be easily obtained by applying the classical convex optimization methods. The numerical examples are given to verify the main conclusions.

To study the problems of multi-attribute decision making in which the attribute values are given in the form of linguistic fuzzy numbers and the information of attribute weights are incomplete, a new multi-attribute decision making model is presented based on the optimal membership and the relative entropy. Firstly, the definitions of the optimal membership and the relative entropy are given. Secondly, for all alternatives, a set of preference weight vectors are obtained by solving a set of linear programming models whose goals are all to maximize the optimal membership. Thirdly, a relative entropy model is established to aggregate the preference weight vectors, thus an optimal weight vector is determined. Based on this optimal weight vector, the algorithm of deviation degree minimization is proposed to rank all the alternatives. Finally, a decision making example is given to demonstrate the feasibility and rationality of this new model.

Function one direction S-rough sets have dynamic characteristics and law characteristics. By using the function one direction S-rough sets, this article presents the concepts of the f-hiding law, F-hiding law, f-hiding law dependence and F-hiding law dependence. Based on the concepts above, this article proposes the hidingdependence theorem of f-hiding laws, the hiding-dependence theorem of F-hiding laws, the hiding-dependence separation theorem, the hiding dependence-discovery principle of unknown laws. Finally, the application of the hiding dependence of hiding laws in the discovery of system laws is given.

The advantage of using a spline function to evaluate the trajectory parameters optimization is discussed. A new method that using adaptive varied terminal-node spline interpolation for solving trajectory optimization is proposed. And it is validated in optimizing the trajectory of guided bombs and extended range guided munitions (ERGM). The solutions are approximate to the real optimization results. The advantage of this arithmetic is that it can be used to solve the trajectory optimization with complex models. Thus, it is helpful for solving the practical engineering optimization problem.

Adaptive optimization is one of the means that agile organization of command and control resource (AOC2R) adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net (CPN) model of AOC2R and then searches for the result by ant colony optimization (ACO) algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.

The systematism of weapon combat is the typical characteristic of a modern battlefield. The process of combat is complex and the demand description of weapon system of systems (SoS) is difficult. Granular analyzing is an important method for solving the complex problem in the world. Granular thinking is introduced into the demand description of weapon SoS. Granular computing and granular combination based on a relation of compatibility is proposed. Based on the level of degree and degree of detail, the granular resolution of weapon SoS is defined and an example is illustrated at the end.

This paper presents a new trajectory linearization control scheme for a class of nonlinear systems subject to harmonic disturbance. It is supposed that the frequency of the disturbance is known, but the amplitude and the phase are unknown. A disturbance observer dynamics is constructed to estimate the harmonic disturbance, and then the estimation is used to implement a compensation control law to cancel the disturbance. By Lyapunov’s direct method, a rigorous poof shows that the composite error of the closed-loop system can approach zero exponentially. Finally, the proposed method is illustrated by the application to control of an inverted pendulum. Compared with two existing methods, the proposed method demonstrates better performance in tracking error and response time.

Radio frequency identification (RFID) has prominent advantages compared with other autoidentification technologies. Combining RFID with network technology, physical object tracking and information sharing can possibly be carried out in an innovative way. Regarding open-loop RFID applications, RFID public services infrastructure (PSI) is presented, PSI architecture is designed, and service modules are implemented, and a demonstrative application system, blood management and traceability system, is studied to verify PSI. Experimental results show the feasibility of the proposed architecture and the usability of PSI framework software.

A novel soft initial-rotation control system and an H∞ robust constant rotational speed controller (RCRSC) for a rotational MEMS (micro-electro-mechanical system) gyro are presented. The soft initial-rotation control system can prevent the possible tumbling down of the suspended rotor and ensure a smooth and fast initial-rotation process. After the initial-rotation process, in order to maintain the rotational speed accurately constant, the RCRSC is acquired through the mixed sensitivity design approach. Simulation results show that the actuation voltage disturbances from the internal carrier waves in the gyro is reduced by more than 15.3 dB, and the speed fluctuations due to typical external vibrations ranging from 10 Hz to 200 Hz can also be restricted to 10−3 rad/s order.

The problem of observer-based robust predictive control is studied for the singular systems with norm-bounded uncertainties and time-delay, and the design method of robust predictive observer-based controller is proposed. By constructing the Lyapunov function with the error terms, the infinite time domain “min-max” optimization problems are converted into convex optimization problems solving by the linear matrix inequality (LMI), and the sufficient conditions for the existence of this control are derived. It is proved that the robust stability of the closed-loop singular systems can be guaranteed by the initial feasible solutions of the optimization problems, and the regular and the impulse-free of the singular systems are also guaranteed. A simulation example illustrates the efficiency of this method.

This article is concerned with the problem of robust dissipative filtering for continuous-time polytopic uncertain neutral systems. The main purpose is to obtain a stable and proper linear filter such that the filtering error system is strictly dissipative. A new criterion for the dissipativity of neutral systems is first provided in terms of linear matrix inequalities (LMI). Then, an LMI sufficient condition for the existence of a robust filter is established and a design procedure is proposed for this type of systems. Two numerical examples are given. One illustrates the less conservativeness of the proposed criterion; the other demonstrates the validity of the filtering design procedure.

Gyro’s drift is not only the main drift error which influences gyro’s precision but also the primary factor that affects gyro’s reliability. Reducing zero drift and random drift is a key problem to the output of a gyro signal. A three-layer de-nosing threshold algorithm is proposed based on the wavelet decomposition to dispose the signal which is collected from a running fiber optic gyro (FOG). The coefficients are obtained from the three-layer wavelet packet decomposition. By setting the high frequency part which is greater than wavelet packet threshold as zero, then reconstructing the nodes which have been filtered out noise and interruption, the soft threshold function is constructed by the coefficients of the third nodes. Compared wavelet packet de-noise with forced de-noising method, the proposed method is more effective. Simulation results show that the random drift compensation is enhanced by 13.1%, and reduces zero drift by 0.052 6^?/h.

Recently, a two-dimensional (2-D) Tsallis entropy thresholding method has been proposed as a new method for image segmentation. But the computation complexity of 2-D Tsallis entropy is very large and becomes an obstacle to real time image processing systems. A fast recursive algorithm for 2-D Tsallis entropy thresholding is proposed. The key variables involved in calculating 2-D Tsallis entropy are written in recursive form. Thus, many repeating calculations are avoided and the computation complexity reduces to O(L2) fromO(L4). The effectiveness of the proposed algorithm is illustrated by experimental results.

To improve the agility, dynamics, composability, reusability, and development efficiency restricted by monolithic federation object model (FOM), a modular FOM is proposed by high level architecture (HLA) evolved product development group. This paper reviews the state-of-the-art of HLA evolved modular FOM. In particular, related concepts, the overall impact on HLA standards, extension principles, and merging processes are discussed. Also permitted and restricted combinations, and merging rules are provided, and the influence on HLA interface specification is given. The comparison between modular FOM and base object model (BOM) is performed to illustrate the importance of their combination. The applications of modular FOM are summarized. Finally, the significance to facilitate compoable simulation both in academia and practice is presented and future directions are pointed out.

Chain length of closed circle DNA is equal. The same closed circle DNA’s position corresponds to different recognition sequence, and the same recognition sequence corresponds to different foreign DNA segment, so closed circle DNA computing model is generalized. For change positive-weighted Hamilton circuit problem, closed circle DNA algorithm is put forward. First, three groups of DNA encoding are encoded for all arcs, and deck groups are designed for all vertices. All possible solutions are composed. Then, the feasible solutions are filtered out by using group detect experiment, and the optimization solutions are obtained by using group insert experiment and electrophoresis experiment. Finally, all optimization solutions are found by using detect experiment. Complexity of algorithm is concluded and validity of DNA algorithm is explained by an example. Three dominances of the closed circle DNA algorithm are analyzed, and characteristics and dominances of group delete experiment are discussed.

In many machine learning problems, a large amount of data is available but only a few of them can be labeled easily. This provides a research branch to effectively combine unlabeled and labeled data to infer the labels of unlabeled ones, that is, to develop transductive learning. In this article, based on Pattern classification via single sphere (SSPC), which seeks a hypersphere to separate data with the maximum separation ratio, a progressive transductive pattern classification method via single sphere (PTSSPC) is proposed to construct the classifier using both the labeled and unlabeled data. PTSSPC utilize the additional information of the unlabeled samples and obtain better classification performance than SSPC when insufficient labeled data information is available. Experiment results show the algorithm can yields better performance.

To avoid the curse of dimensionality, text categorization (TC) algorithms based on machine learning (ML) have to use an feature selection (FS) method to reduce the dimensionality of feature space. Although having been widely used, FS process will generally cause information losing and then have much side-effect on the whole performance of TC algorithms. On the basis of the sparsity characteristic of text vectors, a new TC algorithm based on lazy feature selection (LFS) is presented. As a new type of embedded feature selection approach, the LFS method can greatly reduce the dimension of features without any information losing, which can improve both efficiency and performance of algorithms greatly. The experiments show the new algorithm can simultaneously achieve much higher both performance and efficiency than some of other classical TC algorithms.

An embedded cryptosystem needs higher reconfiguration capability and security. After analyzing the newly emerging side-channel attacks on elliptic curve cryptosystem (ECC), an efficient fractional width-w NAF (FWNAF) algorithm is proposed to secure ECC scalar multiplication from these attacks. This algorithm adopts the fractional window method and probabilistic SPA scheme to reconfigure the pre-computed table, and it allows designers to make a dynamic configuration on pre-computed table. And then, it is enhanced to resist SPA, DPA, RPA and ZPA attacks by using the random masking method. Compared with the WBRIP and EBRIP methods, our proposals has the lowest total computation cost and reduce the shake phenomenon due to sharp fluctuation on computation performance.

In order to indicate the performances of a large-scale communication network with domain partition and interconnection today, a kind of reliability index weighed by normalized capacity is defined. Based on the route rules of network with domain partition and interconnection, the interconnection indexes among the nodes within the domain and among the domains are given from several aspects. It is expatiated on that the index can thoroughly represent the effect on the reliability index of the objective factor and the subjective measures of the designer, which obeys the route rules of a network with domain partition and interconnection. It is discussed that the defined index is rational and compatible with the traditional index.