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Recently, the ontological metamodel plays an increasingly important role to specify systems in two forms: ontology and metamodel. Ontology is a descriptive model representing reality by a set of concepts, their interrelations, and constraints. On the other hand, metamodel is a more classical, but more powerful model in which concepts and relationships are represented in a prescriptive way. This study firstly clarifies the difference between the two approaches, then explains their advantages and limitations, and attempts to explore a general ontological metamodeling framework by integrating each characteristic, in order to implement semantic simulation model engineering. As a proof of concept, this paper takes the combat effectiveness simulation systems as a motivating case, uses the proposed framework to define a set of ontological composable modeling frameworks, and presents an underwater targets search scenario for running simulations and analyzing results. Finally, this paper expects that this framework will be generally used in other fields. [ABSTRACT FROM AUTHOR]

Under the conditions of strong sea clutter and complex moving targets, it is extremely difficult to detect moving targets in the maritime surface. This paper proposes a new algorithm named improved tunable Q-factor wavelet transform (TQWT) for moving target detection. Firstly, this paper establishes a moving target model and sparsely compensates the Doppler migration of the moving target in the fractional Fourier transform (FRFT) domain. Then, TQWT is adopted to decompose the signal based on the discrimination between the sea clutter and the target's oscillation characteristics, using the basis pursuit denoising (BPDN) algorithm to get the wavelet coefficients. Furthermore, an energy selection method based on the optimal distribution of sub-bands energy is proposed to sparse the coefficients and reconstruct the target. Finally, experiments on the Council for Scientific and Industrial Research (CSIR) dataset indicate the performance of the proposed method and provide the basis for subsequent target detection. [ABSTRACT FROM AUTHOR]

Owing to the wide range of applications in various fields, generative models have become increasingly popular. However, they do not handle spatio-temporal features well. Inspired by the recent advances in these models, this paper designs a distributed spatio-temporal generative adversarial network (STGAN-D) that, given some initial data and random noise, generates a consecutive sequence of spatio-temporal samples which have a logical relationship. This paper builds a spatio-temporal discriminator to distinguish whether the samples generated by the generator meet the requirements for time and space coherence, and builds a controller for distributed training of the network gradient updated to separate the model training and parameter updating, to improve the network training rate. The model is trained on the skeletal dataset and the traffic dataset. In contrast to traditional generative adversarial networks (GANs), the proposed STGAN-D can generate logically coherent samples with the corresponding spatial and temporal features while avoiding mode collapse. In addition, this paper shows that the proposed model can generate different styles of spatio-temporal samples given different random noise inputs, and the controller can improve the network training rate. This model will extend the potential range of applications of GANs to areas such as traffic information simulation and multiagent adversarial simulation. [ABSTRACT FROM AUTHOR]

In the case of the given design variables and constraint functions, this paper is concerned with the rapid overall parameters design of trajectory, propulsion and aerodynamics for long-range ballistic missiles based on the index of the minimum take-off mass. In contrast to the traditional subsystem independent design, this paper adopts the research idea of the combination of the subsystem independent design and the multisystem integration design. Firstly, the trajectory, propulsion and aerodynamics of the subsystem are separately designed by the engineering design, including the design of the minimum energy trajectory, the computation of propulsion system parameters, and the calculation of aerodynamic coefficient and dynamic derivative of the missile by employing the software of missile DATCOM. Then, the uniform design method is used to simplify the constraint conditions and the design variables through the integration design, and the accurate design of the optimized variables would be accomplished by adopting the uniform particle swarm optimization (PSO) algorithm. Finally, the automation design software is written for the three-stage solid ballistic missile. The take-off mass of 29 850 kg is derived by the subsystem independent design, and 20 constraints are reduced by employing the uniform design on the basis of 29 design variables and 32 constraints, and the take-off mass is dropped by 1 850 kg by applying the combination of the uniform design and PSO. The simulation results demonstrate the effectiveness and feasibility of the proposed hybrid optimization technique. [ABSTRACT FROM AUTHOR]

In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic priority. However, the priority of the imaging task is dynamic in actual engineering. To supplement the research on imaging observation, this paper proposes the task priority model, dynamic scheduling strategy and Heuristic algorithm. At first, this paper analyzes the relevant theoretical basis of imaging observation, decomposes the task priority into four parts, including target priority, imaging task priority, track, telemetry & control (TT&C) requirement priority and data transmission requirement priority, summarizes the attribute factors that affect the above four types of priority in detail, and designs the corresponding priority model. Then, this paper takes the emergency tasks scheduling problem as the background, proposes the dynamic scheduling strategy and heuristic algorithm. Finally, the task priority model, dynamic scheduling strategy and heuristic algorithm are verified by experiments. [ABSTRACT FROM AUTHOR]

Measuring the business-IT alignment (BITA) of an organization determines its alignment level, provides directions for further improvements, and consequently promotes the organizational performances. Due to the capabilities of enterprise architecture (EA) in interrelating different business/IT viewpoints and elements, the development of EA is superior to support BITA measurement. Extant BITA measurement literature is sparse when it concerns EA. The literature tends to explain how EA viewpoints or models correlate with BITA, without discussing where to collect and integrate EA data. To address this gap, this paper attempts to propose a specific BITA measurement process through associating a BITA maturity model with a famous EA framework: DoD Architectural Framework 2.0 (DoDAF2.0). The BITA metrics in the maturity model are connected to the meta-models and models of DoDAF2.0. An illustrative ArchiSurance case is conducted to explain the measurement process. Systematically, this paper explores the process of BITA measurement from the viewpoint of EA, which helps to collect the measurement data in an organized way and analyzes the BITA level in the phase of architecture development. [ABSTRACT FROM AUTHOR]

Performance degradation or system resource exhaustion can be attributed to inadequate computing resources as a result of software aging. In the real world, the workload of a web server varies with time, which will cause a nonlinear aging phenomenon. The nonlinear property often makes analysis and modelling difficult. Workload is one of the important factors influencing the speed of aging. This paper quantitatively analyzes the workload-aging relation and proposes a framework for aging control under varying workloads. In addition, this paper proposes an approach that employs prior information of workloads to accurately forecast incoming system exhaustion. The workload data are used as a threshold to divide the system resource usage data into multiple sections, while in each section the workload data can be treated as a constant. Each section is described by an individual autoregression (AR) model. Compared with other AR models, the proposed approach can forecast the aging process with a higher accuracy. [ABSTRACT FROM AUTHOR]

In order to cope with the increasing threat of the ballistic missile (BM) in a shorter reaction time, the shooting policy of the layered defense system needs to be optimized. The main decisionmaking problem of shooting optimization is how to choose the next BM which needs to be shot according to the previous engagements and results, thus maximizing the expected return of BMs killed or minimizing the cost of BMs penetration. Motivated by this, this study aims to determine an optimal shooting policy for a two-layer missile defense (TLMD) system. This paper considers a scenario in which the TLMD system wishes to shoot at a collection of BMs one at a time, and to maximize the return obtained from BMs killed before the system demise. To provide a policy analysis tool, this paper develops a general model for shooting decision-making, the shooting engagements can be described as a discounted reward Markov decision process. The index shooting policy is a strategy that can effectively balance the shooting returns and the risk that the defense mission fails, and the goal is to maximize the return obtained from BMs killed before the system demise. The numerical results show that the index policy is better than a range of competitors, especially the mean returns and the mean killing BM number [ABSTRACT FROM AUTHOR]

This paper studies the adaptive beamforming algorithm based on the frequency diverse array (FDA) array where the interference is located at the same angle (but different range) with the target. We take the cross subarray-based FDA with sinusoidal frequency offset (CSB sin-FDA) as the receiving array instead of the basic FDA. The sampling covariance matrix under insufficient snapshot can be corrected by the automatic diagonal loading method. On the basis of decomposing the mismatched steering vector error into a vertical component and a parallel one, this paper searches the vertical component of the error by the quadratic constraint method. The numerical simulation verifies that the beamformer based on the CSB sin-FDA can effectively hold the mainlobe at the target position when the snapshot is insufficient or the steering vector is mismatched. [ABSTRACT FROM AUTHOR]

In many practical applications of image segmentation problems, employing prior information can greatly improve segmentation results. This paper continues to study one kind of prior information, called prior distribution. Within this research, there is no exact template of the object; instead only several samples are given. The proposed method, called the parametric distribution prior model, extends our previous model by adding the training procedure to learn the prior distribution of the objects. Then this paper establishes the energy function of the active contour model (ACM) with consideration of this parametric form of prior distribution. Therefore, during the process of segmenting, the template can update itself while the contour evolves. Experiments are performed on the airplane data set. Experimental results demonstrate the potential of the proposed method that with the information of prior distribution, the segmentation effect and speed can be both improved efficaciously. [ABSTRACT FROM AUTHOR]

In a system of systems (SoS), resilience is an important factor in maintaining the functionality, stability, and enhancing the operation effectiveness. From the perspective of resilience, this paper studies the importance of the SoS, and a resilience-based importance measure analysis is conducted to provide suggestions in the design and optimization of the structure of the SoS. In this paper, the components of the SoS are simplified as four kinds of network nodes: sensor, decision point, influencer, and target. In this networked SoS, the number of operation loops is used as the performance indicator, and an approximate algorithm, which is based on eigenvalue of the adjacency matrix, is proposed to calculate the number of operation loops. In order to understand the performance change of the SoS during the attack and defense process in the operations, an integral resilience model is proposed to depict the resilience of the SoS. From different perspectives of enhancing the resilience, different measures, parameters and the corresponding algorithms for the resilience importance of components are proposed. Finally, a case study on an SoS is conducted to verify the validity of the network modelling and the resilience-based importance analysis method. [ABSTRACT FROM AUTHOR]

The accurate quantification of human error probability (HEP) has long been a main pursuit for most human reliability analysis (HRA) methods. This paper proposes a strategy to analyze and predict human error on the basis of a further modification of the existing cognitive reliability and error analysis method (CREAM) in HRA. Through providing a broader definition for the key parameters used in the quantification method, this paper produces a relatively flexible strategy to determine the nominal HEP (HEP0). Basing on this strategy, the actual quantification of HEP in CREAM is able to be applied to more verified conditions. To prove the validity of the method proposed, a case study of spacecraft launch is also introduced, in which the prediction derived from the method is proved consistent with real field data. [ABSTRACT FROM AUTHOR]

This paper presents the design of an experimental battlefield dynamic scanning and staring imaging system based on a fast steering mirror (FSM), which is capable of real-time monitoring of hot targets and wide-area reconnaissance of hot regions. First, the working principle and working sequence of the FSM are briefly analyzed. The mathematical model of the FSM system is built by modeling its dynamic and electrical properties, and the rationality of the model is validated by means of model identification. Second, the influence of external sources of disturbance such as the carrier and moment on the control precision of the FSM is effectively suppressed by the jointly controlling of proportional integral (PI) and disturbance observer (DOB), thus realizing a high precision and strong robustness control of the FSM system. Then, this paper designs an experimental prototype and introduces a special optical structure to enable the infrared camera to share the FSM with the visible light camera. Finally, the influence of the velocity difference between the mirror of the FSM and the rotating platform on the imaging quality of the system is experimentally analyzed by using the image sharpness evaluation method based on point sharpness. A good dynamic scanning and staring imaging result is achieved when the velocity of these two components correspond. [ABSTRACT FROM AUTHOR]

While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection of objects with multiple aspect ratios and scales is still a key problem. This paper proposes a top-down and bottom-up feature pyramid network (TDBU-FPN), which combines multi-scale feature representation and anchor generation at multiple aspect ratios. First, in order to build the multi-scale feature map, this paper puts a number of fully convolutional layers after the backbone. Second, to link neighboring feature maps, top-down and bottom-up flows are adopted to introduce context information via top-down flow and supplement suboriginal information via bottom-up flow. The top-down flow refers to the deconvolution procedure, and the bottom-up flow refers to the pooling procedure. Third, the problem of adapting different object aspect ratios is tackled via many anchor shapes with different aspect ratios on each multi-scale feature map. The proposed method is evaluated on the pattern analysis, statistical modeling and computational learning visual object classes (PASCAL VOC) dataset and reaches an accuracy of 79%, which exhibits a 1.8% improvement with a detection speed of 23 fps. [ABSTRACT FROM AUTHOR]

To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing (LIP) model, this paper proposes what we believe to be an effective image enhancement algorithm. This algorithm introduces fuzzy entropy, makes full use of neighborhood information, fuzzy information and human visual characteristics. To enhance an image, this paper first carries out the reasonable fuzzy-3 partition of its histogram into the dark region, intermediate region and bright region. It then extracts the statistical characteristics of the three regions and adaptively selects the parameter α according to the statistical characteristics of the image’s gray-scale values. It also adds a useful nonlinear transform, thus increasing the ubiquity of the algorithm. Finally, the causes for the gray-scale value overcorrection that occurs in the traditional image enhancement algorithms are analyzed and their solutions are proposed. The simulation results show that our image enhancement algorithm can effectively suppress the noise of an image, enhance its contrast and visual effect, sharpen its edge and adjust its dynamic range. [ABSTRACT FROM AUTHOR]

The impact angle control over guidance (IACG) law against stationary targets is proposed by using feedback linearization control (FLC) and finite time control (FTC). First, this paper transforms the kinematics equation of guidance systems into the feedbackable linearization model, in which the guidance law is obtained without considering the impact angle via FLC. For the purpose of the line of sight (LOS) angle and its rate converging to the desired values, the second-order LOS angle is considered as a double-integral system. Then, this paper utilizes FTC to design a controller which can guarantee the states of the double-integral system converging to the desired values. Numerical simulation illustrates the performance of the IACG, in contrast to the existing guidance law. [ABSTRACT FROM AUTHOR]

This paper links parallel factor (PARAFAC) analysis to the problem of nominal direction-of-arrival (DOA) estimation for coherently distributed (CD) sources and proposes a fast PARAFAC-based algorithm by establishing the trilinear PARAFAC model. Relying on the uniqueness of the low-rank three-way array decomposition and the trilinear alternating least squares regression, the proposed algorithm achieves nominal DOA estimation and outperforms the conventional estimation of signal parameter via rotational technique CD (ESPRIT-CD) and propagator method CD (PM-CD) methods in terms of estimation accuracy. Furthermore, by means of the initialization via the propagator method, this paper accelerates the convergence procedure of the proposed algorithm with no estimation performance degradation. In addition, the proposed algorithm can be directly applied to the multiple-source scenario, where sources have different angular distribution shapes. Numerical simulation results corroborate the effectiveness and superiority of the proposed fast PARAFAC-based algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a suppression method of the deceptive false target (FT) produced by digital radio frequency memory (DRFM) in a multistatic radar system. The simulated deceptive false targets from DRFM cannot be easily discriminated and suppressed with traditional radar systems. Therefore, multistatic radar has attracted considerable interest as it provides improved performance against deception jamming due to several separated receivers. This paper first investigates the received signal model in the presence of multiple false targets in all receivers of the multistatic radar. Then, obtain the propagation time delays of the false targets based on the cross-correlation test of the received signals in different receivers. In doing so, local-density-based spatial clustering of applications with noise (LDBSCAN) is proposed to discriminate the FTs from the physical targets (PTs) after compensating the FTs time delays, where the FTs are approximately coincident with one position, while PTs possess small dispersion. Numerical simulations are carried out to demonstrate the feasibility and validness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper analyses the issue of impact time control of super-cavitation weapons impact fixed targets which mainly refer to the ships or submarines who lost power, but still have combat capability. Control over impact time constraints of guidance law (ITCG) is derived by using sliding mode control (SMC) and Lyapunov stability theorem. The expected impact time is realized by using the notion of attack process and estimated time-to-go to design sliding mode surface (SMS). ITCG contains equivalent and discontinuous guidance laws, once state variables arrive at SMS, the equivalent guidance law keeps the state variables on SMS, then the discontinuous guidance law enforces state variables to move and reach SMS. The singularity problem of ITCG is also analyzed. Theoretical analysis and numerical simulation results are given to test the effectiveness of ITCG designed in this paper. [ABSTRACT FROM AUTHOR]

This paper proposes a novel dynamic Petri net (PN) model based on Dempster-Shafer (D-S) evidence theory, and this improved evidential Petri net (EPN) model is used in knowledge inference and reliability analysis of complex mechanical systems. The EPN could take epistemic uncertainty such as interval information, subjective information into account by applying D-S evidence quantification theory. A dynamic representation model is also proposed based on the dynamic operation rules of the EPN model, and an improved artificial bee colony (ABC) algorithm is employed to proceed optimization calculation during the complex systems' learning process. The improved ABC algorithm and D-S evidence theory overcome the disadvantage of extremely subjective in traditional knowledge inference efficiently and thus could improve the accuracy of the EPN learning model. Through a simple numerical case and a satellite driving system analysis, this paper proves the superiority of the EPN and the dynamic knowledge representation method in reliability analysis of complex systems. [ABSTRACT FROM AUTHOR]

This paper proposes a desirable method to detect different kinds of low probability of intercept (LPI) radar signals, targeted at the main intra-pulse modulation method of LPI radar signals including the signals of linear frequency modulation, phase code, and frequency code. Firstly, it improves the coherent integration of LPI radar signals by adding the periodicity of the ambiguity function. Then, it develops a frequency domain detection method based on fast Fourier transform (FFT) and segmented autocorrelation function to detect signals without features of linear frequency modulation by virtue of the distribution characteristics of noise signals in the frequency domain. Finally, this paper gives a verification of the performance of the method for different signal-to-noise ratios by conducting simulation experiments, and compares the method with existing ones. Additionally, this method is characterized by the straightforward calculation and high real-time performance, which is conducive to better detecting all kinds of LPI radar signals. [ABSTRACT FROM AUTHOR]

This paper considers an optimal sequential inspection schedule for a second-hand product after that the free nonrenewable warranty is expired. The length of warranty is prespecified and during the warranty period, the product is minimally repaired by the dealer when it fails. Following the expiration of the non-renewing warranty, the product is inspected and upgraded sequentially a fixed number of times at the expenses of the customer. At each inspection, the failure rate of the product is reduced proportionally so that the product is upgraded. The product is assumed to deteriorate as it ages and the replacement of the product occurs when a fixed number of inspections are rendered. In addition, the intervals between two successive inspections are assumed to decrease monotonically. The main objective of this paper is to determine the optimal improvement level to upgrade the product at each inspection so that the expected maintenance cost during the life cycle of the product is minimized from the perspective of the customer. Under the given cost structures, we derive an explicit formula to ootain the expected maintenance cost incurred during the life cycle of the product and discuss the method to find the optimal level of the improvement analytically in case the failure times follow the Weibull distribution. Numerical results are analyzed to observe the impact of relevant parameters on the optimal solution. [ABSTRACT FROM AUTHOR]

The analog-to-information convertor (AIC) is a successful practice of compressive sensing (CS) theory in the analog signal acquisition. This paper presents a multi-narrowband signals sampling and reconstruction model based on AIC and block sparsity. To overcome the practical problems, the block sparsity is divided into uniform block and non-uniform block situations, and the block restricted isometry property and sub-sampling limit in different situations are analyzed respectively in detail. Theoretical analysis proves that using the block sparsity in AIC can reduce the restricted isometric constant, increase the reconstruction probability and reduce the sub-sampling rate. Simulation results show that the proposed model can complete sub-sampling and reconstruction for multi-narrowband signals. This paper extends the application range of AIC from the finite information rate signal to the multi-narowband signals by using the potential relevance of support sets. The proposed receiving model has low complexity and is easy to implement, which can promote the application of CS theory in the radar receiver to reduce the burden of analog-todigital convertor (ADC) and solve bandwidth limitations of ADC. [ABSTRACT FROM AUTHOR]

Fuze is the information processing and control unit of the ammunition, so the quality of the fuze becomes one of the most important aspects of ammunition detection. Since using recoil force is a common method to the arm fuze, its dynamic simulation test has always been the focus of the fuze test research. A new fuze recoil environmental simulation method is proposed based on the electromagnetic launcher. Then the trigger control characteristics of the fuze recoil simulation system and the influence of the trigger position on the recoil force are studied. The results of the study show that although the pulse width of the armature force curve can be changed by adjusting the trigger position, due to the limit of the range, there also exists the contradiction that the electromagnetic pulse width gets narrow with the increase of electromagnetic force peak. Thus, it cannot meet the requirements of the fuze launch recoil simulation. In order to make the recoil force close to the actual environment, the multi-stage trigger control characteristics are analyzed, and the influence of trigger position on recoil environmental force characteristics is studied. Then a fuze launch recoil environmental simulation platform is established and continuous electromagnetic force is achieved by using the trigger strategy. Finally, the experiment is performed to simulate the fuze launch recoil environment and show the feasibility and effectiveness of the proposed theoretical analysis. The major research work of this paper includes studying the composition and basic principle of the simulation system, establishing a launch model to analyze the single-stage and multi-stage coil fuze launch recoil characteristics, designing the test device to verify the correctness and validity of the research. This paper draws the conclusions that the feasibility of the fuze launch environmental simulation based on the electromagnetic launcher is verified, the trigger position has a great influence on force peak continuity, the problems of low maximum overload peak and short peak duration in the multi-stage coil fuze launch environmental simulation can be effectively solved through adjusting the trigger position, the system has creative and extensive application prospects. [ABSTRACT FROM AUTHOR]

With the development of multi-autonomous underwater vehicle (AUV) cooperative systems, the evaluation of their reliability is becoming more and more important. Since AUVs are always in motion, the reliability of the system is not stationary, but it varies with time. This paper studies the time-varying reliability evaluation indexes for multi-AUV cooperative systems. Aimed at elucidating the characteristics of the system, by considering the motion of the AUVs, two time dependent reliability evaluation indexes, natural connectivity and all-terminal reliability of the basic reliability indexes, are determined with the graph theory. Then the time-varying reliability of multi-AUV cooperative systems is evaluated combining with an actual example. This paper provides a method to evaluate the time-varying reliability of multi-AUV cooperative systems. [ABSTRACT FROM AUTHOR]

The fractal properties of sea clutter are proposed and applied to the maritime target detection. Calculation of the measured data shows that, the Hurst exponent of the sea clutter with targets and the sea clutter without targets are different, which enables us to detect low-observable targets within the sea clutter. This paper explains the reason why the Hurst exponent can distinguish the presence or absence of targets in theory and proposes a fractal detector based on the Hurst exponent. Comparing the fractal detector proposed in this paper to the energy detector by the detection results of 140 frames data of the real sea clutter, it is demonstrated that the fractal detection method has a better detection performance. In order to get systemic conclusions, the new sea clutter data with different signal-to-clutter ratios (SCRs) are constructed in the way that add the sea clutter data with targets to the pure sea clutter data. The results show that the fractal detection method has a better performance than the statistical method on detection of maritime targets, especially maritime weak targets with low SCR. [ABSTRACT FROM AUTHOR]

With the development of multi-autonomous underwater vehicle (AUV) cooperative systems, the evaluation of their reliability is becoming more and more important. Aimed at the characteristics of the system, three reliability indexes-standard entropy of rank distribution, all-terminal reliability and standard natural connectivity are determined in this paper. Topology structure and underwater acoustic communication are considered. The calculation methods of the three reliability indexes are proposed, and the characteristics of these indexes are analyzed. The reliability indexes of two multi-AUV cooperative systems are obtained as examples. Results show that these three indexes reflect different aspects of reliability for multi-AUV cooperative systems. This paper provides some methods to evaluate the reliability of multi-AUV cooperative systems, which is of practical value. [ABSTRACT FROM AUTHOR]

In order to solve the problem that previous relation researches in operational task-resource matching are hard to flexible computing for generating a new matching scheme from the existing scheme under the condition of operational tasks or resources adjusted in uncertainty cases, role-based approaches to operational task-resource flexible matching model and algorithm are proposed in the paper for flexible matching operational tasks with resources. Firstly, through introducing the concept of roles, the role-based calculation framework of operational task-resource flexible matching is constructed. Secondly, two aspect indexes about resource utilization ratio (RUR) and time utilization ratio (TUR) are given to reflect operational task-resource matching quality (TRMQ), which can be regarded as the objective function for modeling role-based operational task-resource flexible matching mathematical formulation. On the basis of this, the role-based artificial bee colony (RABC) algorithm, including five specific calculating operators, is put forward for solving the flexible matching problem with double encoding on operational tasks and resources by roles. Finally, via comparing with the previous methods in application cases, it can be validated that role-based model and proposed algorithm are more effective, which can be used to obtain a new incremental scheme from the existing matching scheme for adopting the operational tasks or resources adjustment. Moreover, there are flexible computation advantages of the approaches proposed in this paper to solve the problem about operational task-resource matching in large-scale. [ABSTRACT FROM AUTHOR]

Imaging precession targets based on the narrowband radar to distinguish the real warhead from mid-course targets is a new technique in missile defense systems. Aiming at the typical mid-course flying scene, this paper describes the principle of the narrowband imaging method, and analyzes the influence on the narrowband imaging by the target translational motion. Then the precision qualification is deduced for both the distance compensation and the velocity compensation, and the conclusion that the velocity compensation is more appropriate for the motion compensation in the narrowband imaging is given. Furthermore, this paper proposes a motion compensation algorithm for the narrowband radar which reduces the interference of the signal phase chaos caused by the rebuilt real signal phase, thus realizing the precise translational motion compensation of the narrowband signal. Finally, the effectiveness of this method is proved by both theoretic analysis and experiment results. [ABSTRACT FROM AUTHOR]

To fully display the modeling mechanism of the novel fractional order grey model (FGM (q,1)), this paper decomposes the data matrix of the model into the mean generation matrix, the accumulative generation matrix and the raw data matrix, which are consistent with the fractional order accumulative grey model (FAGM (1,1)). Following this, this paper decomposes the accumulative data difference matrix into the accumulative generation matrix, the q-order reductive accumulative matrix and the raw data matrix, and then combines the least square method, finding that the differential order affects the model parameters only by affecting the formation of differential sequences. This paper then summarizes matrix decomposition of some special sequences, such as the sequence generated by the strengthening and weakening operators, the jumping sequence, and the non-equidistance sequence. Finally, this paper expresses the influences of the raw data transformation, the accumulation sequence transformation, and the differential matrix transformation on the model parameters as matrices, and takes the non-equidistance sequence as an example to show the modeling mechanism. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of service composition in military organization cloud cooperation (MOCC). Military service providers (MSP) cooperate together to provide military resources for military service users (MSU). A group of atom services, each of which has its level of quality of service (QoS), can be combined together into a certain structure to form a composite service. Since there are a large number of atom services having the same function, the atom service is selected to participate in the composite service so as to fulfill users' will. In this paper a method based on discrete particle swarm optimization (DPSO) is proposed to tackle this problem. The method aims at selecting atom services from service repositories to constitute the composite service, satisfying the MSU's requirement on QoS. Since the QoS criteria include location-aware criteria and location-independent criteria, this method aims to get the composite service with the highest location-aware criteria and the best-match location-independent criteria. Simulations show that the DPSO has a better performance compared with the standard particle swarm optimization (PSO) and genetic algorithm (GA). [ABSTRACT FROM AUTHOR]

This paper focuses on the recognition rate comparison for competing recognition algorithms, which is a common problem of many pattern recognition research areas. The paper firstly reviews some traditional recognition rate comparison procedures and discusses their limitations. A new method, the posterior probability calculation (PPC) procedure is then proposed based on Bayesian technique. The paper analyzes the basic principle, process steps and computational complexity of the PPC procedure. In the Bayesian view, the posterior probability represents the credible degree (equal to confidence level) of the comparison results. The posterior probability of correctly selecting or sorting the competing recognition algorithms is derived, and the minimum sample size requirement is also pre-estimated and given out by the form of tables. To further illustrate how to use our method, the PPC procedure is used to prove the rationality of the experiential choice in one application and then to calculate the confidence level with the fixed-size datasets in another application. These applications reveal the superiority of the PPC procedure, and the discussions about the stopping rule further explain the underlying statistical causes. Finally we conclude that the PPC procedure achieves all the expected functions and be superior to the traditional methods. [ABSTRACT FROM AUTHOR]

This paper provides a direct and fast acquisition algorithm of civilian long length (CL) codes in the L2 civil (L2C) signal. The proposed algorithm simultaneously reduces the number of fast Fourier transformation (FFT) correlation through hyper code technique and the amount of points in every FFT correlation by using an averaging correlation method. To validate the proposed acquisition performance, the paper applies this algorithm to the real L2C signal collected by the global positioning system (GPS) L2C intermediate frequency (IF) signal sampler--SIS100L2C. The acquisition results show that the proposed modified algorithm can acquire the code phase accurately with less calculation and its acquisition performance is better than the single hyper code method. [ABSTRACT FROM AUTHOR]

This paper improves the resampling step of particle filtering (PF) based on a broad interactive genetic algorithm to resolve particle degeneration and particle shortage. For target tracking in image processing, this paper uses the information coming from the particles of the previous fame image and new observation data to self-adaptively determine the selecting range of particles in current fame image. The improved selecting operator with jam gene is used to ensure the diversity of particles in mathematics, and the absolute arithmetical crossing operator whose feasible solution space being close about crossing operation, and non-uniform mutation operator is used to capture all kinds of mutation in this paper. The result of simulating experiment shows that the algorithm of this paper has better iterative estimating capability than extended Kalman filtering (EKF), PF, regularized partide filtering (RPF), and genetic algorithm (GA)-PF. [ABSTRACT FROM AUTHOR]

Coordinated multi-point (CoMP) transmission is put forward in the long term evolution-advanced (LTE-A) system to improve both average and cell-edge throughput. CoMP-joint processing (JP) scheme can get a larger cell-edge throughput and a lower bit error rate (BER) than the CoMP-coordinated beamforming (CB) scheme, but it also has higher complexity due to data sharing. A hybrid coordinated strategy with parameter a , which indicates the proportion of users employing the CoMP-JP scheme, is proposed to apply the CoMP-JP scheme to improve the poorer communication quality of cell edge and employ the CoMP-CB scheme for other users to enhance average throughput and spectral efficiency. This paradigm selects users defined by the certain threshold of signal to interference plus noise power ratio (SINR) corresponding to the parameter α to the CoMP-JP scheme. This paper compares the BER performance between the block diagonalization (BD) based precoding and the linear precoders by maximizing signal to leakage and noise ratio (SLNR), and also indicates that the SLNR based precoding algorithm gets lower BER than the BD based precoding algorithm with certain signal-to-noise ratios (SNRs). Finally, this paper discusses that the system performance is partially affected by the percentage of CoMP-JP users and concludes that 50% of users sorted to communicate under the CoMP-JP scheme will reach the best system performance. [ABSTRACT FROM AUTHOR]

A communication and navigation receiver is required to remove hostile jamming signals and synchronize receiving signals effectively especially for satellite communication and navigation whose resources are becoming more and more limited. This paper proposes a novel signal receiving method by combining the processes of anti-jamming and synchronization to reduce the overall computational complexity at the expense of slightly affecting the detection probability, which is analyzed in detail by derivations. Furthermore, this paper introduces sparse Fourier transformation (SFT) into the proposed algorithm to replace fast Fourier transformation (FFT) so as to further reduce the calculation time especially in large frequency offset environments. [ABSTRACT FROM AUTHOR]

Radar radio frequency (RF) stealth is very important in electronic war (EW), and waveform design and selection. Existing evaluation rules of radar RF stealth include too many parameters of radar and interceptors, such as Schleher interception factor, which makes it difficult to evaluate radar RF stealth technologies if interceptor parameters are unknown. In communication, security capacity has been presented to describe the possible ability to communicate in complete security. Since the essential of the security capacity is to have the interceptor get none valued information from the emitter, this paper is proposed to study security information factors taking advantage of mutual information to evaluate radar RF stealth under some conditions. Through analyzing mutual information obtained by the radar and the interceptor, this paper defines the security information factor with and without cooperative jamming. Furthermore, this paper deduces the ratio of the match filter to the match incoherent filter and discuss mutual information received by the interceptor. Numerical simulations illustrate radar RF stealth effects based on the security information factor concept under different conditions. [ABSTRACT FROM AUTHOR]

This paper investigates the maximum network throughput for resource-constrained space networks based on the delay and disruption-tolerant networking (DTN) architecture. Specifically, this paper proposes a methodology for calculating the maximum network throughput of multiple transmission tasks under storage and delay constraints over a space network. A mixed-integer linear programming (MILP) is formulated to solve this problem. Simulations results show that the proposed methodology can successfully calculate the optimal throughput of a space network under storage and delay constraints, as well as a clear, monotonic relationship between end-to-end delay and the maximum network throughput under storage constraints. At the same time, the optimization results shine light on the routing and transport protocol design in space communication, which can be used to obtain the optimal network throughput. [ABSTRACT FROM AUTHOR]

Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines (VMs). This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches. [ABSTRACT FROM AUTHOR]

Level of repair analysis (LORA) is an important method of maintenance decision for establishing systems of operation and maintenance in the equipment development period. Currently, the research on equipment of repair level focuses on economic analysis models which are used to optimize costs and rarely considers the maintenance time required by the implementation of the maintenance program. In fact, as to the system requiring high mission complete success, the maintenance time is an important factor which has a great influence on the availability of equipment systems. Considering the relationship between the maintenance time and the spares stocks level, it is obvious that there are contradictions between the maintenance time and the cost. In order to balance these two factors, it is necessary to build an optimization LORA model. To this end, the maintenance time representing performance characteristic is introduced, and on the basis of spares stocks which is traditionally regarded as a decision variable, a decision variable of repair level is added, and a multi-echelon multi-indenture (MEMI) optimization LORA model is built which takes the best cost-effectiveness ratio as the criterion, the expected number of backorder (EBO) as the objective function and the cost as the constraint. Besides, the paper designs a convex programming algorithm of multi-variable for the optimization model, provides solutions to the non-convex objective function and methods for improving the efficiency of the algorithm. The method provided in this paper is proved to be credible and effective according to the numerical example and the simulation result. [ABSTRACT FROM AUTHOR]

Most sensors or cameras discussed in the sensor network community are usually 3D homogeneous, even though their 2D coverage areas in the ground plane are heterogeneous. Meanwhile, observed objects of camera networks are usually simplified as 2D points in previous literature. However in actual application scenes, not only cameras are always heterogeneous with different height and action radiuses, but also the observed objects are with 3D features (i.e., height). This paper presents a sensor planning formulation addressing the efficiency enhancement of visual tracking in 3D heterogeneous camera networks that track and detect people traversing a region. The problem of sensor planning consists of three issues: (i) how to model the 3D heterogeneous cameras; (ii) how to rank the visibility, which ensures that the object of interest is visible in a camera's field of view; (iii) how to reconfigure the 3D viewing orientations of the cameras. This paper studies the geometric properties of 3D heterogeneous camera networks and addresses an evaluation formulation to rank the visibility of observed objects. Then a sensor planning method is proposed to improve the efficiency of visual tracking. Finally, the numerical results show that the proposed method can improve the tracking performance of the system compared to the conventional strategies. [ABSTRACT FROM AUTHOR]

How to allocate a resource efficiently and fairly attracts the attention of both researchers and practitioners. Data envelopment analysis (DEA) has been brought to bear on its solution. The existing literature applies Gini coefficient to measure the fairness in the resource allocation process. However, the Gini coefficient is inapplicable in many applications. This paper proposes a novel centralized resource allocation model based on DEA that considers both the efficiency and the fairness. This paper adopts a notion of fairness, namely α-fairness that is well studied in welfare economics and is of practical significance. The new model integrates a-fairness with DEA to support resource allocation decisions. It aids decision makers in making a trade-off between the efficiency and the fairness. An illustrative application is used to validate the proposed approach. [ABSTRACT FROM AUTHOR]

Up to present, the problem of the evaluation of fault diagnosability for nonlinear systems has been investigated by many researchers. However, no attempt has been done to evaluate the diagnosability of multiple faults occurring simultaneously for nonlinear systems. This paper proposes a method based on differential geometry theories to solve this problem. Then the evaluation of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is achieved. To deal with the effect of control laws on the evaluation results of fault diagnosability, a design scheme of the evaluation of fault diagnosability is proposed. Then the influence of uncertainties on the evaluation results of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is analyzed. The numerical simulation results are obtained to show the effectiveness of the proposed evaluation scheme of fault diagnosability. [ABSTRACT FROM AUTHOR]

In reliability engineering, the observations of the variables of interest are always limited due to cost or schedule constraints. Consequently, the epistemic uncertainty, which derives from lack of knowledge and information, plays a vital influence on the reliability evaluation. Belief reliability is a new reliability metric that takes the impact of epistemic uncertainty into consideration and belief reliability distribution is fundamental to belief reliability application. This paper develops a new method called graduation formula to construct belief reliability distribution with limited observations. The developed method constructs the belief reliability distribution by determining the corresponding belief degrees of the observations. An algorithm is designed for the graduation formula as it is a set of transcendental equations, which is difficult to determine the analytical solution. The developed method and the proposed algorithm are illustrated by two numerical examples to show their efficiency and future application. [ABSTRACT FROM AUTHOR]

Weapon system portfolio selection is an important combinatorial problem that arises in various applications, such as weapons development planning and equipment procurement, which are of concern to military decision makers. However, the existing weapon system-of-systems (SoS) is tightly coupled. Because of the diversity and connectivity of mission requirements, it is difficult to describe the direct mapping relationship from the mission to the weapon system. In the latest service-oriented research, the introduction of service modules to build a service-oriented, flexible, and combinable structure is an important trend. This paper proposes a service-oriented weapon system portfolio selection method, by introducing service to serve as an intermediary to connect missions and system selection, and transferring the weapon system selection into the service portfolio selection. Specifically, the relation between the service and the task is described through the service-task mapping matrix; and the relation between the service and the weapon system is constructed through the servicesystem mapping matrix. The service collaboration network to calculate the flexibility and connectivity of each service portfolio is then established. Through multi-objective programming, the optimal service portfolios are generated, which are further decoded into weapon system portfolios. [ABSTRACT FROM AUTHOR]

Tolerance sensitivity limits the practical application of the cross-eye jammer. Previous literature has demonstrated that retrodirective cross-eye jamming with multiple antenna elements possesses the advantage of loose tolerance requirements compared to traditional cross-eye jamming. However, the previous analysis was limited, because there are still some factors affecting the parameter tolerance of the multiple-element retrodirective cross-eye jamming (MRCJ) system and they have not been investigated completely, such as the loop difference, the baseline ratio and the jammer-to-signal ratio. This paper performs a comprehensive tolerance analysis of the MRCJ system with a nonuniformspacing linear array. Simulation results demonstrate the tolerance effects of the above influence factors and give reasonable advice for easing tolerance sensitivity. [ABSTRACT FROM AUTHOR]

Image fusion based on the sparse representation (SR) has become the primary research direction of the transform domain method. However, the SR-based image fusion algorithm has the characteristics of high computational complexity and neglecting the local features of an image, resulting in limited image detail retention and a high registration misalignment sensitivity. In order to overcome these shortcomings and the noise existing in the image of the fusion process, this paper proposes a new signal decomposition model, namely the multi-source image fusion algorithm of the gradient regularization convolution SR (CSR). The main innovation of this work is using the sparse optimization function to perform two-scale decomposition of the source image to obtain high-frequency components and low-frequency components. The sparse coefficient is obtained by the gradient regularization CSR model, and the sparse coefficient is taken as the maximum value to get the optimal high frequency component of the fused image. The best low frequency component is obtained by using the fusion strategy of the extreme or the average value. The final fused image is obtained by adding two optimal components. Experimental results demonstrate that this method greatly improves the ability to maintain image details and reduces image registration sensitivity. [ABSTRACT FROM AUTHOR]

For the classical GM(1,1) model, the prediction accuracy is not high, and the optimization of the initial and background values is one-sided. In this paper, the Lagrange mean value theorem is used to construct the background value as a variable related to k. At the same time, the initial value is set as a variable, and the corresponding optimal parameter and the time response formula are determined according to the minimum value of mean relative error (MRE). Combined with the domestic natural gas annual consumption data, the classical model and the improved GM(1,1) model are applied to the calculation and error comparison respectively. It proves that the improved model is better than any other models. [ABSTRACT FROM AUTHOR]

This paper proposes a multivariable fixed-time leaderfollower formation control method for a group of nonholonomic mobile robots, which has the ability to estimate multiple uncertainties. Firstly, based on the state space model of the leader-follower formation, a multivariable fixed-time formation kinematics controller is designed. Secondly, to overcome uncertainties existing in the nonholonomic mobile robot system, such as load change, friction, external disturbance, a multivariable fixed-time torque controller based on the fixed-time disturbance observer at the dynamic level is designed. The designed torque controller is cascaded with the formation controller and finally realizes accurate estimation of the uncertain part of the system, the follower tracking of reference velocity and the desired formation of the leader and the follower in a fixed-time. The fixed-time upper bound is completely determined by the controller parameters, which is independent of the initial state of the system. The multivariable fixed-time control theory and the Lyapunov method are adopted to ensure the system stability. Finally, the effectiveness of the proposed algorithm is verified by the experimental simulation. [ABSTRACT FROM AUTHOR]

In this paper, a practical decoupling control scheme for fighter aircraft is proposed to achieve high angle of attack (AOA) tracking and super maneuver action by utilizing the thrust vector technology. Firstly, a six degree-of-freedom (DOF) nonlinear model with 12 variables is given. Due to low sufficiency of the aerodynamic actuators at high AOA, a thrust vector model with rotatable engine nozzles is derived. Secondly, the active disturbance rejection control (ADRC) is used to realize a three-channel decoupling control such that a strong coupling between different channels can be treated as total disturbance, which is estimated by the designed extended state observer. The control surface allocation is implemented by the traditional daisy chain method. Finally, the effectiveness of the presented control strategy is demonstrated by some numerical simulation results. [ABSTRACT FROM AUTHOR]