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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]