The capture probability of interceptors has been deeply studied. Firstly, the definition of capture probability is analyzed. It is transformed into calculating the probability that the relative position vector between the target and the interceptor locates in a certain cone. The relative position vector and associated covariance matrix are projected in line-of-sight coordinates, and the 3-dimensional integral of a probability function in a cone is calculated to obtain the capture probability. The integral equation is a complicated expression of probability, and it is simplified to an explicit approximate expression according to some assumptions based on the characteristics of the engineering problems. The approximation precision is analyzed by comparative simulation difference, which indicates that approximate assumptions are reasonable. Utilizing the explicit xpression, the characteristics of capture probability are analyzed respectively with the factors, such as the distance between the interceptor and the target, the precision of relative position vector, the maximum capture distance and the maximum field angle of interceptor seeker.
According to the characteristic of cruise missiles, navigation point setting is simplified, and the principle of route planning for saturation attack and a concept of reference route are put forward. With the help of the shortest-tangent idea in route-planning and the algorithm of back reasoning from targets, a reference route algorithm is built on the shortest range and threat avoidance. Then a route-flight-time algorithm is built on navigation points. Based on the conditions of multi-direction saturation attack, a route planning algorithm of multi-direction saturation attack is built on reference route, route-flight-time, and impact azimuth. Simulation results show that the algorithm can realize missiles fired in a salvo launch reaching the target simultaneously from different directions while avoiding threat.
An ant colony optimization (ACO)-simulated annealing (SA)-based algorithm is developed for the target assignment problem (TAP) in the air defense (AD) command and control (C2) system of surface to air missile (SAM) tactical unit. The accomplishment process of target assignment (TA) task is analyzed. A firing advantage degree (FAD) concept of fire unit (FU) intercepting targets is put forward and its evaluation model is established by using a linear weighted synthetic method. A TA optimization model is presented and its solving algorithms are designed respectively based on ACO and SA. A hybrid optimization strategy is presented and developed synthesizing the merits of ACO and SA. The simulation examples show that the model and algorithms can meet the solving requirement of TAP in AD combat.
According to the characteristic and the requirement of multipath planning, a new multipath planning method is proposed based on network. This method includes two steps: the construction of network and multipath searching. The construction of network proceeds in three phases: the skeleton extraction of the configuration space, the judgment of the cross points in the skeleton and how to link the cross points to form a network. Multipath searching makes use of the network and iterative penalty method (IPM) to plan multi-paths, and adjusts the planar paths to satisfy the requirement of maneuverability of unmanned aerial vehicle (UAV). In addition, a new height planning method is proposed to deal with the height planning of 3D route. The proposed algorithm can find multiple paths automatically according to distribution of terrain and threat areas with high efficiency. The height planning can make 3D route following the terrain. The simulation experiment illustrates the feasibility of the proposed method.
A new method that stabilizes network-based systems with both bounded delay and packet disordering is discussed under the state feedback controller. A novel model, fully describing the dynamic characteristic of network-based systems with packet disordering, is constructed. Different from the existing models of network-based systems, the number of delay items is time-varying in the model proposed. Further, this model is converted into a parameter-uncertain discrete-time system with time-varying delay item numbers in terms of matrix theory. Moreover, the less conservative stability condition is obtained by avoiding utilisation of Moon et al.’ inequality and bounding inequalities for quadratic functional terms. By solving a minization problem based on linear matrix inequalities, the state feedback controller is presented. A numerical example is given to illustrate the effectiveness of the proposed method.
The command and control (C2) is a decision-making process based on human cognition, which contains operational, physical, and human characteristics, so it takes on uncertainty and complexity. As a decision support approach, Bayesian networks (BNs) provide a framework in which a decision is made by combining the experts’ knowledge and the specific data. In addition, an expert system represented by human cognitive framework is adopted to express the real-time decision-making process of the decision maker. The combination of the Bayesian decision support and human cognitive framework in the C2 of a specific application field is modeled and executed by colored Petri nets (CPNs), and the consequences of execution manifest such combination can perfectly present the decision-making process in C2.
Unmanned aerial vehicle (UAV) resource scheduling means to allocate and aggregate the available UAV resources depending on the mission requirements and the battlefield situation assessment. In previous studies, the models cannot reflect the mission synchronization; the targets are treated respectively, which results in the large scale of the problem and high computational complexity. To overcome these disadvantages, a model for UAV resource scheduling under mission synchronization is proposed, which is based on single-objective non-linear integer programming. And several cooperative teams are aggregated for the target clusters from the available resources. The evaluation indices of weapon allocation are referenced in establishing the objective function and the constraints for the issue. The scales of the target clusters are considered as the constraints for the scales of the cooperative teams to make them match in scale. The functions of the intersection between the “mission time-window” and the UAV “arrival time-window” are introduced into the objective function and the constraints in order to describe the mission synchronization effectively. The results demonstrate that the proposed expanded model can meet the requirement of mission synchronization, guide the aggregation of cooperative teams for the target clusters and control the scale of the problem effectively.
This paper considers the problem of applying data mining techniques to aeronautical field. The truncation method, which is one of the techniques in the aeronautical data mining, can be used to efficiently handle the air-combat behavior data. The technique of air-combat behavior data mining based on the truncation method is proposed to discover the air-combat rules or patterns. The simulation platform of the air-combat behavior data mining that supports two fighters is implemented. The simulation experimental results show that the proposed air-combat behavior data mining technique based on the truncation method is feasible whether in efficiency or in effectiveness.
The coordinated Bayesian optimization algorithm (CBOA) is proposed according to the characteristics of the function independence, conformity and supplementary between the electronic countermeasure (ECM) and the firepower attack systems. The selection criteria are combinations of probabilities of individual fitness and coordinated degree and can select choiceness individual to construct Bayesian network that manifest population evolution by producing the new chromosome. Thus the CBOA cannot only guarantee the effective pattern coordinated decision-making mechanism between the populations, but also maintain the population multiplicity, and enhance the algorithm performance. The simulation result confirms the algorithm validity.
An extended compromise ratio method (CRM) based on fuzzy distances is developed to solve fuzzy multi-attribute group decision making problems in which weights of attributes and ratings of alternatives on attributes are expressed with values of linguistic variables parameterized using triangular fuzzy numbers. A compromise solution is determined by introducing the ranking index based on the concept that the chosen alternative should be as close as possible to the positive ideal solution and as far away from the negative ideal solution as possible simultaneously. This proposed method is compared with other existing methods to show its feasibility and effectiveness and illustrated with an example of the military route selection problem as one of the possible applications.
Ultrafast optoelectronic technology has been widely used in terahertz time domain spectrum, terahertz imaging technology, terahertz communication and so on, and great progress has been achieved in the past two decade. Recently, this innovative technology has been applied in radio metrology and supplied a potential and hopeful method to solve the existent challenges of calibration devices and equipments with bandwidth up to 100 GHz. This paper generally summarizes the emerging applications of the ultrafast optoelectronic technology in radio metrology. The main applications of this technology in calibrating broadband sampling oscilloscopes, the high-speed photodiodes and calibrating the electrical pulse generators are emphasized, and the testing of monolithic microwave integrated circuits is also presented.
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.
As to oppositional, multi-objective and hierarchical characteristic of air formation to ground attack-defends campaign, and using dynamic space state model of military campaign, this article establishes a principal and subordinate hierarchical interactive decision-making way, the Nash-Stackelberg-Nash model, to solve the problems in military operation, and find out the associated best strategy in hierarchical dynamic decision-making. The simulating result indicate that when applying the model to air formation to ground attack-defends decision-making system, it can solve the problems of two hierarchies' dynamic oppositional decision-making favorably, and reach preferable effect in battle. It proves that the model can provide an effective way for analyzing a battle.
Abundant test data are required in assessment of weapon performance. When weapon test data are insufficient, Bayesian analyses in small sample circumstance should be considered and the test data should be provided by simulations. The several Bayesian approaches are discussed and some limitations are founded. An improvement is put forward after limitations of Bayesian approaches available are analyzed and the improved approach is applied to assessment of some new weapon performance.
A multi-stage influence diagram is used to model the pilot's sequential decision making in one on one air combat. The model based on the multi-stage influence diagram graphically describes the elements of decision process, and contains a point-mass model for the dynamics of an aircraft and takes into account the decision maker's preferences under uncertain conditions. Considering an active opponent, the opponent's maneuvers can be modeled stochastically. The solution of multistage influence diagram can be obtained by converting the multistage influence diagram into a two-level optimization problem. The simulation results show the model is effective.
For several superior controllers of the first-order integrating processes with long delay, the windup problems are analyzed in detail when the control signal saturates. The results show that these controllers have similar characteristics about the process input limitation. And then, a simple and effective anti-windup scheme, without an additional parameter, is designed for these controllers. Simulations run with three main controllers, and the results illustrate that the proposed method may achieve good performance under the nominal and model uncertainty cases.
The exponential stability is investigated for a class of continuous time linear systems with a finite state Markov chain form process and the impulsive jump at switching moments. The conditions, based on the average dwell time and the ratio of expectation of the total time running on all unstable subsystems to the expectation of the total time running on all stable subsystems, assure the exponential stability with a desired stability degree of the system irrespective of the impact of impulsive jump. The uniformly bounded result is realized for the case in which switched system is subjected to the impulsive effect of the excitation signal at some switching moments.
NCW(network centric warfare) is an information warfare concentrating on network. A global network-centric warfare architecture with OGSA grid technology is put forward, which is a four levels system including the user level, the application level, the grid middleware layer and the resource level. In grid middleware layer,based on virtual hosting environment, a BEPL4WS grid service composition method is introduced. In addition, the NCW grid service model is built with the help of Eclipse-SDK-3.0.1 and Bpws4j.
WTA (weapon-target allocation) of air defense operation is a very complicated problem and current models focus on static and restricted WTA problem mostly. Based on the dynamic characteristics of air defense operational command and decision of warships' formation, a dynamic WTA model is established. Simulation results show that switch fire and repetition fire of anti-air weapon systems affect the result of the air defense operation remarkably and the dynamic model is more satisfying than static ones. Related results are gained based on the analysis of the simulation results and the results are accordant with the intuitionistic tactical judgment. The model is some reference for the research of air defense C?I system of warships' formation.
