Assessment and sequencing of air target threat based on intuitionistic fuzzy entropy and dynamic VIKOR

In view of the fact that traditional air target threat assessment methods are difficult to reflect the combat characteristics of uncertain, dynamic and hybrid formation, an algorithm is proposed to solve the multi-target threat assessment problems. The target attribute weight is calculated by the intuitionistic fuzzy entropy(IFE) algorithm and the time series weight is gained by the Poisson distribution method based on multi-times data. Finally,assessment and sequencing of the air multi-target threat model based on IFE and dynamic Vlse Kriterijumska Optimizacija I Kompromisno Resenje(VIKOR) is established with an example which indicates that the method is reasonable and effective.

Deep reinforcement learning and its application in autonomous fitting optimization for attack areas of UCAVs

The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies while increasing the tactical capabilities of combat aircraft. As a research object, common UCAV uses the neural network fitting strategy to obtain values of attack areas. However, this simple strategy cannot cope with complex environmental changes and autonomously optimize decision-making problems. To solve the problem, this paper proposes a new deep deterministic policy gradient(DDPG) strategy based on deep reinforcement learning for the attack area fitting of UCAVs in the future battlefield. Simulation results show that the autonomy and environmental adaptability of UCAVs in the future battlefield will be improved based on the new DDPG algorithm and the training process converges quickly. We can obtain the optimal values of attack areas in real time during the whole flight with the well-trained deep network.

Modeling and Algorithm Application of Weapon Assignment System

In order to improve weapon assignment(WA)accuracy in real scenario,an artificial neural network(ANN)model is built to calculate real-time weapon kill probabilities.Considering the WA characteristic,each input representing one assessment index should be normalized properly.Therefore,the modified WA model is oriented from constant value to dynamic computation.Then an improved invasive weed optimization algorithm is applied to solve the WA problem.During search process,local search is used to improve the initial population,and seed reproduction is redefined to guarantee the mutation from multipoint to single point.In addition,the idea of vaccination and immune selection in biology is added into optimization process.Finally,simulation results verify the model′s rationality and effectiveness of the proposed algorithm.

Winning Probability Estimation Based on Improved Bradley-Terry Model and Bayesian Network for Aircraft Carrier Battle

To provide a decision-making aid for aircraft carrier battle,the winning probability estimation based on Bradley-Terry model and Bayesian network is presented. Firstly,the armed forces units of aircraft carrier are classified into three types,which are aircraft,ship and submarine. Then,the attack ability value and defense ability value for each type of armed forces are estimated by using BP neural network,whose training results of sample data are consistent with the estimation results. Next,compared the assessment values through an improved Bradley-Terry model and constructed a Bayesian network to do the global assessment,the winning probabilities of both combat sides are obtained. Finally,the winning probability estimation for a navy battle is given to illustrate the validity of the proposed scheme.

An Effective Method of Threshold Selection for Small Object Image

The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.

Partition region-based suppressed fuzzy C-means algorithm

Aimed at the problem that the traditional suppressed fuzzy C-means clustering algorithms ignore the real needs of different objects, applying the same suppressed parameter for modifying membership degrees of all the objects, a novel partition region-based suppressed fuzzy C-means clustering algorithm with better capacity of adaptability and robustness is proposed in this paper. The model based on the real needs of different objects is built, making it clear to decide whether to proceed with further determination; in addition, the external user-defined suppressed parameter is automatically selected according to the intrinsic structural characteristic of each dataset, making the proposed method become robust to the fluctuations in the incoming dataset and initial conditions. Experimental results show that the proposed method is more robust than its counterparts and overcomes the weakness of the original suppressed clustering algorithm in most cases.

Motion Control of Capsule-like Underwater Robot Utilizing the Swing Properties of Ionic Polymer Metal Composite Actuators

Ionic Polymer Metal Composite(IPMC)is a novel electrically actuated intelligent material with the advantages of big bending displacement,low driving voltage,flexible and so on.It has been recognized as one of the most attractive actuators with prospective applications for underwater robots and bionic organs.In this work,a capsule-like robot was introduced with the pectoral and caudal fins made of IPMC.By analyzing the properties of displacement response to square waves with different frequencies and low level voltages,it was found that performance of IPMC are frequency sensitive.Besides,when the absolute value of low level voltage decreases,IPMC could swing on one side with the decrease in amplitudes,whereas the amplitude at high level voltage fluctuates within small ranges at low frequencies.IPMC tip can approximately maintain when the frequency of driving signal around 30 Hz.Such properties were employed to control the locomotion of robot combining the motions of pectoral and caudal fin.Thus,the locomotions of swimming forward,turning and positioning were realized.

Dynamic attack zone of air-to-air missile after being launched in random wind field

A new concept is presented for air-to-air missile which is dynamic attack zone after being launched in random wind field. This new concept can be used to obtain the 4-dimensional （4-D） information regarding the dynamic envelope of an air-to-air missile at any flight time airned at different flight targets considering influences of random wind, in the situation of flight fighters coop- crated with missiles fighting against each other. Based on an air-to-air missile model, some typical cases of dynamic attack zone after being launched in random wind field were numerically simulated. Compared with the simulation results of traditional dynamic envelope, the properties of dynamic attack zone after being launched are as follows. The 4-D dynamic attack zone after being launched is inside traditional maximum dynamic envelope, but its forane boundary is usually not inside traditional no-escape dynamic envelope; Traditional dynamic attack zone can just be reliably used at launch time, while dynamic envelope after being launched can be reliably and accurately used during any flight antagonism time. Traditional envelope is a special case of dynamic envelope after being launched when the dynamic envelope is calculated at the launch time： the dynamic envelope after being launched can be inflt, enced by the random wind field.

Two-dimensional launch window method to search for launch opportunities of interplanetary missions

Accurate and highly efficient approaches to obtain mission opportunities are still the goals of mission planners of interplanetary explorations.The search for launch opportunities not only determines the specified launch window of the mission but also presents the performance requirements for the interplanetary probe and its launch vehicle.An effective method, namely the two-dimensional launch window method, is developed from a completely new perspective to determine all the launch opportunities of the mission in this research.For a fixed launch time,the method to determine all the time windows in the dimension of Time-of-Flight(TOF) is firstly proposed and these time windows represent all the launch opportunities for the given launch time.And then, the two-dimensional launch window method is proposed, which computes the time windows in both the launch time and TOF dimensions to achieve all launch opportunities of the mission.Numerical examples are provided to demonstrate the accuracy and high efficiency of the method.Compared with the widely-used pock-chop plot method, the proposed method reduces the computational time by two orders of magnitude for the same search precision, and thus is especially suitable for the cases involving rapid, high-precision, and/or large-scale searches for mission opportunities.