A situation maintenance-based cooperative guidance strategy is proposed to intercept a high-speed and high-maneuverability target via inferior missiles.Reachability and relative motion analyses are conducted to develo...A situation maintenance-based cooperative guidance strategy is proposed to intercept a high-speed and high-maneuverability target via inferior missiles.Reachability and relative motion analyses are conducted to develop and pursue virtual targets,respectively.A two-stage guidance strategy under nonlinear kinematics is developed on the basis of virtual targets.The first stage optimizes the coverage and collision situation by pursuing virtual targets under specific angular constraints.The second stage subsequently intercepts the superior target based on the handover condition optimized by the first stage.Numerical simulation results are provided to compare the effectiveness and superiority of the proposed strategy with those of the reachability-based cooperative strategy(RCS),coverage-based cooperative guidance(CBCG)and augmented proportional navigation(APN)under various maneuvering modes.展开更多
Political skill is a critical interpersonal competency.However,the self-reported political skill scale is unsuitable for personnel selection beacuse it may lead to socially desirable responses,thereby compromising the...Political skill is a critical interpersonal competency.However,the self-reported political skill scale is unsuitable for personnel selection beacuse it may lead to socially desirable responses,thereby compromising the authenticity of the test scores.Consequently,the absence of a valid assessment method limits the application of political skill in selection con-texts.In this study,we applied the situational judgment test(SJT)method to measure political skill and conducted two sub-studies to evaluate the reliability and validity of the situational judgment test of political skill(SJT-PS).Study 1 focused on the development and initial testing of the SJT-PS.The results demonstrated that the SJT-PS possessed strong structural validity and reliability.Study 2 aimed to assess the criterion-related and incremental validity of the SJT-PS.To evaluate the predictive validity of the SJT-PS in selection contexts,we first compared the correlations between the SJT-PS and self-reported political skill with social desirability.Subsequently,we selected team-member exchange(TMX)and workplace popularity as criteria.The results indicated that the SJT-PS was less affected by social desirability,while self-reported political skill exhibited a significant positive correlation with social desirability.Additionally,the SJT-PS positively pre-dicted TMX and workplace popularity and demonstrated incremental validity over the self-reported political skill scale.展开更多
This paper gives an analysis of the dynamic characteristics of situation elements(SEs) in situation awareness(SA)research. The purpose of the discussion is to understand the factors that influence SA and to help in de...This paper gives an analysis of the dynamic characteristics of situation elements(SEs) in situation awareness(SA)research. The purpose of the discussion is to understand the factors that influence SA and to help in designing the training systems to improve operators’ SA. The status function of SEs is defined and the derivative of the function represents trends of the status of SEs at each moment. Then, Fourier transform(FT) is used to give the frequency-domain function in terms of the time-domain status function. In frequency domain, the bandwidth of the status function is used as a criterion to characterize the notion of "fast" and"slow" of the change of SE’s status, which represents the dynamic characteristic of SEs. The criterion constitutes the first analytical measurement of the dynamic characteristic of SEs, which is one of the important factors that influence the SA process.展开更多
A method is proposed to resolve the typical problem of air combat situation assessment. Taking the one-to-one air combat as an example and on the basis of air combat data recorded by the air combat maneuvering instrum...A method is proposed to resolve the typical problem of air combat situation assessment. Taking the one-to-one air combat as an example and on the basis of air combat data recorded by the air combat maneuvering instrument, the problem of air combat situation assessment is equivalent to the situation classification problem of air combat data. The fuzzy C-means clustering algorithm is proposed to cluster the selected air combat sample data and the situation classification of the data is determined by the data correlation analysis in combination with the clustering results and the pilots＇ description of the air combat process. On the basis of semi-supervised naive Bayes classifier, an improved algorithm is proposed based on data classification confidence, through which the situation classification of air combat data is carried out. The simulation results show that the improved algorithm can assess the air combat situation effectively and the improvement of the algorithm can promote the classification performance without significantly affecting the efficiency of the classifier.展开更多
Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the per...Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the performance of space surveillance,is the top-level design in SSA missions reviewed.The recognized real programs about SBO SAA proposed by the institutions in the U.S.,Canada,Europe,etc.,are summarized firstly,from which an insight of the development trend of SBO SAA can be obtained.According to the aim of the SBO SSA,the missions can be divided into general surveillance and space object tracking.Thus,there are two major categories for SBO SSA strategies.Existing general surveillance strategies for observing low earth orbit(LEO)objects and beyond-LEO objects are summarized and compared in terms of coverage rate,revisit time,visibility period,and image processing.Then,the SBO space object tracking strategies,which has experienced from tracking an object with a single satellite to tracking an object with multiple satellites cooperatively,are also summarized.Finally,this paper looks into the development trend in the future and points out several problems that challenges the SBO SSA.展开更多
The status of an operator’s situation awareness is one of the critical factors that influence the quality of the missions.Thus the measurement method of the situation awareness status is an important topic to researc...The status of an operator’s situation awareness is one of the critical factors that influence the quality of the missions.Thus the measurement method of the situation awareness status is an important topic to research.So far,there are lots of methods designed for the measurement of situation awareness status,but there is no model that can measure it accurately in real-time,so this work is conducted to deal with such a gap.Firstly,collect the relevant physiological data of operators while they are performing a specific mission,simultaneously,measure their status of situation awareness by using the situation awareness global assessment technique(SAGAT),which is known for accuracy but cannot be used in real-time.And then,after the preprocessing of the raw data,use the physiological data as features,the SAGAT’s results as a label to train a fuzzy cognitive map(FCM),which is an explainable and powerful intelligent model.Also,a hybrid learning algorithm of particle swarm optimization(PSO)and gradient descent is proposed for the FCM training.The final results show that the learned FCM can assess the status of situation awareness accurately in real-time,and the proposed hybrid learning algorithm has better efficiency and accuracy.展开更多
Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents in...Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents include opti-mal path points generation,path smoothing and cooperative rendezvous.In the path points generation part,the path points availability testing algorithm and the path segments availability testing algorithm are designed,on this foundation,the swarm intelligence-based path point generation algorithm is utilized to generate the optimal path.In the path smoothing part,taking ter-minal attack angle constraint and maneuverability constraint into consideration,the Dubins curve is introduced to smooth the path segments.In cooperative rendezvous part,we take esti-mated time of arrival requirement constraint and flight speed range constraint into consideration,the speed control strategy and flight path control strategy are introduced,further,the decoupling scheme of the circling maneuver and detouring maneuver is designed,in this case,the maneuver ways,maneu-ver point,maneuver times,maneuver path and flight speed are determined.Finally,the simulation experiments are conducted and the acquired results reveal that the time-space cooperation of multiple unmanned aeriel vehicles(UAVs)is effectively real-ized,in this way,the combat situation suppression against the enemy can be realized in SEAD scenarios.展开更多
In order to improve the performance of UAV's autonomous maneuvering decision-making,this paper proposes a decision-making method based on situational continuity.The algorithm in this paper designs a situation eval...In order to improve the performance of UAV's autonomous maneuvering decision-making,this paper proposes a decision-making method based on situational continuity.The algorithm in this paper designs a situation evaluation function with strong guidance,then trains the Long Short-Term Memory(LSTM)under the framework of Deep Q Network(DQN)for air combat maneuvering decision-making.Considering the continuity between adjacent situations,the method takes multiple consecutive situations as one input of the neural network.To reflect the difference between adjacent situations,the method takes the difference of situation evaluation value as the reward of reinforcement learning.In different scenarios,the algorithm proposed in this paper is compared with the algorithm based on the Fully Neural Network(FNN)and the algorithm based on statistical principles respectively.The results show that,compared with the FNN algorithm,the algorithm proposed in this paper is more accurate and forwardlooking.Compared with the algorithm based on the statistical principles,the decision-making of the algorithm proposed in this paper is more efficient and its real-time performance is better.展开更多
The mass organizing power is a distinctive feature of the Communist Party of China,an important criterion to test the nature of the proletarian party,and an essential condition to transform the Party’s organizational...The mass organizing power is a distinctive feature of the Communist Party of China,an important criterion to test the nature of the proletarian party,and an essential condition to transform the Party’s organizational advantages into strength superiority.In order to improve the mass organizing power,on the basis of giving full play to the traditional advantages,we’re required to carry out the mass line,and from the perspective of political construction,highlight political functions,strengthening work practices and organization system,taking advantage of technologies,promoting capacity,and intensifying the sense of responsibility,thus to provide a steady stream of power for the great rejuvenation of the Chinese nation.展开更多
The anomaly detection of electromagnetic environment situation(EMES) has essential reference value for electromagnetic equipment behavior cognition and battlefield threat assessment.In this paper,we proposed a deep le...The anomaly detection of electromagnetic environment situation(EMES) has essential reference value for electromagnetic equipment behavior cognition and battlefield threat assessment.In this paper,we proposed a deep learning-based method for detecting anomalies in EMES to address the problem of relatively low efficiency of electromagnetic environment situation anomaly detection(EMES-AD).Firstly,the convolutional kernel extracts the static features of different regions of the EMES.Secondly,the dynamic features of the region are obtained by using a recurrent neural network(LSTM).Thirdly,the Spatio-temporal features of the region are recovered by using a de-convolutional network and then fused to predict the EMES.The structural similarity algorithm(SSIM) is used to determine whether it is anomalous.We developed the detection framework,de-signed the network parameters,simulated the data sets containing different anomalous types of EMES,and carried out the detection experiments.The experimental results show that the proposed method is effective.展开更多
The unmanned combat aerial vehicle(UCAV)is a research hot issue in the world,and the situation assessment is an important part of it.To overcome shortcomings of the existing situation assessment methods,such as low ac...The unmanned combat aerial vehicle(UCAV)is a research hot issue in the world,and the situation assessment is an important part of it.To overcome shortcomings of the existing situation assessment methods,such as low accuracy and strong dependence on prior knowledge,a datadriven situation assessment method is proposed.The clustering and classification are combined,the former is used to mine situational knowledge,and the latter is used to realize rapid assessment.Angle evaluation factor and distance evaluation factor are proposed to transform multi-dimensional air combat information into two-dimensional features.A convolution success-history based adaptive differential evolution with linear population size reduc-tion-means(C-LSHADE-Means)algorithm is proposed.The convolutional pooling layer is used to compress the size of data and preserve the distribution characteristics.The LSHADE algorithm is used to initialize the center of the mean clustering,which over-comes the defect of initialization sensitivity.Comparing experi-ment with the seven clustering algorithms is done on the UCI data set,through four clustering indexes,and it proves that the method proposed in this paper has better clustering performance.A situation assessment model based on stacked autoen-coder and learning vector quantization(SAE-LVQ)network is constructed,and it uses SAE to reconstruct air combat data fea-tures,and uses the self-competition layer of the LVQ to achieve efficient classification.Compared with the five kinds of assess-ments models,the SAE-LVQ model has the highest accuracy.Finally,three kinds of confrontation processes from air combat maneuvering instrumentation(ACMI)are selected,and the model in this paper is used for situation assessment.The assessment results are in line with the actual situation.展开更多
With the rapid development of digital and intelligent information systems, display of radar situation interface has become an important challenge in the field of human-computer interaction. We propose a method for the...With the rapid development of digital and intelligent information systems, display of radar situation interface has become an important challenge in the field of human-computer interaction. We propose a method for the optimization of radar situation interface from error-cognition through the mapping of information characteristics. A mapping method of matrix description is adopted to analyze the association properties between error-cognition sets and design information sets. Based on the mapping relationship between the domain of error-cognition and the domain of design information, a cross-correlational analysis is carried out between error-cognition and design information.We obtain the relationship matrix between the error-cognition of correlation between design information and the degree of importance among design information. Taking the task interface of a warfare navigation display as an example, error factors and the features of design information are extracted. Based on the results, we also propose an optimization design scheme for the radar situation interface.展开更多
Ⅰ. The present Situation of Transnational Corporations’ Investment in TEDA (1 ) General situation Since its founding ten years ago, especially since 1992. TEDA has achieved encouraging successesin undertaking major ...Ⅰ. The present Situation of Transnational Corporations’ Investment in TEDA (1 ) General situation Since its founding ten years ago, especially since 1992. TEDA has achieved encouraging successesin undertaking major projects. drawing the attention of leading consortia, omnibearingly solicitingbusiness and drawing foreign capital. By September 30, 1994, TEDA had approved 2054 solely for-展开更多
To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov pr...To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov process, so that the air combat situation can be effectively calculated via Bayesian inference theory. According to the situation assessment result,adaptively adjusts the weights of maneuver decision factors, which makes the objective function more reasonable and ensures the superiority situation for UCAV. As the air combat game is characterized by highly dynamic and a significant amount of uncertainty,to enhance the robustness and effectiveness of maneuver decision results, fuzzy logic is used to build the functions of four maneuver decision factors. Accuracy prediction of opponent aircraft is also essential to ensure making a good decision; therefore, a prediction model of opponent aircraft is designed based on the elementary maneuver method. Finally, the moving horizon optimization strategy is used to effectively model the whole air combat maneuver decision process. Various simulations are performed on typical scenario test and close-in dogfight, the results sufficiently demonstrate the superiority of the designed maneuver decision method.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.62203362)the Natural Science Basic Research Program of Shaanxi(Grant No.2023-JC-QN-0569)。
文摘A situation maintenance-based cooperative guidance strategy is proposed to intercept a high-speed and high-maneuverability target via inferior missiles.Reachability and relative motion analyses are conducted to develop and pursue virtual targets,respectively.A two-stage guidance strategy under nonlinear kinematics is developed on the basis of virtual targets.The first stage optimizes the coverage and collision situation by pursuing virtual targets under specific angular constraints.The second stage subsequently intercepts the superior target based on the handover condition optimized by the first stage.Numerical simulation results are provided to compare the effectiveness and superiority of the proposed strategy with those of the reachability-based cooperative strategy(RCS),coverage-based cooperative guidance(CBCG)and augmented proportional navigation(APN)under various maneuvering modes.
基金supported by the National Nature Science Foundation of China(7191001010)。
文摘Political skill is a critical interpersonal competency.However,the self-reported political skill scale is unsuitable for personnel selection beacuse it may lead to socially desirable responses,thereby compromising the authenticity of the test scores.Consequently,the absence of a valid assessment method limits the application of political skill in selection con-texts.In this study,we applied the situational judgment test(SJT)method to measure political skill and conducted two sub-studies to evaluate the reliability and validity of the situational judgment test of political skill(SJT-PS).Study 1 focused on the development and initial testing of the SJT-PS.The results demonstrated that the SJT-PS possessed strong structural validity and reliability.Study 2 aimed to assess the criterion-related and incremental validity of the SJT-PS.To evaluate the predictive validity of the SJT-PS in selection contexts,we first compared the correlations between the SJT-PS and self-reported political skill with social desirability.Subsequently,we selected team-member exchange(TMX)and workplace popularity as criteria.The results indicated that the SJT-PS was less affected by social desirability,while self-reported political skill exhibited a significant positive correlation with social desirability.Additionally,the SJT-PS positively pre-dicted TMX and workplace popularity and demonstrated incremental validity over the self-reported political skill scale.
基金supported by the National Natural Science Foundation of China(61174198)the PLA Military Graduate Students Foundation(2011JY002-163)
文摘This paper gives an analysis of the dynamic characteristics of situation elements(SEs) in situation awareness(SA)research. The purpose of the discussion is to understand the factors that influence SA and to help in designing the training systems to improve operators’ SA. The status function of SEs is defined and the derivative of the function represents trends of the status of SEs at each moment. Then, Fourier transform(FT) is used to give the frequency-domain function in terms of the time-domain status function. In frequency domain, the bandwidth of the status function is used as a criterion to characterize the notion of "fast" and"slow" of the change of SE’s status, which represents the dynamic characteristic of SEs. The criterion constitutes the first analytical measurement of the dynamic characteristic of SEs, which is one of the important factors that influence the SA process.
基金supported by the Aviation Science Foundation of China(20152096019)
文摘A method is proposed to resolve the typical problem of air combat situation assessment. Taking the one-to-one air combat as an example and on the basis of air combat data recorded by the air combat maneuvering instrument, the problem of air combat situation assessment is equivalent to the situation classification problem of air combat data. The fuzzy C-means clustering algorithm is proposed to cluster the selected air combat sample data and the situation classification of the data is determined by the data correlation analysis in combination with the clustering results and the pilots＇ description of the air combat process. On the basis of semi-supervised naive Bayes classifier, an improved algorithm is proposed based on data classification confidence, through which the situation classification of air combat data is carried out. The simulation results show that the improved algorithm can assess the air combat situation effectively and the improvement of the algorithm can promote the classification performance without significantly affecting the efficiency of the classifier.
基金This work was supported by the National Natural Science Foundation of China(61690210,61690213).
文摘Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the performance of space surveillance,is the top-level design in SSA missions reviewed.The recognized real programs about SBO SAA proposed by the institutions in the U.S.,Canada,Europe,etc.,are summarized firstly,from which an insight of the development trend of SBO SAA can be obtained.According to the aim of the SBO SSA,the missions can be divided into general surveillance and space object tracking.Thus,there are two major categories for SBO SSA strategies.Existing general surveillance strategies for observing low earth orbit(LEO)objects and beyond-LEO objects are summarized and compared in terms of coverage rate,revisit time,visibility period,and image processing.Then,the SBO space object tracking strategies,which has experienced from tracking an object with a single satellite to tracking an object with multiple satellites cooperatively,are also summarized.Finally,this paper looks into the development trend in the future and points out several problems that challenges the SBO SSA.
基金supported by the National Natural Science Foundation of China(61305133)the Aeronautical Science Foundation of China grant number 2020Z023053002.
文摘The status of an operator’s situation awareness is one of the critical factors that influence the quality of the missions.Thus the measurement method of the situation awareness status is an important topic to research.So far,there are lots of methods designed for the measurement of situation awareness status,but there is no model that can measure it accurately in real-time,so this work is conducted to deal with such a gap.Firstly,collect the relevant physiological data of operators while they are performing a specific mission,simultaneously,measure their status of situation awareness by using the situation awareness global assessment technique(SAGAT),which is known for accuracy but cannot be used in real-time.And then,after the preprocessing of the raw data,use the physiological data as features,the SAGAT’s results as a label to train a fuzzy cognitive map(FCM),which is an explainable and powerful intelligent model.Also,a hybrid learning algorithm of particle swarm optimization(PSO)and gradient descent is proposed for the FCM training.The final results show that the learned FCM can assess the status of situation awareness accurately in real-time,and the proposed hybrid learning algorithm has better efficiency and accuracy.
文摘Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents include opti-mal path points generation,path smoothing and cooperative rendezvous.In the path points generation part,the path points availability testing algorithm and the path segments availability testing algorithm are designed,on this foundation,the swarm intelligence-based path point generation algorithm is utilized to generate the optimal path.In the path smoothing part,taking ter-minal attack angle constraint and maneuverability constraint into consideration,the Dubins curve is introduced to smooth the path segments.In cooperative rendezvous part,we take esti-mated time of arrival requirement constraint and flight speed range constraint into consideration,the speed control strategy and flight path control strategy are introduced,further,the decoupling scheme of the circling maneuver and detouring maneuver is designed,in this case,the maneuver ways,maneu-ver point,maneuver times,maneuver path and flight speed are determined.Finally,the simulation experiments are conducted and the acquired results reveal that the time-space cooperation of multiple unmanned aeriel vehicles(UAVs)is effectively real-ized,in this way,the combat situation suppression against the enemy can be realized in SEAD scenarios.
基金supported by the Natural Science Basic Research Program of Shaanxi(Program No.2022JQ-593)。
文摘In order to improve the performance of UAV's autonomous maneuvering decision-making,this paper proposes a decision-making method based on situational continuity.The algorithm in this paper designs a situation evaluation function with strong guidance,then trains the Long Short-Term Memory(LSTM)under the framework of Deep Q Network(DQN)for air combat maneuvering decision-making.Considering the continuity between adjacent situations,the method takes multiple consecutive situations as one input of the neural network.To reflect the difference between adjacent situations,the method takes the difference of situation evaluation value as the reward of reinforcement learning.In different scenarios,the algorithm proposed in this paper is compared with the algorithm based on the Fully Neural Network(FNN)and the algorithm based on statistical principles respectively.The results show that,compared with the FNN algorithm,the algorithm proposed in this paper is more accurate and forwardlooking.Compared with the algorithm based on the statistical principles,the decision-making of the algorithm proposed in this paper is more efficient and its real-time performance is better.
基金The research is supported by the foundation of National Social Science Planning Fund Project“Research on General Secretary Xi Jinping’s Thought of Ideals and Beliefs for Youth”(18BKS016).
文摘The mass organizing power is a distinctive feature of the Communist Party of China,an important criterion to test the nature of the proletarian party,and an essential condition to transform the Party’s organizational advantages into strength superiority.In order to improve the mass organizing power,on the basis of giving full play to the traditional advantages,we’re required to carry out the mass line,and from the perspective of political construction,highlight political functions,strengthening work practices and organization system,taking advantage of technologies,promoting capacity,and intensifying the sense of responsibility,thus to provide a steady stream of power for the great rejuvenation of the Chinese nation.
基金funded by the National Natural Science Foundation of China, grant number 11975307the National Defense Science and Technology Innovation Special Zone Project, grant number 19-H863-01-ZT-003-003-12。
文摘The anomaly detection of electromagnetic environment situation(EMES) has essential reference value for electromagnetic equipment behavior cognition and battlefield threat assessment.In this paper,we proposed a deep learning-based method for detecting anomalies in EMES to address the problem of relatively low efficiency of electromagnetic environment situation anomaly detection(EMES-AD).Firstly,the convolutional kernel extracts the static features of different regions of the EMES.Secondly,the dynamic features of the region are obtained by using a recurrent neural network(LSTM).Thirdly,the Spatio-temporal features of the region are recovered by using a de-convolutional network and then fused to predict the EMES.The structural similarity algorithm(SSIM) is used to determine whether it is anomalous.We developed the detection framework,de-signed the network parameters,simulated the data sets containing different anomalous types of EMES,and carried out the detection experiments.The experimental results show that the proposed method is effective.
基金supported by the Natural Science Foundation of Shaanxi Province(2020JQ-481,2021JM-224)the Aeronautical Science Foundation of China(201951096002).
文摘The unmanned combat aerial vehicle(UCAV)is a research hot issue in the world,and the situation assessment is an important part of it.To overcome shortcomings of the existing situation assessment methods,such as low accuracy and strong dependence on prior knowledge,a datadriven situation assessment method is proposed.The clustering and classification are combined,the former is used to mine situational knowledge,and the latter is used to realize rapid assessment.Angle evaluation factor and distance evaluation factor are proposed to transform multi-dimensional air combat information into two-dimensional features.A convolution success-history based adaptive differential evolution with linear population size reduc-tion-means(C-LSHADE-Means)algorithm is proposed.The convolutional pooling layer is used to compress the size of data and preserve the distribution characteristics.The LSHADE algorithm is used to initialize the center of the mean clustering,which over-comes the defect of initialization sensitivity.Comparing experi-ment with the seven clustering algorithms is done on the UCI data set,through four clustering indexes,and it proves that the method proposed in this paper has better clustering performance.A situation assessment model based on stacked autoen-coder and learning vector quantization(SAE-LVQ)network is constructed,and it uses SAE to reconstruct air combat data fea-tures,and uses the self-competition layer of the LVQ to achieve efficient classification.Compared with the five kinds of assess-ments models,the SAE-LVQ model has the highest accuracy.Finally,three kinds of confrontation processes from air combat maneuvering instrumentation(ACMI)are selected,and the model in this paper is used for situation assessment.The assessment results are in line with the actual situation.
基金supported by Jiangsu Province Nature Science Foundation of China (BK20221490)the Key Fundamental Research Funds for the Central Universities (30920041114)+2 种基金the National Natural Science Foundation of China (52175469,71601068)the Key Research and Development (Social Development) Project of Jiangsu Province(BE2019647)Jiangsu Province Social Science Foundation of China (20YSB013)。
文摘With the rapid development of digital and intelligent information systems, display of radar situation interface has become an important challenge in the field of human-computer interaction. We propose a method for the optimization of radar situation interface from error-cognition through the mapping of information characteristics. A mapping method of matrix description is adopted to analyze the association properties between error-cognition sets and design information sets. Based on the mapping relationship between the domain of error-cognition and the domain of design information, a cross-correlational analysis is carried out between error-cognition and design information.We obtain the relationship matrix between the error-cognition of correlation between design information and the degree of importance among design information. Taking the task interface of a warfare navigation display as an example, error factors and the features of design information are extracted. Based on the results, we also propose an optimization design scheme for the radar situation interface.
文摘Ⅰ. The present Situation of Transnational Corporations’ Investment in TEDA (1 ) General situation Since its founding ten years ago, especially since 1992. TEDA has achieved encouraging successesin undertaking major projects. drawing the attention of leading consortia, omnibearingly solicitingbusiness and drawing foreign capital. By September 30, 1994, TEDA had approved 2054 solely for-
基金supported by the National Natural Science Foundation of China(61601505)the Aeronautical Science Foundation of China(20155196022)the Shaanxi Natural Science Foundation of China(2016JQ6050)
文摘To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov process, so that the air combat situation can be effectively calculated via Bayesian inference theory. According to the situation assessment result,adaptively adjusts the weights of maneuver decision factors, which makes the objective function more reasonable and ensures the superiority situation for UCAV. As the air combat game is characterized by highly dynamic and a significant amount of uncertainty,to enhance the robustness and effectiveness of maneuver decision results, fuzzy logic is used to build the functions of four maneuver decision factors. Accuracy prediction of opponent aircraft is also essential to ensure making a good decision; therefore, a prediction model of opponent aircraft is designed based on the elementary maneuver method. Finally, the moving horizon optimization strategy is used to effectively model the whole air combat maneuver decision process. Various simulations are performed on typical scenario test and close-in dogfight, the results sufficiently demonstrate the superiority of the designed maneuver decision method.
