Pub Date : 2023-10-01DOI: 10.23919/JSEE.2023.000132
Cal Tianyi;Dan Bo;Huang Weibo
The angular resolution of radar is of crucial significance to its tracking performance. In this paper, a super-resolution parameter estimation algorithm based on wide-narrowband joint processing is proposed to improve the angular resolution of wideband monopulse radar. The range cells containing resolvable scattering points are detected in the wideband mode, and these range cells are adopted to estimate part of the target parameters by algorithms of low computational requirement. Then, the likelihood function of the echo is constructed in the narrow-band mode to estimate the rest of the parameters, and the parameters estimated in the wideband mode are employed to reduce computation and enhance estimation accuracy. Simulation results demonstrate that the proposed algorithm has higher estimation accuracy and lower computational complexity than the current algorithm and can avoid the risk of model mismatch.
{"title":"Super-resolution parameter estimation of monopulse radar by wide-narrowband joint processing","authors":"Cal Tianyi;Dan Bo;Huang Weibo","doi":"10.23919/JSEE.2023.000132","DOIUrl":"https://doi.org/10.23919/JSEE.2023.000132","url":null,"abstract":"The angular resolution of radar is of crucial significance to its tracking performance. In this paper, a super-resolution parameter estimation algorithm based on wide-narrowband joint processing is proposed to improve the angular resolution of wideband monopulse radar. The range cells containing resolvable scattering points are detected in the wideband mode, and these range cells are adopted to estimate part of the target parameters by algorithms of low computational requirement. Then, the likelihood function of the echo is constructed in the narrow-band mode to estimate the rest of the parameters, and the parameters estimated in the wideband mode are employed to reduce computation and enhance estimation accuracy. Simulation results demonstrate that the proposed algorithm has higher estimation accuracy and lower computational complexity than the current algorithm and can avoid the risk of model mismatch.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 5","pages":"1158-1170"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.23919/JSEE.2023.000079
Yao Dongdong;Wang Xiaofang;Lin Hai;Wang Zhuping
To ensure safe flight of multiple fixed-wing unmanned aerial vehicles (UAVs) formation, considering trajectory planning and formation control together, a leader trajectory planning method based on the sparse A* algorithm is introduced. Firstly, a formation controller based on prescribed performance theory is designed to control the transient and steady formation configuration, as well as the formation forming time, which not only can form the designated formation configuration but also can guarantee collision avoidance and terrain avoidance theoretically. Next, considering the constraints caused by formation controller on trajectory planning such as the safe distance, turn angle and step length, as well as the constraint of formation shape, a leader trajectory planning method based on sparse A* algorithm is proposed. Simulation results show that the UAV formation can arrive at the destination safely with a short trajectory no matter keeping the formation or encountering formation transformation.
{"title":"Leader trajectory planning method considering constraints of formation controller","authors":"Yao Dongdong;Wang Xiaofang;Lin Hai;Wang Zhuping","doi":"10.23919/JSEE.2023.000079","DOIUrl":"https://doi.org/10.23919/JSEE.2023.000079","url":null,"abstract":"To ensure safe flight of multiple fixed-wing unmanned aerial vehicles (UAVs) formation, considering trajectory planning and formation control together, a leader trajectory planning method based on the sparse A* algorithm is introduced. Firstly, a formation controller based on prescribed performance theory is designed to control the transient and steady formation configuration, as well as the formation forming time, which not only can form the designated formation configuration but also can guarantee collision avoidance and terrain avoidance theoretically. Next, considering the constraints caused by formation controller on trajectory planning such as the safe distance, turn angle and step length, as well as the constraint of formation shape, a leader trajectory planning method based on sparse A* algorithm is proposed. Simulation results show that the UAV formation can arrive at the destination safely with a short trajectory no matter keeping the formation or encountering formation transformation.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 5","pages":"1294-1308"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The performance of a strapdown inertial navigation system (SINS) largely depends on the accuracy and rapidness of the initial alignment. A novel anti-interference self-alignment algorithm by attitude optimization estimation for SINS on a rocking base is presented in this paper. The algorithm transforms the initial alignment into the initial attitude determination problem by using infinite vector observations to remove the angular motions, the SINS alignment is heuristically established as an optimization problem of finding the minimum eigenvector. In order to further improve the alignment precision, an adaptive recursive weighted least squares (ARWLS) curve fitting algorithm is used to fit the translational motion interference-contaminated reference vectors according to their time domain characteristics. Simulation studies and experimental results favorably demonstrate its rapidness, accuracy and robustness.
{"title":"Anti-interference self-alignment algorithm by attitude optimization estimation for SINS on a rocking base","authors":"Xue Haijian;Wang Tao;Cai Xinghu;Wang Jintao;Liu Fei","doi":"10.23919/JSEE.2023.000112","DOIUrl":"https://doi.org/10.23919/JSEE.2023.000112","url":null,"abstract":"The performance of a strapdown inertial navigation system (SINS) largely depends on the accuracy and rapidness of the initial alignment. A novel anti-interference self-alignment algorithm by attitude optimization estimation for SINS on a rocking base is presented in this paper. The algorithm transforms the initial alignment into the initial attitude determination problem by using infinite vector observations to remove the angular motions, the SINS alignment is heuristically established as an optimization problem of finding the minimum eigenvector. In order to further improve the alignment precision, an adaptive recursive weighted least squares (ARWLS) curve fitting algorithm is used to fit the translational motion interference-contaminated reference vectors according to their time domain characteristics. Simulation studies and experimental results favorably demonstrate its rapidness, accuracy and robustness.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 5","pages":"1333-1342"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.23919/JSEE.2023.000128
Zhang Yaozhong;Wu Zhuoran;Xiong Zhenkai;Chen Long
The deep deterministic policy gradient (DDPG) algorithm is an off-policy method that combines two mainstream reinforcement learning methods based on value iteration and policy iteration. Using the DDPG algorithm, agents can explore and summarize the environment to achieve autonomous decisions in the continuous state space and action space. In this paper, a cooperative defense with DDPG via swarms of unmanned aerial vehicle (UAV) is developed and validated, which has shown promising practical value in the effect of defending. We solve the sparse rewards problem of reinforcement learning pair in a long-term task by building the reward function of UAV swarms and optimizing the learning process of artificial neural network based on the DDPG algorithm to reduce the vibration in the learning process. The experimental results show that the DDPG algorithm can guide the UAVs swarm to perform the defense task efficiently, meeting the requirements of a UAV swarm for non-centralization, autonomy, and promoting the intelligent development of UAVs swarm as well as the decision-making process.
{"title":"A UAV collaborative defense scheme driven by DDPG algorithm","authors":"Zhang Yaozhong;Wu Zhuoran;Xiong Zhenkai;Chen Long","doi":"10.23919/JSEE.2023.000128","DOIUrl":"https://doi.org/10.23919/JSEE.2023.000128","url":null,"abstract":"The deep deterministic policy gradient (DDPG) algorithm is an off-policy method that combines two mainstream reinforcement learning methods based on value iteration and policy iteration. Using the DDPG algorithm, agents can explore and summarize the environment to achieve autonomous decisions in the continuous state space and action space. In this paper, a cooperative defense with DDPG via swarms of unmanned aerial vehicle (UAV) is developed and validated, which has shown promising practical value in the effect of defending. We solve the sparse rewards problem of reinforcement learning pair in a long-term task by building the reward function of UAV swarms and optimizing the learning process of artificial neural network based on the DDPG algorithm to reduce the vibration in the learning process. The experimental results show that the DDPG algorithm can guide the UAVs swarm to perform the defense task efficiently, meeting the requirements of a UAV swarm for non-centralization, autonomy, and promoting the intelligent development of UAVs swarm as well as the decision-making process.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 5","pages":"1211-1224"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.23919/JSEE.2023.000119
Hu Lei;Yi Guoxing;Nan Yi;Wang Hao
Aiming at the suppression of enemy air defense (SEAD) task under the complex and complicated combat scenario, the spatiotemporal cooperative path planning methods are studied in this paper. The major research contents include optimal 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 terminal attack angle constraint and maneuverability constraint into consideration, the Dubins curve is introduced to smooth the path segments. In cooperative rendezvous part, we take estimated 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, maneuver 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 realized, in this way, the combat situation suppression against the enemy can be realized in SEAD scenarios.
{"title":"Combat situation suppression of multiple UAVs based on spatiotemporal cooperative path planning","authors":"Hu Lei;Yi Guoxing;Nan Yi;Wang Hao","doi":"10.23919/JSEE.2023.000119","DOIUrl":"https://doi.org/10.23919/JSEE.2023.000119","url":null,"abstract":"Aiming at the suppression of enemy air defense (SEAD) task under the complex and complicated combat scenario, the spatiotemporal cooperative path planning methods are studied in this paper. The major research contents include optimal 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 terminal attack angle constraint and maneuverability constraint into consideration, the Dubins curve is introduced to smooth the path segments. In cooperative rendezvous part, we take estimated 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, maneuver 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 realized, in this way, the combat situation suppression against the enemy can be realized in SEAD scenarios.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 5","pages":"1191-1210"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For the underwater long baseline (LBL) positioning systems, the traditional distance intersection algorithm simplifies the sound speed to a constant, and calculates the underwater target position parameters with a nonlinear iteration. However, due to the complex underwater environment, the sound speed changes with time and space, and then the acoustic propagation path is actually a curve, which inevitably causes some errors to the traditional distance intersection positioning algorithm. To reduce the position error caused by the uncertain underwater sound speed, a new time of arrival (TOA) intersection underwater positioning algorithm of LBL system is proposed. Firstly, combined with the vertical layered model of the underwater sound speed, an implicit positioning model of TOA intersection is constructed through the constant gradient acoustic ray tracing. And then an optimization function based on the overall TOA residual square sum is advanced to solve the position parameters for the underwater target. Moreover, the parti-cle swarm optimization (PSO) algorithm is replaced with the traditional nonlinear least square method to optimize the implicit positioning model of TOA intersection. Compared with the traditional distance intersection positioning model, the TOA intersection positioning model is more suitable for the engineering practice and the optimization algorithm is more effective. Simulation results show that the proposed methods in this paper can effectively improve the positioning accuracy for the underwater target.
{"title":"TOA positioning algorithm of LBL system for underwater target based on PSO","authors":"Xing Yao;He Zhangming;Wang Jiongqi;Zhou Xuanying;Chen Yuyun;Pan Xiaogang","doi":"10.23919/JSEE.2023.000107","DOIUrl":"https://doi.org/10.23919/JSEE.2023.000107","url":null,"abstract":"For the underwater long baseline (LBL) positioning systems, the traditional distance intersection algorithm simplifies the sound speed to a constant, and calculates the underwater target position parameters with a nonlinear iteration. However, due to the complex underwater environment, the sound speed changes with time and space, and then the acoustic propagation path is actually a curve, which inevitably causes some errors to the traditional distance intersection positioning algorithm. To reduce the position error caused by the uncertain underwater sound speed, a new time of arrival (TOA) intersection underwater positioning algorithm of LBL system is proposed. Firstly, combined with the vertical layered model of the underwater sound speed, an implicit positioning model of TOA intersection is constructed through the constant gradient acoustic ray tracing. And then an optimization function based on the overall TOA residual square sum is advanced to solve the position parameters for the underwater target. Moreover, the parti-cle swarm optimization (PSO) algorithm is replaced with the traditional nonlinear least square method to optimize the implicit positioning model of TOA intersection. Compared with the traditional distance intersection positioning model, the TOA intersection positioning model is more suitable for the engineering practice and the optimization algorithm is more effective. Simulation results show that the proposed methods in this paper can effectively improve the positioning accuracy for the underwater target.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 5","pages":"1319-1332"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.23919/JSEE.2023.000142
Yu Chaopeng;Xiong Wei;Li Xiaoqing;Dong Lei
Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters, the accuracy and confidence of meteorology target detection are reduced. In this paper, a deep convolutional neural network (DCNN) is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input. For each weather radar image, the corresponding digital elevation model (DEM) image is extracted on basis of the radar antenna scanning parameters and plane position, and is further fed to the network as a supplement for ground clutter suppression. The features of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process. Then the network parameters are updated by the back propagation iteration of the training error. Experimental results on the real measured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors. Meanwhile, the network outputs are in good agreement with the expected meteorology detection results (labels). It is demonstrated that the proposed network would have a promising meteorology observation application with minimal effort on network variables or parameter changes.
{"title":"Deep convolutional neural network for meteorology target detection in airborne weather radar images","authors":"Yu Chaopeng;Xiong Wei;Li Xiaoqing;Dong Lei","doi":"10.23919/JSEE.2023.000142","DOIUrl":"https://doi.org/10.23919/JSEE.2023.000142","url":null,"abstract":"Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters, the accuracy and confidence of meteorology target detection are reduced. In this paper, a deep convolutional neural network (DCNN) is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input. For each weather radar image, the corresponding digital elevation model (DEM) image is extracted on basis of the radar antenna scanning parameters and plane position, and is further fed to the network as a supplement for ground clutter suppression. The features of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process. Then the network parameters are updated by the back propagation iteration of the training error. Experimental results on the real measured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors. Meanwhile, the network outputs are in good agreement with the expected meteorology detection results (labels). It is demonstrated that the proposed network would have a promising meteorology observation application with minimal effort on network variables or parameter changes.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 5","pages":"1147-1157"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.23919/JSEE.2023.000091
Ronghua Du;Wenhe Liao;Xiang Zhang
This paper proposes an optimal maneuver strategy to improve the observability of angles-only rendezvous from the perspective of relative navigation. A set of dimensionless relative orbital elements (ROEs) is used to parameterize the relative motion, and the objective function of the observability of angles-only navigation is established. An analytical solution of the optimal maneuver strategy to improve the observability of angles-only navigation is obtained by means of numerical analysis. A set of dedicated semi-physical simulation system is built to test the performances of the proposed optimal maneuver strategy. Finally, the effectiveness of the method proposed in this paper is verified through the comparative analysis of the objective function of the observability of angles-only navigation and the performances of the angles-only navigation filter under different maneuver schemes. Compared with the cases without orbital maneuver, it is concluded that the tangential filtering accuracy with the optimal orbital maneuver at the terminal time is increased by 35% on average, and the radial and normal filtering accuracy is increased by 30% on average.
{"title":"Optimal Maneuver Strategy to Improve the Observability of Angles-Only Rendezvous","authors":"Ronghua Du;Wenhe Liao;Xiang Zhang","doi":"10.23919/JSEE.2023.000091","DOIUrl":"10.23919/JSEE.2023.000091","url":null,"abstract":"This paper proposes an optimal maneuver strategy to improve the observability of angles-only rendezvous from the perspective of relative navigation. A set of dimensionless relative orbital elements (ROEs) is used to parameterize the relative motion, and the objective function of the observability of angles-only navigation is established. An analytical solution of the optimal maneuver strategy to improve the observability of angles-only navigation is obtained by means of numerical analysis. A set of dedicated semi-physical simulation system is built to test the performances of the proposed optimal maneuver strategy. Finally, the effectiveness of the method proposed in this paper is verified through the comparative analysis of the objective function of the observability of angles-only navigation and the performances of the angles-only navigation filter under different maneuver schemes. Compared with the cases without orbital maneuver, it is concluded that the tangential filtering accuracy with the optimal orbital maneuver at the terminal time is increased by 35% on average, and the radial and normal filtering accuracy is increased by 30% on average.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 4","pages":"1020-1032"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/5971804/10241333/10241317.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45424339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.23919/JSEE.2023.000102
Yang Zhao;Jicheng Liu;Ju Jiang;Ziyang Zhen
The dynamic weapon target assignment (DWTA) problem is of great significance in modern air combat. However, DWTA is a highly complex constrained multi-objective combinatorial optimization problem. An improved elitist non-dominated sorting genetic algorithm-II (NSGA-II) called the non-dominated shuffled frog leaping algorithm (NSFLA) is proposed to maximize damage to enemy targets and minimize the self-threat in air combat constraints. In NSFLA, the shuffled frog leaping algorithm (SFLA) is introduced to NSGA-II to replace the inside evolutionary scheme of the genetic algorithm (GA), displaying low optimization speed and heterogeneous space search defects. Two improvements have also been raised to promote the internal optimization performance of SFLA. Firstly, the local evolution scheme, a novel crossover mechanism, ensures that each individual participates in updating instead of only the worst ones, which can expand the diversity of the population. Secondly, a discrete adaptive mutation algorithm based on the function change rate is applied to balance the global and local search. Finally, the scheme is verified in various air combat scenarios. The results show that the proposed NSFLA has apparent advantages in solution quality and efficiency, especially in many aircraft and the dynamic air combat environment.
{"title":"Shuffled Frog Leaping Algorithm with Non-Dominated Sorting for Dynamic Weapon-Target Assignment","authors":"Yang Zhao;Jicheng Liu;Ju Jiang;Ziyang Zhen","doi":"10.23919/JSEE.2023.000102","DOIUrl":"10.23919/JSEE.2023.000102","url":null,"abstract":"The dynamic weapon target assignment (DWTA) problem is of great significance in modern air combat. However, DWTA is a highly complex constrained multi-objective combinatorial optimization problem. An improved elitist non-dominated sorting genetic algorithm-II (NSGA-II) called the non-dominated shuffled frog leaping algorithm (NSFLA) is proposed to maximize damage to enemy targets and minimize the self-threat in air combat constraints. In NSFLA, the shuffled frog leaping algorithm (SFLA) is introduced to NSGA-II to replace the inside evolutionary scheme of the genetic algorithm (GA), displaying low optimization speed and heterogeneous space search defects. Two improvements have also been raised to promote the internal optimization performance of SFLA. Firstly, the local evolution scheme, a novel crossover mechanism, ensures that each individual participates in updating instead of only the worst ones, which can expand the diversity of the population. Secondly, a discrete adaptive mutation algorithm based on the function change rate is applied to balance the global and local search. Finally, the scheme is verified in various air combat scenarios. The results show that the proposed NSFLA has apparent advantages in solution quality and efficiency, especially in many aircraft and the dynamic air combat environment.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 4","pages":"1007-1019"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/5971804/10241333/10241316.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47253211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.23919/JSEE.2023.000108
Ying Chen;Tianyu Yang;Yanfang Wang
Degradation and overstress failures occur in many electronic systems in which the operation load and environmental conditions are complex. The dependency of them called dependent competing failure process (DCFP), has been widely studied. Electronic system may experience mutual effects of degradation and shocks, they are considered to be interdependent. Both the degradation and the shock processes will decrease the limit of system and cause cumulative effect. Finally, the competition of hard and soft failure will cause the system failure. Based on the failure mechanism accumulation theory, this paper constructs the shock-degradation acceleration and the threshold descent model, and a system reliability model established by using these two models. The mutually DCFP effect of electronic system interaction has been decomposed into physical correlation of failure, including acceleration, accumulation and competition. As a case, a reliability of electronic system in aeronautical system has been analyzed with the proposed method. The method proposed is based on failure physical evaluation, and could provide important reference for quantitative evaluation and design improvement of the newly designed system in case of data deficiency.
{"title":"Reliability Modeling of Mutual DCFP Considering Failure Physical Dependency","authors":"Ying Chen;Tianyu Yang;Yanfang Wang","doi":"10.23919/JSEE.2023.000108","DOIUrl":"10.23919/JSEE.2023.000108","url":null,"abstract":"Degradation and overstress failures occur in many electronic systems in which the operation load and environmental conditions are complex. The dependency of them called dependent competing failure process (DCFP), has been widely studied. Electronic system may experience mutual effects of degradation and shocks, they are considered to be interdependent. Both the degradation and the shock processes will decrease the limit of system and cause cumulative effect. Finally, the competition of hard and soft failure will cause the system failure. Based on the failure mechanism accumulation theory, this paper constructs the shock-degradation acceleration and the threshold descent model, and a system reliability model established by using these two models. The mutually DCFP effect of electronic system interaction has been decomposed into physical correlation of failure, including acceleration, accumulation and competition. As a case, a reliability of electronic system in aeronautical system has been analyzed with the proposed method. The method proposed is based on failure physical evaluation, and could provide important reference for quantitative evaluation and design improvement of the newly designed system in case of data deficiency.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 4","pages":"1063-1073"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/5971804/10241333/10241321.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49632544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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