Pub Date : 2024-03-12DOI: 10.23919/jsee.2023.000160
Ruihan Zhang, Bing Sun
Dominant technology formation is the key for the high-tech industry to “cross the chasm” and gain an established foothold in the market (and hence disrupt the regime). Therefore, a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism. Specifically, based on complex adaptive system theory and the basic stimulus-response model, we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape. The results indicate the following: (i) The dynamic interaction is “stimulus-reaction-selection”, which promotes the dominant technology's formation. (ii) The dominant technology's formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms. (iii) The dominant technology's formation in the high-tech industry is influenced by learning ability, the number of adopting users and adaptability. Therein, a “critical scale” of learning ability exists to promote the formation of leading technology: a large number of adopting users can promote the dominant technology's formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape. There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology's formation. (iv) The socio-technical landscape can promote the leading technology's shaping in the high-tech industry, and different elements have different effects. This study promotes research on the formation mechanism of dominant technology in the high-tech industry, presents new perspectives and methods for researchers, and provides essential enlightenment for managers to formulate technology strategies.
{"title":"Complex Adaptive System Theory, Agent-Based Modeling, and Simulation in Dominant Technology Formation","authors":"Ruihan Zhang, Bing Sun","doi":"10.23919/jsee.2023.000160","DOIUrl":"https://doi.org/10.23919/jsee.2023.000160","url":null,"abstract":"Dominant technology formation is the key for the high-tech industry to “cross the chasm” and gain an established foothold in the market (and hence disrupt the regime). Therefore, a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism. Specifically, based on complex adaptive system theory and the basic stimulus-response model, we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape. The results indicate the following: (i) The dynamic interaction is “stimulus-reaction-selection”, which promotes the dominant technology's formation. (ii) The dominant technology's formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms. (iii) The dominant technology's formation in the high-tech industry is influenced by learning ability, the number of adopting users and adaptability. Therein, a “critical scale” of learning ability exists to promote the formation of leading technology: a large number of adopting users can promote the dominant technology's formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape. There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology's formation. (iv) The socio-technical landscape can promote the leading technology's shaping in the high-tech industry, and different elements have different effects. This study promotes research on the formation mechanism of dominant technology in the high-tech industry, presents new perspectives and methods for researchers, and provides essential enlightenment for managers to formulate technology strategies.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"23 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154725","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 : 2024-03-12DOI: 10.23919/jsee.2024.000025
Jing Tian, Wei Zhang
In engineering application, there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval (PRI). Therefore, if the training samples used to calculate the weight vector does not contain the jamming, then the jamming cannot be removed by adaptive spatial filtering. If the weight vector is constantly updated in the range dimension, the training data may contain target echo signals, resulting in signal cancellation effect. To cope with the situation that the training samples are contaminated by target signal, an iterative training sample selection method based on non-homogeneous detector (NHD) is proposed in this paper for updating the weight vector in entire range dimension. The principle is presented, and the validity is proven by simulation results.
{"title":"Robust Adaptive Radar Beamforming Based on Iterative Training Sample Selection Using Kurtosis of Generalized Inner Product Statistics","authors":"Jing Tian, Wei Zhang","doi":"10.23919/jsee.2024.000025","DOIUrl":"https://doi.org/10.23919/jsee.2024.000025","url":null,"abstract":"In engineering application, there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval (PRI). Therefore, if the training samples used to calculate the weight vector does not contain the jamming, then the jamming cannot be removed by adaptive spatial filtering. If the weight vector is constantly updated in the range dimension, the training data may contain target echo signals, resulting in signal cancellation effect. To cope with the situation that the training samples are contaminated by target signal, an iterative training sample selection method based on non-homogeneous detector (NHD) is proposed in this paper for updating the weight vector in entire range dimension. The principle is presented, and the validity is proven by simulation results.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"41 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154574","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 : 2024-02-12DOI: 10.23919/jsee.2023.000145
Zeqi Yang, Yiheng Liu, Hua Zhang, Shuai Ma, Kai Chang, Ning Liu, Xiaode Lyu
With the extensive application of large-scale array antennas, the increasing number of array elements leads to the increasing dimension of received signals, making it difficult to meet the real-time requirement of direction of arrival (DOA) estimation due to the computational complexity of algorithms. Traditional subspace algorithms require estimation of the covariance matrix, which has high computational complexity and is prone to producing spurious peaks. In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements, this paper proposes a DOA estimation method based on Krylov subspace and weighted $l_{1}$ -norm. The method uses the multistage Wiener filter (MSWF) iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace, further uses the measurement matrix to reduce the dimensionality of the signal subspace observation, constructs a weighted matrix, and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted $l_{1}$ -norm to solve the target DOA. Simulation results show that the proposed method has high resolution under large array conditions, effectively suppresses spurious peaks, reduces computational complexity, and has good robustness for low signal to noise ratio (SNR) environment.
随着大规模阵列天线的广泛应用，阵元数量的增加导致接收信号的维数不断增加，由于算法的计算复杂性，很难满足到达方向（DOA）估计的实时性要求。传统的子空间算法需要估计协方差矩阵，计算复杂度高，而且容易产生假峰值。为了降低 DOA 估计算法的计算复杂度，提高其在大型阵元下的估计精度，本文提出了一种基于 Krylov 子空间和加权 $l_{1}$ 准则的 DOA 估计方法。该方法利用多级维纳滤波（MSWF）迭代求解 Krylov 子空间的基础作为信号子空间的估计，进一步利用测量矩阵降低信号子空间观测的维度，构造加权矩阵，并结合稀疏重构建立基于残差平方和和加权 $l_{1}$-norm 的凸优化函数求解目标 DOA。仿真结果表明，所提方法在大阵列条件下具有较高的分辨率，能有效抑制杂散峰值，降低计算复杂度，在低信噪比（SNR）环境下具有良好的鲁棒性。
{"title":"DOA Estimation of High-Dimensional Signals Based on Krylov Subspace and Weighted $l_{1}$-Norm","authors":"Zeqi Yang, Yiheng Liu, Hua Zhang, Shuai Ma, Kai Chang, Ning Liu, Xiaode Lyu","doi":"10.23919/jsee.2023.000145","DOIUrl":"https://doi.org/10.23919/jsee.2023.000145","url":null,"abstract":"With the extensive application of large-scale array antennas, the increasing number of array elements leads to the increasing dimension of received signals, making it difficult to meet the real-time requirement of direction of arrival (DOA) estimation due to the computational complexity of algorithms. Traditional subspace algorithms require estimation of the covariance matrix, which has high computational complexity and is prone to producing spurious peaks. In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements, this paper proposes a DOA estimation method based on Krylov subspace and weighted <tex xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">$l_{1}$</tex>\u0000-norm. The method uses the multistage Wiener filter (MSWF) iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace, further uses the measurement matrix to reduce the dimensionality of the signal subspace observation, constructs a weighted matrix, and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted <tex xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">$l_{1}$</tex>\u0000-norm to solve the target DOA. Simulation results show that the proposed method has high resolution under large array conditions, effectively suppresses spurious peaks, reduces computational complexity, and has good robustness for low signal to noise ratio (SNR) environment.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"22 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547483","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}
Adaptive detection of range-spread targets is considered in the presence of subspace interference plus Gaussian clutter with unknown covariance matrix. The target signal and interference are supposed to lie in two linearly independent subspaces with deterministic but unknown coordinates. Relying on the two-step criteria, two adaptive detectors based on Gradient tests are proposed, in homogeneous and partially homogeneous clutter plus subspace interference, respectively. Both of the proposed detectors exhibit theoretically constant false alarm rate property against unknown clutter covariance matrix as well as the power level. Numerical results show that, the proposed detectors have better performance than their existing counterparts, especially for mismatches in the signal steering vectors.
{"title":"Adaptive Detection of Range-Spread Targets in Homogeneous and Partially Homogeneous Clutter Plus Subspace Interference","authors":"Tao Jian, Jia He, Bencai Wang, Yu Liu, Congan Xu, Zikeng Xie","doi":"10.23919/jsee.2023.000147","DOIUrl":"https://doi.org/10.23919/jsee.2023.000147","url":null,"abstract":"Adaptive detection of range-spread targets is considered in the presence of subspace interference plus Gaussian clutter with unknown covariance matrix. The target signal and interference are supposed to lie in two linearly independent subspaces with deterministic but unknown coordinates. Relying on the two-step criteria, two adaptive detectors based on Gradient tests are proposed, in homogeneous and partially homogeneous clutter plus subspace interference, respectively. Both of the proposed detectors exhibit theoretically constant false alarm rate property against unknown clutter covariance matrix as well as the power level. Numerical results show that, the proposed detectors have better performance than their existing counterparts, especially for mismatches in the signal steering vectors.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"80 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154707","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}
Aiming at the shortcoming that the traditional industrial manipulator using off-line programming cannot change along with the change of external environment, the key technologies such as machine vision and manipulator control are studied, and a complete manipulator vision tracking system is designed. Firstly, Denavit-Hartenberg (D-H) parameters method is used to construct the model of the manipulator and analyze the forward and inverse kinematics equations of the manipulator. At the same time, a binocular camera is used to obtain the three-dimensional position of the target. Secondly, in order to make the manipulator track the target more accurately, the fuzzy adaptive square root unscented Kalman filter (FSRUKF) is proposed to estimate the target state. Finally, the manipulator tracking system is built by using the position-based visual servo. The simulation experiments show that FSRUKF converges faster and with less error than the square root unscented Kalman filter (SRUKF), which meets the application requirements of the manipulator tracking system, and basically meets the application requirements of the manipulator tracking system in the practical experiments.
{"title":"Manipulator Tracking Technology Based on FSRUKF","authors":"Guoqing Shi, Boyan Zhang, Jiandong Zhang, Qiming Yang, Xiaofeng Huang, Jianyao Que, Junwei Pu, Xiutang Geng","doi":"10.23919/jsee.2024.000009","DOIUrl":"https://doi.org/10.23919/jsee.2024.000009","url":null,"abstract":"Aiming at the shortcoming that the traditional industrial manipulator using off-line programming cannot change along with the change of external environment, the key technologies such as machine vision and manipulator control are studied, and a complete manipulator vision tracking system is designed. Firstly, Denavit-Hartenberg (D-H) parameters method is used to construct the model of the manipulator and analyze the forward and inverse kinematics equations of the manipulator. At the same time, a binocular camera is used to obtain the three-dimensional position of the target. Secondly, in order to make the manipulator track the target more accurately, the fuzzy adaptive square root unscented Kalman filter (FSRUKF) is proposed to estimate the target state. Finally, the manipulator tracking system is built by using the position-based visual servo. The simulation experiments show that FSRUKF converges faster and with less error than the square root unscented Kalman filter (SRUKF), which meets the application requirements of the manipulator tracking system, and basically meets the application requirements of the manipulator tracking system in the practical experiments.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"30 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141060269","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 : 2024-01-24DOI: 10.23919/jsee.2023.000116
Chen Chen, Wei Quan, Zhuang Shao
Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit (SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform (FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features. Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.
空中威胁评估是现代空战中的关键环节，其结果对指挥官的决策具有重要意义。考虑到现有威胁评估方法难以处理高维时间序列目标数据，本文提出了一种基于自注意机制和门控循环单元（SAGRU）的威胁评估方法。首先，建立了包括空战态势和能力特征在内的威胁特征系统。此外，还应用了基于分数傅里叶变换（FRFT）的数据增强过程，以从时间序列态势特征中提取更多有价值的信息。此外，为了捕捉战场演变的关键特征，还设计了双向 GRU 和 SA 机制来增强特征。随后，在对处理后的空战态势和能力特征进行串联后，将通过全连接神经层和 softmax 分类器预测目标威胁水平。最后，为了验证该模型，引入了由作战模拟系统生成的空战数据集进行模型训练和测试。对比实验表明，所提出的模型具有结构合理性，能比其他现有的基于深度学习的模型更快、更准确地完成威胁评估。
{"title":"Aerial Target Threat Assessment Based on Gated Recurrent Unit and Self-Attention Mechanism","authors":"Chen Chen, Wei Quan, Zhuang Shao","doi":"10.23919/jsee.2023.000116","DOIUrl":"https://doi.org/10.23919/jsee.2023.000116","url":null,"abstract":"Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit (SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform (FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features. Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"4 5 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141060272","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 : 2024-01-24DOI: 10.23919/jsee.2024.000011
Shaojie Mao, Lianwang Diao, Yu Sun, Heng Wang, Kan Yi, Xin Xu, Xiaobin Mao, Kecheng Zhang, Long Sheng
The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence, surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing, decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.
{"title":"A Framework of Force of Information Influence and Application for C4KISR System","authors":"Shaojie Mao, Lianwang Diao, Yu Sun, Heng Wang, Kan Yi, Xin Xu, Xiaobin Mao, Kecheng Zhang, Long Sheng","doi":"10.23919/jsee.2024.000011","DOIUrl":"https://doi.org/10.23919/jsee.2024.000011","url":null,"abstract":"The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence, surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing, decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"808 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141060303","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}
To address the shortcomings of single-step decision making in the existing deep reinforcement learning based unmanned aerial vehicle (UAV) real-time path planning problem, a real-time UAV path planning algorithm based on long short-term memory (RPP-LSTM) network is proposed, which combines the memory characteristics of recurrent neural network (RNN) and the deep reinforcement learning algorithm. LSTM networks are used in this algorithm as Q-value networks for the deep Q network (DQN) algorithm, which makes the decision of the Q-value network has some memory. Thanks to LSTM network, the Q-value network can use the previous environmental information and action information which effectively avoids the problem of single-step decision considering only the current environment. Besides, the algorithm proposes a hierarchical reward and punishment function for the specific problem of UAV real-time path planning, so that the UAV can more reasonably perform path planning. Simulation verification shows that compared with the traditional feed-forward neural network (FNN) based UAV autonomous path planning algorithm, the RPP-LSTM proposed in this paper can adapt to more complex environments and has significantly improved robustness and accuracy when performing UAV real-time path planning.
{"title":"Real-Time UAV Path Planning Based on LSTM Network","authors":"Jiandong Zhang, Yukun Guo, Lihui Zheng, Qiming Yang, Guoqing Shi, Yong Wu","doi":"10.23919/jsee.2023.000157","DOIUrl":"https://doi.org/10.23919/jsee.2023.000157","url":null,"abstract":"To address the shortcomings of single-step decision making in the existing deep reinforcement learning based unmanned aerial vehicle (UAV) real-time path planning problem, a real-time UAV path planning algorithm based on long short-term memory (RPP-LSTM) network is proposed, which combines the memory characteristics of recurrent neural network (RNN) and the deep reinforcement learning algorithm. LSTM networks are used in this algorithm as Q-value networks for the deep Q network (DQN) algorithm, which makes the decision of the Q-value network has some memory. Thanks to LSTM network, the Q-value network can use the previous environmental information and action information which effectively avoids the problem of single-step decision considering only the current environment. Besides, the algorithm proposes a hierarchical reward and punishment function for the specific problem of UAV real-time path planning, so that the UAV can more reasonably perform path planning. Simulation verification shows that compared with the traditional feed-forward neural network (FNN) based UAV autonomous path planning algorithm, the RPP-LSTM proposed in this paper can adapt to more complex environments and has significantly improved robustness and accuracy when performing UAV real-time path planning.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"18 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141060305","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 : 2024-01-24DOI: 10.23919/jsee.2023.000148
Shichao Chen, Feng Luo, Min Tian, Wanghan Lyu
In this paper, a detection method combining Cameron decomposition based on polarization scattering characteristics in sea clutter background is proposed. Firstly, the Cameron decomposition is exploited to fuse the radar echoes of full polarization channels at the data level. Due to the artificial material structure on the surface of the target, it can be shown that the non-reciprocity of the target cell is stronger than that of the clutter cell. Then, based on the analysis of the decomposition results, a new feature with scattering geometry characteristics in polarization domain, denoted as Cameron polarization decomposition scattering weight (CPD-SW), is extracted as the test statistic, which can achieve more detailed descriptions of the clutter scattering characteristics utilizing the difference between their scattering types. Finally, the superiority of the proposed CPD-SW detector over traditional detectors in improving detection performance is verified by the IPIX measured dataset, which has strong stability under short-time observation in threshold detection and can also improve the separability of feature space zin anomaly detection.
本文提出了一种基于海杂波背景下极化散射特性的卡梅隆分解探测方法。首先，利用卡梅隆分解在数据层面对全极化信道的雷达回波进行融合。由于目标表面的人工材料结构，可以证明目标单元的非互易性强于杂波单元。然后，在分析分解结果的基础上，提取具有极化域散射几何特征的新特征，即卡梅伦极化分解散射权重（CPD-SW）作为测试统计量，利用其散射类型的差异实现对杂波散射特征更详细的描述。最后，通过 IPIX 测量数据集验证了 CPD-SW 检测器在提高检测性能方面优于传统检测器，在阈值检测中具有较强的短时观测稳定性，还能提高异常检测中特征空间 z 的可分离性。
{"title":"Short-Time Maritime Target Detection Based on Polarization Scattering Characteristics","authors":"Shichao Chen, Feng Luo, Min Tian, Wanghan Lyu","doi":"10.23919/jsee.2023.000148","DOIUrl":"https://doi.org/10.23919/jsee.2023.000148","url":null,"abstract":"In this paper, a detection method combining Cameron decomposition based on polarization scattering characteristics in sea clutter background is proposed. Firstly, the Cameron decomposition is exploited to fuse the radar echoes of full polarization channels at the data level. Due to the artificial material structure on the surface of the target, it can be shown that the non-reciprocity of the target cell is stronger than that of the clutter cell. Then, based on the analysis of the decomposition results, a new feature with scattering geometry characteristics in polarization domain, denoted as Cameron polarization decomposition scattering weight (CPD-SW), is extracted as the test statistic, which can achieve more detailed descriptions of the clutter scattering characteristics utilizing the difference between their scattering types. Finally, the superiority of the proposed CPD-SW detector over traditional detectors in improving detection performance is verified by the IPIX measured dataset, which has strong stability under short-time observation in threshold detection and can also improve the separability of feature space zin anomaly detection.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"22 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154704","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 : 2024-01-24DOI: 10.23919/jsee.2023.000133
Shuwen Xu, Yifan Hao, Zhuo Wang, Jian Xue
This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and non-Gaussian sea clutter. The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters, and the target is modeled as a subspace range-spread target model. The persymmetric structure is used to model the clutter covariance matrix, in order to reduce the reliance on secondary data of the designed detectors. Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test (GLRT), Rao test, and Wald test. All the proposed detectors have constant false-alarm rate property with respect to the clutter texture, the speckle covariance matrix. Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments, and the proposed GLRT detector has the best detection performance under different parameters.
{"title":"Persymmetric Adaptive Polarimetric Detection of Subspace Range-Spread Targets in Compound Gaussian Sea Clutter","authors":"Shuwen Xu, Yifan Hao, Zhuo Wang, Jian Xue","doi":"10.23919/jsee.2023.000133","DOIUrl":"https://doi.org/10.23919/jsee.2023.000133","url":null,"abstract":"This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and non-Gaussian sea clutter. The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters, and the target is modeled as a subspace range-spread target model. The persymmetric structure is used to model the clutter covariance matrix, in order to reduce the reliance on secondary data of the designed detectors. Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test (GLRT), Rao test, and Wald test. All the proposed detectors have constant false-alarm rate property with respect to the clutter texture, the speckle covariance matrix. Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments, and the proposed GLRT detector has the best detection performance under different parameters.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"41 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154663","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}
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