Aiming at the problem that a single correlation filter model is sensitive to complex scenes such as background interference and occlusion,a tracking algorithm based on multi-time-space perception and instance-specific...Aiming at the problem that a single correlation filter model is sensitive to complex scenes such as background interference and occlusion,a tracking algorithm based on multi-time-space perception and instance-specific proposals is proposed to optimize the mathematical model of the correlation filter(CF).Firstly,according to the consistency of the changes between the object frames and the filter frames,the mask matrix is introduced into the objective function of the filter,so as to extract the spatio-temporal information of the object with background awareness.Secondly,the object function of multi-feature fusion is constructed for the object location,which is optimized by the Lagrange method and solved by closed iteration.In the process of filter optimization,the constraints term of time-space perception is designed to enhance the learning ability of the CF to optimize the final track-ing results.Finally,when the tracking results fluctuate,the boundary suppres-sion factor is introduced into the instance-specific proposals to reduce the risk of model drift effectively.The accuracy and success rate of the proposed algorithm are verified by simulation analysis on two popular benchmarks,the object tracking benchmark 2015(OTB2015)and the temple color 128(TC-128).Extensive experimental results illustrate that the optimized appearance model of the proposed algorithm is effective.The distance precision rate and overlap success rate of the proposed algorithm are 0.756 and 0.656 on the OTB2015 benchmark,which are better than the results of other competing algorithms.The results of this study can solve the problem of real-time object tracking in the real traffic environment and provide a specific reference for the detection of traffic abnormalities.展开更多
正交时频空间(Orthogonal Time Frequency Space)是近年来兴起的一种新型多载波调制技术。与正交频分复用(Orthogonal Frequency Division Multiplexing)一样,OTFS也存在峰均比(Peak to Average Power Ratio)过高的问题。为此,论文尝试...正交时频空间(Orthogonal Time Frequency Space)是近年来兴起的一种新型多载波调制技术。与正交频分复用(Orthogonal Frequency Division Multiplexing)一样,OTFS也存在峰均比(Peak to Average Power Ratio)过高的问题。为此,论文尝试将μ律压扩滤波器应用与OTFS系统。将发送端经过海森堡变换的信号中进行μ律压扩变换,且在接收端进行反压扩恢复原始信号,以降低PAPR。仿真结果表明,在OTFS中应用μ律压扩滤波器,在显著降低PAPR的同时,对误码率性能影响较小,且易于工程实现。展开更多
为探究高比例可再生能源系统下风光资源的消纳与多元化利用途径,提出一种电氨转换及风光时空相关性的多能耦合系统两阶段鲁棒优化模型。首先分析了电制氨的运行机制,并结合直接氨燃料电池技术,探讨了电制氨与氨燃料电池协同运行的系统...为探究高比例可再生能源系统下风光资源的消纳与多元化利用途径,提出一种电氨转换及风光时空相关性的多能耦合系统两阶段鲁棒优化模型。首先分析了电制氨的运行机制,并结合直接氨燃料电池技术,探讨了电制氨与氨燃料电池协同运行的系统特性。为综合考虑风光出力的相关性与不确定性并选择最相近极限场景,该文采用最小体积封闭椭球算法构建高维椭球集,并通过1-范数和∞-范数建立风光出力场景的概率分布置信集,有效整合风光出力不确定性的分布信息。针对鲁棒优化模型中二元变量导致计算时间较长问题,该文提出了一种改进列与约束生成(column and constraint generation,C&CG)算法,利用三分块-交替方向乘子法和近似凸化方法分别处理主-子问题,并通过非精确C&CG算法对主-子问题进行迭代求解,在确保计算效率的同时,快速逼近最优解。结果表明,所提模型获取的极限场景能够准确捕捉风光出力的时空相关性及不确定性,电-氨转换系统有效促进了可再生能源的合理消纳,在确保系统安全稳定运行的同时,显著提升了调度经济性及求解效率。展开更多
针对低信噪比环境下复杂多类雷达信号调制识别准确率低的问题,提出一种基于时频融合特征与多尺度双重注意力网络的新方法。通过应用平滑伪Wigner-Ville分布、傅里叶同步压缩变换和基于变分模态分解的希尔伯特黄变换3种时频分析方法,并...针对低信噪比环境下复杂多类雷达信号调制识别准确率低的问题,提出一种基于时频融合特征与多尺度双重注意力网络的新方法。通过应用平滑伪Wigner-Ville分布、傅里叶同步压缩变换和基于变分模态分解的希尔伯特黄变换3种时频分析方法,并结合去噪预处理技术,将雷达信号转换为三通道时频特征图,显著增强了特征的稳健性与表达力。设计了一种多尺度双重注意力网络,通过多尺度通道注意力机制实现跨尺度信息融合与噪声抑制,同时利用多尺度空间注意力自适应感知雷达信号的时频结构,并通过门控融合与残差连接技术进一步整合信息。实验结果表明,在信噪比为-10 d B的条件下,新方法对12类典型雷达信号调制方式的平均识别率达到98.99%,显示出良好的稳健性。展开更多
基金funded by the Basic Science Major Foundation(Natural Science)of the Jiangsu Higher Education Institutions of China(Grant:22KJA520012)the Xuzhou Science and Technology Plan Project(Grant:KC21303,KC22305)the sixth“333 project”of Jiangsu Province.
文摘Aiming at the problem that a single correlation filter model is sensitive to complex scenes such as background interference and occlusion,a tracking algorithm based on multi-time-space perception and instance-specific proposals is proposed to optimize the mathematical model of the correlation filter(CF).Firstly,according to the consistency of the changes between the object frames and the filter frames,the mask matrix is introduced into the objective function of the filter,so as to extract the spatio-temporal information of the object with background awareness.Secondly,the object function of multi-feature fusion is constructed for the object location,which is optimized by the Lagrange method and solved by closed iteration.In the process of filter optimization,the constraints term of time-space perception is designed to enhance the learning ability of the CF to optimize the final track-ing results.Finally,when the tracking results fluctuate,the boundary suppres-sion factor is introduced into the instance-specific proposals to reduce the risk of model drift effectively.The accuracy and success rate of the proposed algorithm are verified by simulation analysis on two popular benchmarks,the object tracking benchmark 2015(OTB2015)and the temple color 128(TC-128).Extensive experimental results illustrate that the optimized appearance model of the proposed algorithm is effective.The distance precision rate and overlap success rate of the proposed algorithm are 0.756 and 0.656 on the OTB2015 benchmark,which are better than the results of other competing algorithms.The results of this study can solve the problem of real-time object tracking in the real traffic environment and provide a specific reference for the detection of traffic abnormalities.
文摘正交时频空间(Orthogonal Time Frequency Space)是近年来兴起的一种新型多载波调制技术。与正交频分复用(Orthogonal Frequency Division Multiplexing)一样,OTFS也存在峰均比(Peak to Average Power Ratio)过高的问题。为此,论文尝试将μ律压扩滤波器应用与OTFS系统。将发送端经过海森堡变换的信号中进行μ律压扩变换,且在接收端进行反压扩恢复原始信号,以降低PAPR。仿真结果表明,在OTFS中应用μ律压扩滤波器,在显著降低PAPR的同时,对误码率性能影响较小,且易于工程实现。
文摘为探究高比例可再生能源系统下风光资源的消纳与多元化利用途径,提出一种电氨转换及风光时空相关性的多能耦合系统两阶段鲁棒优化模型。首先分析了电制氨的运行机制,并结合直接氨燃料电池技术,探讨了电制氨与氨燃料电池协同运行的系统特性。为综合考虑风光出力的相关性与不确定性并选择最相近极限场景,该文采用最小体积封闭椭球算法构建高维椭球集,并通过1-范数和∞-范数建立风光出力场景的概率分布置信集,有效整合风光出力不确定性的分布信息。针对鲁棒优化模型中二元变量导致计算时间较长问题,该文提出了一种改进列与约束生成(column and constraint generation,C&CG)算法,利用三分块-交替方向乘子法和近似凸化方法分别处理主-子问题,并通过非精确C&CG算法对主-子问题进行迭代求解,在确保计算效率的同时,快速逼近最优解。结果表明,所提模型获取的极限场景能够准确捕捉风光出力的时空相关性及不确定性,电-氨转换系统有效促进了可再生能源的合理消纳,在确保系统安全稳定运行的同时,显著提升了调度经济性及求解效率。
文摘针对低信噪比环境下复杂多类雷达信号调制识别准确率低的问题,提出一种基于时频融合特征与多尺度双重注意力网络的新方法。通过应用平滑伪Wigner-Ville分布、傅里叶同步压缩变换和基于变分模态分解的希尔伯特黄变换3种时频分析方法,并结合去噪预处理技术,将雷达信号转换为三通道时频特征图,显著增强了特征的稳健性与表达力。设计了一种多尺度双重注意力网络,通过多尺度通道注意力机制实现跨尺度信息融合与噪声抑制,同时利用多尺度空间注意力自适应感知雷达信号的时频结构,并通过门控融合与残差连接技术进一步整合信息。实验结果表明,在信噪比为-10 d B的条件下,新方法对12类典型雷达信号调制方式的平均识别率达到98.99%,显示出良好的稳健性。
