The problem of two order statistics detection schemes for the detection of a spatially distributed target in white Gaussian noise are studied.When the number of strong scattering cells is known,we first show an optima...The problem of two order statistics detection schemes for the detection of a spatially distributed target in white Gaussian noise are studied.When the number of strong scattering cells is known,we first show an optimal detector,which requires many processing channels.The structure of such optimal detector is complex.Therefore,a simpler quasi-optimal detector is then introduced.The quasi-optimal detector,called the strong scattering cells’ number dependent order statistics（SND-OS） detector,takes the form of an average of maximum strong scattering cells with a known number.If the number of strong scattering cells is unknown in real situation,the multi-channel order statistics（MC-OS） detector is used.In each channel,a various number of maximums scattered from target are averaged.Then,the false alarm probability analysis and thresholds sets for each channel are given,following the detection results presented by means of Monte Carlo simulation strategy based on simulated target model and three measured targets.In particular,the theoretical analysis and simulation results highlight that the MC-OS detector can efficiently detect range-spread targets in white Gaussian noise.展开更多
A method to describe the generation channels of high-order harmonics is proposed. According to this method, the mechanism of generation-channel interference of high-order harmonics is revealed clearly. We take the anh...A method to describe the generation channels of high-order harmonics is proposed. According to this method, the mechanism of generation-channel interference of high-order harmonics is revealed clearly. We take the anharmonic oscillator driven by bi-chrome fields as an example to illustrate that this method can be used to understand the effect of generation-channel interference.展开更多
由于受到硬件条件的限制,通常难以获得具有高分辨率(HR)的遥感图像。利用单幅图像超分辨率(SISR)技术对低分辨率(LR)遥感图像进行超分辨率重建是获取高分辨率遥感图像的常用方法。近年来,在图像超分辨率领域引入的卷积神经网络(CNN)改...由于受到硬件条件的限制,通常难以获得具有高分辨率(HR)的遥感图像。利用单幅图像超分辨率(SISR)技术对低分辨率(LR)遥感图像进行超分辨率重建是获取高分辨率遥感图像的常用方法。近年来,在图像超分辨率领域引入的卷积神经网络(CNN)改进了图像重建性能。然而,现有的基于CNN的超分辨率模型通常使用低阶注意力机制提取深层特征,其表征能力有待提高,且常规卷积的感受野有限,缺乏对远距离依赖关系的学习。为了解决以上问题,提出了一种基于递归门控卷积的遥感图像超分辨率方法RGCSR。该方法引入递归门控卷积g n Conv学习全局依赖和局部细节,通过高阶空间交互来获取高阶特征。首先,使用由高阶交互子模块(HorBlock)和前馈神经网络(FFN)组成的高阶交互——前馈神经网络模块(HFB)提取高阶特征。其次,利用由通道注意力(CA)和g n Conv构建的特征优化模块(FOB)优化各个中间模块的输出特征。最后,在多个数据集上的对比结果表明,RGCSR比现有的基于CNN的超分辨率方法具备更好的重建性能和视觉效果。展开更多
Coherent detection in OFDM systems requires accurate channel state information (CSI) at the receiver. Channel estimation based on pilot-symbol-assisted transmissions provides a reliable way to obtain CSI. Use of pilot...Coherent detection in OFDM systems requires accurate channel state information (CSI) at the receiver. Channel estimation based on pilot-symbol-assisted transmissions provides a reliable way to obtain CSI. Use of pilot symbols for channel estimation, introduces overhead and it is desirable to keep the number of pilot symbols as minimum as possible. This paper introduces a new tight bound for the number of pilots in channel estimation using adaptive scheme in OFDM systems. We calculate the minimum number of necessary pilots using two approaches. The first approach for the number of pilots is obtained based on Doppler frequency shift estimation and the second approach is acquired based on channel length estimation using second order statistics of received signal. Finally we obtain the tight bound for the number of pilots using attained values.展开更多
基金supported by the Major Program of National Natural Science Foundation of China (10990012)the National Natural Science Foundation of China (61201296,61271024)+1 种基金the Fundamental Research Funds for the Central Universities (K5051202037)Guangxi Key Lab of Wireless Wideband Communication & Signal Processing (12205)
文摘The problem of two order statistics detection schemes for the detection of a spatially distributed target in white Gaussian noise are studied.When the number of strong scattering cells is known,we first show an optimal detector,which requires many processing channels.The structure of such optimal detector is complex.Therefore,a simpler quasi-optimal detector is then introduced.The quasi-optimal detector,called the strong scattering cells’ number dependent order statistics（SND-OS） detector,takes the form of an average of maximum strong scattering cells with a known number.If the number of strong scattering cells is unknown in real situation,the multi-channel order statistics（MC-OS） detector is used.In each channel,a various number of maximums scattered from target are averaged.Then,the false alarm probability analysis and thresholds sets for each channel are given,following the detection results presented by means of Monte Carlo simulation strategy based on simulated target model and three measured targets.In particular,the theoretical analysis and simulation results highlight that the MC-OS detector can efficiently detect range-spread targets in white Gaussian noise.
基金Project supported by the National Natural Science Foundation of China (Grant No.10874133)
文摘A method to describe the generation channels of high-order harmonics is proposed. According to this method, the mechanism of generation-channel interference of high-order harmonics is revealed clearly. We take the anharmonic oscillator driven by bi-chrome fields as an example to illustrate that this method can be used to understand the effect of generation-channel interference.
文摘由于受到硬件条件的限制,通常难以获得具有高分辨率(HR)的遥感图像。利用单幅图像超分辨率(SISR)技术对低分辨率(LR)遥感图像进行超分辨率重建是获取高分辨率遥感图像的常用方法。近年来,在图像超分辨率领域引入的卷积神经网络(CNN)改进了图像重建性能。然而,现有的基于CNN的超分辨率模型通常使用低阶注意力机制提取深层特征,其表征能力有待提高,且常规卷积的感受野有限,缺乏对远距离依赖关系的学习。为了解决以上问题,提出了一种基于递归门控卷积的遥感图像超分辨率方法RGCSR。该方法引入递归门控卷积g n Conv学习全局依赖和局部细节,通过高阶空间交互来获取高阶特征。首先,使用由高阶交互子模块(HorBlock)和前馈神经网络(FFN)组成的高阶交互——前馈神经网络模块(HFB)提取高阶特征。其次,利用由通道注意力(CA)和g n Conv构建的特征优化模块(FOB)优化各个中间模块的输出特征。最后,在多个数据集上的对比结果表明,RGCSR比现有的基于CNN的超分辨率方法具备更好的重建性能和视觉效果。
文摘Coherent detection in OFDM systems requires accurate channel state information (CSI) at the receiver. Channel estimation based on pilot-symbol-assisted transmissions provides a reliable way to obtain CSI. Use of pilot symbols for channel estimation, introduces overhead and it is desirable to keep the number of pilot symbols as minimum as possible. This paper introduces a new tight bound for the number of pilots in channel estimation using adaptive scheme in OFDM systems. We calculate the minimum number of necessary pilots using two approaches. The first approach for the number of pilots is obtained based on Doppler frequency shift estimation and the second approach is acquired based on channel length estimation using second order statistics of received signal. Finally we obtain the tight bound for the number of pilots using attained values.
