In order to eliminate the calculation error which is generated by the field point selection of finite-difference time-domain method on the interface of medium, this paper introduces a virtual field which is then unfol...
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ISBN:
(数字)9781728153049
ISBN:
(纸本)9781728153056
In order to eliminate the calculation error which is generated by the field point selection of finite-difference time-domain method on the interface of medium, this paper introduces a virtual field which is then unfolded by Taylor series, and gives the iterative formula of the nonstandard finite-difference time-domain method (NS-FDTD). The non-standard finite-difference time-domain method (NS-FDTD) is used to simulate plane wave irradiating vertically the novel sub-wavelength metal grating resonator, effects of the thickness of metal layer and the relative dielectric constant to extraordinary transmission characteristic are studied, and the extraordinary transmission mechanism is analyzed using the theory of Fabry-Perot cavity. A novel structure with extraordinary transmission characteristic is designed, and the extraordinary transmission characteristic in 450-900 THz band has also been studied using the method of NS-FDTD, the effect caused by some parameters such as thickness of metal layer, relative dielectric constant of dielectric layer has been given. The results show: as the thickness of the metal layer decreases, the factor of extraordinary transmission increases and moves towards high frequency, what's more, the factor moves towards low frequency as the relative dielectric constant of dielectric layer increases. This study provides a theoretical basis for further research on metal film and its extraordinary transmission mechanism.
Tracking with multistatic sonar measurements is challenging due to the fact that the measurements are nonlinear functions of the Cartesian state. To obtain a global estimation of the target position, the existing appr...
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Tracking with multistatic sonar measurements is challenging due to the fact that the measurements are nonlinear functions of the Cartesian state. To obtain a global estimation of the target position, the existing approaches are to fuse local estimations of the target position or expand the measurement vector to be global. But those methods may cause large amounts of calculations due to the need for many Kalman filters or a high dimension of the measurement vector. The paper converted measurements from measurement coordinates to Cartesian coordinates to obtain the global estimation of the target position based on a Kalman filter and avoiding the high dimension problem, which means a low calculation cost. The performance of the proposed method is demonstrated by different simulated scenarios.
Main results of theoretical and experimental investigations since the 1980s of 20th century that led to the formation and developing of new fundamental science discipline: 'Fractal Radio Physics and Fractal Radio ...
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Bistatic forward-looking SAR is a synthetic aperture radar system with an independently moving transmitter and receiver breaks through the limitations of the conventional monostatic SAR on the forward-looking imaging....
ISBN:
(数字)9781728129129
ISBN:
(纸本)9781728129136
Bistatic forward-looking SAR is a synthetic aperture radar system with an independently moving transmitter and receiver breaks through the limitations of the conventional monostatic SAR on the forward-looking imaging. However, the existence of a double hyperbola in the bistatic range equation makes the severe two-Dimension (2-D) coupling. Based on the bistatic SAR space geometrical model and the point target spectrum form the series reversion, this paper introduces the result of bistatic forward-looking SAR raw data processed using polynomial NCS algorithm is given to confirmed the applicability of mentioned algorithm. Furthermore, an analysis about the SAR image feature is discussed, then a produce is defined to slove the problem which may reduce the SNR of bistatic SAR is proposed.
Here, a multi-beam TEM-horn antenna with beam direction is proposed. Presented construction allows obtaining scanning beam and complicated antenna patterns, thus it can be used as substitute of ultra-wideband phased a...
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Because of computing and storage limitation of one satellite, it is difficult to process large amounts of data of spaceborne synthetic aperture radars. A new method for networked satellites data processing based on in...
ISBN:
(数字)9781728129129
ISBN:
(纸本)9781728129136
Because of computing and storage limitation of one satellite, it is difficult to process large amounts of data of spaceborne synthetic aperture radars. A new method for networked satellites data processing based on intersatellite cloud computing system (ICCS) using a “stage-by-stage” CS algorithm is proposed in this paper, which is built with FPGA chips as the computing kernel of the system. Different from the traditional CS algorithm processing, the system divides data processing into three stages. The computing tasks are reasonably allocated to different data processing units (i.e. satellites) in each stage. The method effectively saves computing and storage resources of satellites, improves the utilization rate of a single satellite, and shortens the data processing time. GF-3 satellite SAR raw data is processed by the system, with the performance of the method verified.
Nowadays, narrowband interferences (NBIs) severely affect the imaging quality of synthetic aperture radar (SAR) systems. Fortunately, NBIs has nearly fixed frequencies along the azimuth time and they are demonstrated ...
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Nowadays, narrowband interferences (NBIs) severely affect the imaging quality of synthetic aperture radar (SAR) systems. Fortunately, NBIs has nearly fixed frequencies along the azimuth time and they are demonstrated to be low rank in previous studies. All the NBI suppression methods are based on one-dimensional (1-D) and two-dimensional (2-D) domains to extract NBIs from the received signal. Actually, NBIs have a special low-rank property which can be employed in three-dimensional (3-D) domain for extra spacial degrees of freedom (DOFs). Hence in this paper, we propose a reweighted tensor nuclear norm minimization (RTNNM) algorithm to efficiently and effectively mitigate NBIs via three-mode tensor structure. The proposed method employs the special low-rank property of NBIs via multiple views in range-azimuth-space domain and deals with the drawback of the tensor nuclear norm minimization algorithm. The real X-band SAR data is employed to demonstrate the effectiveness and efficiency of the proposed method.
A dynamically tunable polarization converter has been proposed in this paper, which has a multi-layer structure consisting of an orthogonal cross metallic, graphene strips, spacer substrate and a gold back ground laye...
A dynamically tunable polarization converter has been proposed in this paper, which has a multi-layer structure consisting of an orthogonal cross metallic, graphene strips, spacer substrate and a gold back ground layer. In this paper, the proposed polarization converter can transform the linear polarization incident waves into its cross polarization in reflection mode in terahertz (THz) frequency within an ultra-wideband, and the polarization conversion ratio (PCR) of the proposed structure has over 97% from 4.1 THz to 7.1 THz. Furthermore, by adjusting the chemical potential (or Fermi energy) of the graphene strips, the operating frequency band can be changed dynamically.
Convolutional Neural Networks (CNNs) have achieved remarkable success in breast ultrasound image segmentation, but they still face several challenges when dealing with breast lesions. Due to the limitations of CNNs in...
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Convolutional Neural Networks (CNNs) have achieved remarkable success in breast ultrasound image segmentation, but they still face several challenges when dealing with breast lesions. Due to the limitations of CNNs in modeling long-range dependencies, they often perform poorly in handling issues such as similar intensity distributions, irregular lesion shapes, and blurry boundaries, leading to low segmentation accuracy. To address these issues, we propose the ThreeF-Net, a fine-grained feature fusion network. This network combines the advantages of CNNs and Transformers, aiming to simultaneously capture local features and model long-range dependencies, thereby improving the accuracy and stability of segmentation tasks. Specifically, we designed a Transformer-assisted Dual Encoder Architecture (TDE), which integrates convolutional modules and self-attention modules to achieve collaborative learning of local and global features. Additionally, we designed a Global Group Feature Extraction (GGFE) module, which effectively fuses the features learned by CNNs and Transformers, enhancing feature representation ability. To further improve model performance, we also introduced a Dynamic Fine-grained Convolution (DFC) module, which significantly improves lesion boundary segmentation accuracy by dynamically adjusting convolution kernels and capturing multi-scale features. Comparative experiments with state-of-the-art segmentation methods on three public breast ultrasound datasets demonstrate that ThreeF-Net outperforms existing methods across multiple key evaluation metrics.
A 5×5 broadside slot array backed by a single cavity containing a mode filter is designed. The resonant slot length is obtained by using a waveguide slot model. The simulated and measured results show that this a...
A 5×5 broadside slot array backed by a single cavity containing a mode filter is designed. The resonant slot length is obtained by using a waveguide slot model. The simulated and measured results show that this array achieves more than 8% -10dB return loss and 3dB gain bandwidth.
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