摘要 :
Symmetry is a powerful tool to reduce the freedom degrees of a problem. However, the applicability of the symmetry tool strongly depends on the possibility to calculate the symmetries of the system. General searching methods, e.g....
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Symmetry is a powerful tool to reduce the freedom degrees of a problem. However, the applicability of the symmetry tool strongly depends on the possibility to calculate the symmetries of the system. General searching methods, e.g., ergodic searching, is unpractical for a high-dimensional system since the order of the symmetric group grows with n, where n is the dimension of the system. We propose an approach based on genetic algorithms to search for the symmetric permutations of a binary patterns set. Calculations for five kinds of dimensional pattern set are also given. Results show that the majority of symmetric permutations can be found within an acceptable time for a high-dimensional pattern set by the new approach, which makes it possible to study and design high-dimensional artificial neural networks by the method of symmetry.
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摘要 :
Symmetry is a powerful tool to reduce the freedom degrees of a problem. However, the applicability of the symmetry tool strongly depends on the possibility to calculate the symmetries of the system. General searching methods, e.g....
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Symmetry is a powerful tool to reduce the freedom degrees of a problem. However, the applicability of the symmetry tool strongly depends on the possibility to calculate the symmetries of the system. General searching methods, e.g., ergodic searching, is unpractical for a high-dimensional system since the order of the symmetric group grows with n, where n is the dimension of the system. We propose an approach based on genetic algorithms to search for the symmetric permutations of a binary patterns set. Calculations for five kinds of dimensional pattern set are also given. Results show that the majority of symmetric permutations can be found within an acceptable time for a high-dimensional pattern set by the new approach, which makes it possible to study and design high-dimensional artificial neural networks by the method of symmetry.
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摘要 :
The general approach to ISAR imaging is range-Doppler (RD) imaging approach. For this approach, the translational motion compensation (TMC) is firstly obtained by envelope alignment and autofocus, so the target can be treated as a...
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The general approach to ISAR imaging is range-Doppler (RD) imaging approach. For this approach, the translational motion compensation (TMC) is firstly obtained by envelope alignment and autofocus, so the target can be treated as a rotating target for the next processing. But in this method, scatterers' migration through resolution cells (MTRC) caused by rotational motion is neglected. However in practice, MTRC exists with the improvement of resolution or for big target. For MTRC compensation, a keystone transformation in SAR is used in this paper. Before keystone transformation, it is demanded that the raw data is coherent, while in fact, the ISAR raw data is usually not. So a coherent processing of raw data is proposed. In this paper, the coherent processing of raw data is firstly done and the next step is to correct MTRC. Finally a parameter estimation method of multi-component amplitude modulation and linear frequency modulation (AM-LFM) signal is proposed to estimate the scatterers' instantaneous amplitudes and frequencies, and the range-Instantaneous Doppler (RID) ISAR image is obtained. The effective of this algorithm is testified by the processing of simulation data.
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摘要 :
The general approach to ISAR imaging is range-Doppler (RD) imaging approach. For this approach, the translational motion compensation (TMC) is firstly obtained by envelope alignment and autofocus, so the target can be treated as a...
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The general approach to ISAR imaging is range-Doppler (RD) imaging approach. For this approach, the translational motion compensation (TMC) is firstly obtained by envelope alignment and autofocus, so the target can be treated as a rotating target for the next processing. But in this method, scatterers' migration through resolution cells (MTRC) caused by rotational motion is neglected. However in practice, MTRC exists with the improvement of resolution or for big target. For MTRC compensation, a keystone transformation in SAR is used in this paper. Before keystone transformation, it is demanded that the raw data is coherent, while in fact, the ISAR raw data is usually not. So a coherent processing of raw data is proposed. In this paper, the coherent processing of raw data is firstly done and the next step is to correct MTRC. Finally a parameter estimation method of multi-component amplitude modulation and linear frequency modulation (AM-LFM) signal is proposed to estimate the scatterers' instantaneous amplitudes and frequencies, and the Range-Instantaneous Doppler (RID) ISAR image is obtained. The effective of this algorithm is testified by the processing of simulation data.
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摘要 :
The general approach to ISAR imaging is range-Doppler (RD) imaging approach. For this approach, the translational motion compensation (TMC) is firstly obtained by envelope alignment and autofocus, so the target can be treated as a...
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The general approach to ISAR imaging is range-Doppler (RD) imaging approach. For this approach, the translational motion compensation (TMC) is firstly obtained by envelope alignment and autofocus, so the target can be treated as a rotating target for the next processing. But in this method, scatterers' migration through resolution cells (MTRC) caused by rotational motion is neglected. However in practice, MTRC exists with the improvement of resolution or for big target. For MTRC compensation, a keystone transformation in SAR is used in this paper. Before keystone transformation, it is demanded that the raw data is coherent, while in fact, the ISAR raw data is usually not. So a coherent processing of raw data is proposed. In this paper, the coherent processing of raw data is firstly done and the next step is to correct MTRC. Finally a parameter estimation method of multi-component amplitude modulation and linear frequency modulation (AM-LFM) signal is proposed to estimate the scatterers' instantaneous amplitudes and frequencies, and the range-Instantaneous Doppler (RID) ISAR image is obtained. The effective of this algorithm is testified by the processing of simulation data.
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摘要 :
The anntenna area of distributed micosateliites radar system is usually smaller than the minimum SAR antenna area constraint, and there are range-Doppler ambiguities. So one key focus of this signal processing research is to devel...
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The anntenna area of distributed micosateliites radar system is usually smaller than the minimum SAR antenna area constraint, and there are range-Doppler ambiguities. So one key focus of this signal processing research is to develop processing approaches that exploit the added degrees of freedom of a spatially diverse formation to resolve inherent ambiguities of this sparse aperture distributed micosateliites radar system. In the paper, a beamform processing method of three-dimensional sparse arrays is proposed to spatially null Doppler ambiguities. This method first filters out each unambiguous frequency point from ambiguous Doppler channels of a few different phase centers by using spatial filter, this processing can be regard as a space-time processing, then combines all unambiguous frequency point to a whole unambiguous Doppler band, after that, does imaging processing. Theoretical derivation, performance analysis, and simulation of this method are discussed in the paper.
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摘要 :
The anntenna area of distributed micosateliites radar system is usually smaller than the minimum SAR antenna area constraint, and there are range-Doppler ambiguities. So one key focus of this signal processing research is to devel...
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The anntenna area of distributed micosateliites radar system is usually smaller than the minimum SAR antenna area constraint, and there are range-Doppler ambiguities. So one key focus of this signal processing research is to develop processing approaches that exploit the added degrees of freedom of a spatially diverse formation to resolve inherent ambiguities of this sparse aperture distributed micosateliites radar system. In the paper, a beamform processing method of three-dimensional sparse arrays is proposed to spatially null Doppler ambiguities. This method first filters out each unambiguous frequency point from ambiguous Doppler channels of a few different phase centers by using spatial filter, this processing can be regard as a space-time processing, then combines all unambiguous frequency point to a whole unambiguous Doppler band, after that, does imaging processing. Theoretical derivation, performance analysis, and simulation of this method are discussed in the paper.
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摘要 :
The anntenna area of distributed micosateliites radar system is usually smaller than the minimum SAR antenna area constraint, and there are range-Doppler ambiguities. So one key focus of this signal processing research is to devel...
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The anntenna area of distributed micosateliites radar system is usually smaller than the minimum SAR antenna area constraint, and there are range-Doppler ambiguities. So one key focus of this signal processing research is to develop processing approaches that exploit the added degrees of freedom of a spatially diverse formation to resolve inherent ambiguities of this sparse aperture distributed micosateliites radar system. This paper proposed a Doppler ambiguity resolving method which makes the Doppler ambiguities null in Doppler domain using spatial filter of multiple phase centres.
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Usually inverse synthetic aperture radar (ISAR) imaging is for small aircraft, with long range, moreover the coherent integration angle is small, that is the target's wavenumber spectrum support region can be regard as a rectangle...
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Usually inverse synthetic aperture radar (ISAR) imaging is for small aircraft, with long range, moreover the coherent integration angle is small, that is the target's wavenumber spectrum support region can be regard as a rectangle, Range-Doppler(RD) algorithm or Range-Instantaneous-Doppler (RID) algorithm are employed for image reconstruction after translational motion compensation (TMC), which includes envelope alignment (such as envelope correlation algorithm, minimum entropy algorithm) and autofocus (such as single PPP algorithm, multiple PPP algorithm, PGA, weighted least square algorithm). But migration through resolution cell (MTRC) is not considered after TMC, in fact, the scatterers around the target usually take place MTRC if the size of target is large. In the paper, we first align and focus the high resolution radar target echoes according target center, then we do time scale transform in target's wavenumber domain, that is Soumekh proposed 'keystone' interpolation to compensate MTRC (which can also be realized rapidly by DFT-IFFT or SFT-IFFT in azimuth direction), after range compression (range IFFT), for steadily flying target, target image can be obtained only after azimuth compression (that is FFT in azimuth direction), for maneuvering target, time-frequency analysis must be taken for every range cell, and the existing instantaneous imaging algorithms (such as joint time-frequency distribution algorithm, Radon-Wigner algorithm) are also effective to obtain RID images. This paper gives the ISAR imaging algorithm flow diagram to obtain images from raw data of steadily flying and maneuvering big targets, and simulate data and real data prove that algorithm flow is effective.
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The sufficient condition that guarantees perfect segmentation for an image with PCNNs when the intensity ranges of adjacent regions overlap is one of the main results presented in reference[1]. However, with deep understanding of ...
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The sufficient condition that guarantees perfect segmentation for an image with PCNNs when the intensity ranges of adjacent regions overlap is one of the main results presented in reference[1]. However, with deep understanding of the derivation process used in [1], it is shown in this paper that it is not a sufficient condition. The conditions for perfect image segmentation when there is an overlap in intensity ranges of adjacent regions are still remained unsolved.
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