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Frequency domain compressive sensing method aiming at sparse SAR (Synthetic Aperture Radar) images in airspace

A frequency domain compression and image technology, applied in the field of signal processing, can solve the problems of reducing the data rate, reducing the data rate, affecting the effect of signal reconstruction, etc., and achieving the effect of reducing the data rate

Inactive Publication Date: 2011-07-27
BEIHANG UNIV
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Problems solved by technology

However, at present, many compressed sensing methods only stay in the time domain analysis of the signal, and the data rate can only be reduced to 50% of the total number of original sampling values.
Blindly reducing the data rate will seriously affect the effect of signal reconstruction

Method used

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  • Frequency domain compressive sensing method aiming at sparse SAR (Synthetic Aperture Radar) images in airspace
  • Frequency domain compressive sensing method aiming at sparse SAR (Synthetic Aperture Radar) images in airspace
  • Frequency domain compressive sensing method aiming at sparse SAR (Synthetic Aperture Radar) images in airspace

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Embodiment

[0065] A signal with an upward distance is intercepted from the SAR image, which contains only two scattering points, that is, K=2, and the frequency domain signal length N=256. Using the frequency domain compressed sensing method, the observation vector Y=[α 1 , α 2 ,p 1 ,p 2 ]. According to the observation vector, the frequency domain signal can be reconstructed. After inverse Fourier transform, a high-resolution one-dimensional range image can be obtained. Figure 2a and Figure 2b are the pulse pressure results of the original signal and the reconstructed signal in the time domain, respectively. Table 1 evaluates the effect of reconstruction from distance resolution, peak sidelobe ratio and integral sidelobe ratio respectively.

[0066] Table 1 Pulse pressure results of original signal and reconstructed signal

[0067]

[0068] A single-view complex SAR image with sparse spatial domain is used for simulation. The size of the image is 256×256, and it is sparse i...

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Abstract

The invention discloses a frequency domain compressive sensing method aiming at sparse SAR (Synthetic Aperture Radar) images in airspace and belonging to the technical field of signal processing. The frequency domain compressive sensing method particularly comprises the following steps of: step 1: determining the directions of original SAR images, with sparsity; step 2: carrying out Fourier transform on the original SAR images along the directions with the sparsity to obtain frequency domain images of the directions; step 3: building frequency domain sparse reconstructed models, solving model parameters, establishing observation vectors, and reconstructing frequency domain signals so as to form reconstructed frequency domain images; and step 4: carrying out the Fourier transform on the reconstructed frequency domain images along the directions to obtain reconstructed images. In the invention, by analyzing the sparsity of the SAR images in the airspace, the frequency domain sparse reconstructed models are built by aiming at the frequency domain signals, the model parameters are estimated, projection is carried out on the basis of an appropriate observation matrix and the frequency domain signals are reconstructed by utilizing a small quantity of observed values.

Description

technical field [0001] The present invention relates to a compressed sensing (Compressive Sensing, CS) method for image reconstruction, in particular to a frequency domain compressed sensing (Frequency Domain Compressive Sensing, FDCS) method for sparse SAR images in the spatial domain, belonging to the technical field of signal processing . Background technique [0002] With the rapid development of information technology, people's demand for information is increasing day by day. The traditional Nyquist sampling theorem requires that the sampling rate of the signal should not be lower than twice the signal bandwidth in order to accurately reconstruct the signal. With the increase of signal bandwidth, the required sampling rate and processing speed are getting higher and higher, which brings great challenges to the signal processing capability and corresponding hardware devices. In practical applications, in order to reduce the cost of storage, processing and transmission,...

Claims

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Application Information

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IPC IPC(8): G01S13/90
Inventor 陈杰陈岚李小波朱燕青李春升
Owner BEIHANG UNIV
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