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SAR image ship CFAR detection method based on bilateral truncation statistical characteristics

A statistical feature and image technology, applied in the field of SAR image target detection, can solve the problems of real sea clutter sample removal, poor parameter estimation accuracy, complex process, etc., to improve detection performance, improve fit, and improve calculation efficiency effect

Active Publication Date: 2021-06-01
HEFEI UNIV OF TECH
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Problems solved by technology

However, these methods usually rely on a fixed threshold for clutter truncation. If the fixed threshold is wrongly selected, a large number of real sea clutter samples will be removed, resulting in poor parameter estimation accuracy.
In addition, the clutter truncation and parameter estimation process based on a fixed threshold requires a large number of iterative calculations, which is complex and inefficient

Method used

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  • SAR image ship CFAR detection method based on bilateral truncation statistical characteristics
  • SAR image ship CFAR detection method based on bilateral truncation statistical characteristics
  • SAR image ship CFAR detection method based on bilateral truncation statistical characteristics

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Embodiment Construction

[0050] In this example, if figure 1 As shown, a SAR image ship CFAR detection method based on bilateral truncated statistical properties includes the following steps:

[0051] Step 1: Acquire a SAR image, and set a local sliding window composed of the target window and the background window, and calculate the logarithmic domain mean μ of all pixels of the SAR image in the background window B_ln and the log-domain standard deviation σ B_ln , and then calculate the variation index VI according to the formula (1), and obtain the truncation rule shown in the formula (2), so as to remove the pixels in the background window that do not satisfy the formula (2), and obtain the truncated real sea clutter pixel set express The gray value of the i-th pixel in , i∈[1,n], n represents the number of pixels:

[0052]

[0053] mu B_ln -t 1 ·σ B_ln B )≤μ B_ln +exp(γ / VI)·σ B_ln (2)

[0054] In formula (2), t 1 is the low truncation depth, γ is the weight of the high truncation d...

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Abstract

The invention discloses an SAR image ship CFAR detection method based on bilateral truncation statistical characteristics. The method comprises the steps: 1, obtaining an SAR image, setting a local sliding window composed of a target window and a background window, calculating a logarithm domain mean value, a logarithm domain standard deviation and a variation index of pixels in the background window, obtaining a truncation rule, removing the heterogeneous pixels therein; 2, performing logarithm domain mean value and logarithm domain standard deviation estimation on the reserved real sea clutter by adopting a maximum likelihood estimation method; 3, modeling the real sea clutter gray scale probability density by using logarithmic normal distribution; and 4, establishing a judgment rule according to a given detection false alarm rate, and performing target judgment on the to-be-detected pixel in the target window. According to the method, the heterogeneous pixels in the background window can be effectively removed, so that the detection rate of the ship target under the complex sea condition can be effectively improved on the premise of keeping a relatively low false alarm rate, the calculation efficiency is high, and the method has a relatively good engineering application value.

Description

technical field [0001] The invention relates to the technical field of SAR image target detection, in particular to a SAR image ship CFAR detection method based on bilateral truncation statistical characteristics under complex sea conditions. Background technique [0002] Synthetic Aperture Radar (SAR) is a new technology in the development of radar, it is a high-resolution active imaging sensor. Using SAR remote sensing means, it is possible to realize multi-polarization, multi-band, and multi-angle observation of ground objects, and the obtained image feature information is rich, including amplitude, phase and polarization and other information. Due to the all-day and all-weather observation capabilities of SAR, target detection using SAR images has been highly valued in the field of marine remote sensing, and has gradually become a research hotspot in the current stage of marine applications of SAR images. [0003] Due to the imaging characteristics of SAR, sea clutter i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/292G01S7/35G01S13/90
CPCG01S7/2927G01S7/354G01S13/9021
Inventor 艾加秋毛宇翔裴志林江凯黄光红
Owner HEFEI UNIV OF TECH
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