Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Ship cfar detection method based on bilateral truncated statistics in sar images

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 the detection performance, improve the goodness of fit, and improve the calculation. The effect of efficiency

Active Publication Date: 2022-03-15
HEFEI UNIV OF TECH
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Ship cfar detection method based on bilateral truncated statistics in sar images
  • Ship cfar detection method based on bilateral truncated statistics in sar images
  • Ship cfar detection method based on bilateral truncated statistics in sar images

Examples

Experimental program
Comparison scheme
Effect test

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...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method for detecting ship CFAR in SAR images based on bilateral truncation statistical characteristics. The steps include: 1. Obtain a SAR image, set a local sliding window composed of a target window and a background window, and calculate the pixels in the background window The logarithmic domain mean, logarithmic domain standard deviation and variation index of the logarithmic domain mean and logarithmic domain standard deviation and variation index are obtained, and the truncation rule is obtained to remove the heterogeneous pixels; 2. The logarithmic domain mean and logarithm Domain standard deviation estimation; 3. Use the lognormal distribution to model the gray probability density of real sea clutter; 4. Establish a decision rule based on a given detection false alarm rate, and target the pixels to be tested in the target window judge. The invention can effectively remove heterogeneous pixels in the background window, thereby effectively improving the detection rate of ship targets under complex sea conditions while maintaining a low false alarm rate, and has high calculation efficiency, and has 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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products