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

Two-dimensional self-adaptive radar CFAR (constant false alarm rate) detection method

A constant false alarm detection and self-adaptive technology, applied in the field of target tracking, can solve the problems of CA_CFAR detection performance is good, detection performance decline, detection performance is not as good as to achieve the effect of improving the ability to deal with complex environments and improve the ability to deal with complex environments

Inactive Publication Date: 2013-10-16
XIDIAN UNIV
View PDF6 Cites 35 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] CA_CFAR has good detection performance in the environment of uniform clutter background, but when there are multiple targets or multiple strong interferences, the detection performance will be seriously degraded; OS_CFAR is a CFAR detection method based on ordered statistics, including The detection performance is worse than CA_CFAR in a multi-target environment with interfering targets, but the detection performance is not as good as CA_CFAR in a uniform clutter environment

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
  • Two-dimensional self-adaptive radar CFAR (constant false alarm rate) detection method
  • Two-dimensional self-adaptive radar CFAR (constant false alarm rate) detection method
  • Two-dimensional self-adaptive radar CFAR (constant false alarm rate) detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0040] Step 1, dividing the received echo signal matrix into blocks.

[0041] The radar receives an echo signal matrix with a size of M×N during target detection. To judge whether there is a target, each data unit of the echo signal must be judged one by one.

[0042] When the present invention detects radar targets, the received echo signal matrix is ​​first divided into blocks, and then divided into n sub-blocks with a size of p×q, wherein: M, N, p, and q are not equal to 0, and p, q cannot be 1 at the same time.

[0043] Step 2, calculate the judgment factor α of the sub-block attribute by Monte Carlo simulation experiment.

[0044] To judge the attribute of a sub-block, there needs to be a judgment standard, and the judgment factor α is introduced here,

[0045] 2a) Define the mean ratio k=1,2,...n;

[0046] Among them, β k is the data mean value of the kth sub-...

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

Te invention discloses a two-dimensional self-adaptive radar CFAR (constant false alarm rate) detection method, and mainly solves reduced detection performance during detection by using a signle CA_CFAR method and a signle OS_CFAR method when multiple targets or strong interference occur in clutter background. The method is realized through the following steps of 1) dividing a M*N clutter matrix block following different distributions into n p*q sub-blocks; 2) calculating a judgement factor alpha of an attribute of every sub-block; 3) judging the attribute of every sub-block according to the judgement factor alpha; 4) calculating a two-dimensional unit average CFAR detection threshold value factor T1 and a two-dimensional ordered CFAR detection threshold value factor T2 in different clutter distribution conditions; 5) obtaining detection thresholds K1 (i, j) and K2 (i, j) of every data unit of uniform distributed sub-blocks and non-uniform distributed sub-blocks respectively by using the threshold value factors T1 and T2; and 6) comparing the detection thresholds with every data unit during radar target detection, thereby determining whether a target exists in the data units. The method has the advantages of high detection performance and strong capability of coping with complex environments.

Description

technical field [0001] The invention belongs to the technical field of radar and relates to radar target detection, in particular to a radar constant false alarm detection method for interference targets in two-dimensional signals, which can be used for target tracking. Background technique [0002] The main functions of radar signal processing are detection, tracking and imaging. In radar, detection refers to determining whether a radar measurement is an echo of a target or merely an interference term. Only when it is determined that the measured value is the echo of the target can the next step be processed, such as tracking the target through precise range, angle or Doppler measurements. [0003] Detection decisions are applied at various stages of radar signal processing, from raw echoes to preprocessed data such as Doppler spectra, and even synthetic aperture radar images. For example, each pulse corresponds to a range unit. If there is a target at a certain distance,...

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 Applications(China)
IPC IPC(8): G01S7/41
Inventor 杨明磊陈伯孝夏碧君邓海棠潘静雅
Owner XIDIAN UNIV
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com