MM-CFAR target detection method

A technology of target detection and constant false alarm, applied in radio wave measurement systems, special data processing applications, instruments, etc.

Active Publication Date: 2014-04-30
江苏盐综产业投资发展有限公司
View PDF3 Cites 28 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to address the shortcomings of the existing radar maneuvering weak target detection under a single clutter background, and propose a multi-mode constant false alarm (MM-CFAR) target detection method. The clutter backg

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
  • MM-CFAR target detection method
  • MM-CFAR target detection method
  • MM-CFAR target detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] The present invention will be further described below in conjunction with accompanying drawing.

[0032] Such as figure 1 As shown, a multi-mode based CFAR target detection method, that is, adopting the unit average CFAR in the uniform background, and using the deleted mean CFAR in the non-uniform background, specifically includes the following steps:

[0033] Step 1. Establish uniform and non-uniform distribution clutter background models.

[0034] (1) Establish Rayleigh uniform distribution (Rayleigh distribution). Rayleigh uniform distribution corresponds to a uniformly distributed clutter background. The expression of its probability density function is:

[0035] f ( x ) = x σ 2 exp ( - x 2 2 ...

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 an MM-CFAR target detection method. The method is characterized by comprising the following steps that 1, uniformly-distributed clutter background models and non-uniformly-distributed clutter background models are built; 2, a model set corresponding to clutter background areas is built; 3, MM-CFAR reference windows are divided into a left reference window and a right reference window; 4, weight calculation is conducted according to the model set M, and corresponding constant false alarm processing is conducted according to the value of the weight; 5, threshold coefficients B[0] and B[1] are calculated, a detection probability formula is obtained according to the weight of CA-CFAR and CMLD-CFAR, and detection probability P[d] is obtained. The MM-CFAR target detection method is used for various clutter backgrounds, and the advantages of the CA-CFAR and CMLD-CFAR during detection in uniform backgrounds and non-uniform backgrounds are respectively utilized; compared with a general OS-CFAR, the detection probability is greatly improved in clutter edge backgrounds.

Description

technical field [0001] The invention belongs to the field of radar signal processing, and relates to a multi-mode-based constant false alarm (Multiple Model CFAR, MM-CFAR) target detection method. Background technique [0002] At present, the airborne early warning radar signal processing often adopts long-term coherent accumulation method to increase the actual use of weak target echo signal energy and improve radar detection performance. Although the signal-to-noise ratio of the weak target echo signal has been improved after long-term energy accumulation and various clutter suppression, there are still various noises, clutter, and interference signals in the signal. When using traditional fixed-threshold detection, when the detection threshold is high, the false alarm rate is low, but the target signal may not pass the detection, resulting in a large number of false alarms; and when the detection threshold is lowered, the detection probability will increase, but A large ...

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
IPC IPC(8): G01S7/41G06F19/00
CPCG01S7/414
Inventor 郭云飞周森山彭冬亮骆吉安郑晓枫唐学大
Owner 江苏盐综产业投资发展有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap