Airborne radar space and ground moving target classification and recognition method

A technology for classification and recognition of moving targets, applied to radio wave measurement systems, instruments, etc., can solve problems such as high signal-to-noise ratio requirements, and achieve the effects of stable target characteristics, easy engineering, and low cost

Inactive Publication Date: 2016-06-01
LEIHUA ELECTRONICS TECH RES INST AVIATION IND OF CHINA
View PDF4 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

文献(1.NagelID,SmithS.Creatingalikelihoodvectorforgroundmovingtargetsintheexo-clutterregionofairborneradarsignals.2012WorkshoponSensorDataFusion:Trends,Solutions,Application.Bonn,2012:49-54;2.NagelID,NeumannPC,SmithS.Classificationofgroundmovingtargetsintheexo-clutterregionofair-borneradarsignals.InternationalRadarSymposium,Wroclaw,2008:1- 5) It is proposed to classify and identify air-to-ground targets based on the difference in amplitude modulation characteristics (non-main clutter area) in the range-Doppler domain, but this often requires a higher signal-to-noise ratio

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
  • Airborne radar space and ground moving target classification and recognition method
  • Airborne radar space and ground moving target classification and recognition method
  • Airborne radar space and ground moving target classification and recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] An airborne radar aircraft target classification and recognition technology based on fractal and phase modulation features, including data preprocessing, extraction of fractal and phase modulation features, and classification and recognition algorithms.

[0037] 1. Data preprocessing

[0038] (1) Analyze the measured narrowband data, pulse pressure, and coherent accumulation;

[0039] (2) Extraction is used for feature training and testing, and the data is not less than 100 frames;

[0040] 2. Feature extraction algorithm

[0041] (1) Fractal feature extraction

[0042] Fractal is to describe the roughness and irregularity of the surface of an object. An important feature of fractal is that the calculated fractal dimension is a non-integer form, called fractal dimension, and the parameter describing fractal characteristics is called fractal dimension. Conventional man-made objects such as airplanes usually have a relatively regular geometric shape, and the fractal di...

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 belongs to the airborne radar target classification and recognition technical field and relates to a fractal and phase modulation characteristic-based airborne radar space and ground moving target classification and recognition method. The target classification and recognition algorithm provided by the invention can be realized under a narrow band working mode, and a large quantity of instantaneous bandwidth is not required, so that excessively many resources do not need to be consumed. The additional providing of a target classification and recognition function can be realized possibly under the condition that an airborne radar has miniaturization, multi-function multi-task, multiple-working mode and multi-target tracking requirements, and excessive consumption of radar resources usually has little possibility of being realized on the airborne radar. The recognition results of target features can be rendered based on 100 frames of data, and classification and recognition are carried out.

Description

technical field [0001] The invention belongs to the technical field of airborne radar target classification and recognition, and relates to a method for classification and recognition of airborne radar air-ground moving targets based on fractal and phase modulation features. Background technique [0002] Most airborne surveillance radars have good low-altitude detection performance, but when the airborne surveillance radar works in the downward-looking mode to monitor low-altitude aircraft, it will detect a large amount of ground moving target information, but the airborne radar in the prior art can only pass Doppler velocity and radar cross section (RCS) are used to judge target attributes. Since simultaneously detected low-altitude targets such as helicopters, drones, and ground vehicles have similar Doppler velocities and RCS, airborne radars are prone to misjudgment. [0003] In recent years, there are only a few domestic and foreign published documents on the research ...

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 王福友罗钉王德奇
Owner LEIHUA ELECTRONICS TECH RES INST AVIATION IND OF CHINA
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