Unlock instant, AI-driven research and patent intelligence for your innovation.

A Subspace Feature Extraction Method for Multi-rotor UAV Recognition

A multi-rotor UAV and subspace feature technology, applied in the field of target recognition, can solve problems such as ineffective utilization of spatial distribution information, and achieve the effect of enhancing spatial distribution structure information and improving recognition rate.

Active Publication Date: 2022-03-25
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the conventional subspace composed of the main projection components has the same weight for each projection component. In addition, the spatial distribution information of the samples is not effectively utilized. Therefore, the multi-rotor UAV identification method based on the conventional eigensubspace has been further improved. room for target recognition

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
  • A Subspace Feature Extraction Method for Multi-rotor UAV Recognition
  • A Subspace Feature Extraction Method for Multi-rotor UAV Recognition
  • A Subspace Feature Extraction Method for Multi-rotor UAV Recognition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] The practicability of the present invention will be described below in combination with simulation experiments.

[0033] Four types of UAVs were designed for the simulation experiment, including three-rotor UAVs, four-rotor UAVs, six-rotor UAVs, and eight-rotor UAVs. The blade length is 0.3m, and the distance from the axis to the origin is 0.8m, rotor speed 1200r / m. The simulated radar parameters include: the radar carrier frequency is 24GHz; the pulse repetition frequency is 100KHz; the distance between the target and the radar is 200m; the pitch angle of the UAV relative to the radar is 10°, and the azimuth angle is 30°

[0034] Each type of target records the radar echo signal for 10s, and divides it into segments with a fixed length of 0.05s (including at least one rotation period), the overlap between segments is 50%, and each segment contains 0.05×100000=5000 radar echoes Wave sampling data points, a total of 400 segments for each category. Among the 400 segment...

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 technical field of target recognition, and in particular relates to a subspace feature extraction method for multi-rotor UAV recognition. The present invention first clusters the radar echo data sets of each type of unmanned aerial vehicle, and then forms a clustering distance vector between the sample data and the Mahalanobis distance between the target clustering centers of various types of unmanned aerial vehicles. The singular value weighted subspace is constructed using the class distance vector, the target features are extracted, and the recognition of the multi-rotor UAV is completed. Due to the introduction of clustering distance, the spatial distribution structure information of the sample is enhanced. At the same time, when constructing the subspace, the singular value is used for weighting, which highlights the role of the main projection component, thereby improving the recognition rate of the target.

Description

technical field [0001] The invention belongs to the technical field of target recognition, and in particular relates to a subspace feature extraction method for multi-rotor UAV recognition. Background technique [0002] With the widespread application of drones in military and civilian fields, it has also brought about great security problems, such as illegal intrusion into private areas, collisions with aircraft, and terrorist attacks. Therefore, accurately identifying the type of UAV has very important practical significance in anti-UAV operations. [0003] At present, the eigensubspace method is an effective method for identifying UAVs. It mainly performs eigendecomposition through the radar echo data set of UAV targets, constructs subspaces from the main projection components, and extracts target features. However, the conventional subspace composed of the main projection components has the same weight for each projection component. In addition, the spatial distribution...

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): G06V10/40G06V10/762G06V10/774G06K9/62G06F30/27G01S7/41
CPCG06F30/27G01S7/415G06V10/40G06F18/23213G06F18/214
Inventor 周代英宋苏杭钱凯
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA