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A radar target detection method and system based on graph data and gcn

A radar target and detection method technology, applied in radio wave measurement systems, measurement devices, electromagnetic wave re-radiation, etc. Strong feature extraction ability and the effect of reducing the amount of training parameters

Active Publication Date: 2022-05-13
NAVAL AVIATION UNIV
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Problems solved by technology

This kind of method classifies completely based on the characteristics of the signal sequence, and the signal samples are completely independent of each other during the training and testing process, but the time-domain and spatial-domain relationship information between the signal samples is not fully utilized, and the performance is limited.

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  • A radar target detection method and system based on graph data and gcn
  • A radar target detection method and system based on graph data and gcn
  • A radar target detection method and system based on graph data and gcn

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Embodiment Construction

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0052] In recent years, graph data processing has attracted attention. Graph Neural Networks (GNN) can realize information transfer between adjacent graph data nodes, and has been widely used in text classification, relationship extraction and image classification. At present, GNN application scenarios mainly include molecular chemistry, computer networks, social networks, etc. In such application scenarios, the data itself has an explicit graph structure. Graph...

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Abstract

The invention relates to a radar target detection method and system based on graph data and GCN. The method includes: acquiring radar echo data of a target; dividing the radar echo data according to a time series to obtain a multi-segment signal node sequence; taking a modulo of each signal node sequence to obtain a node feature of each signal node sequence; The node feature is the amplitude information corresponding to the signal node sequence; an adjacency matrix is ​​constructed according to the node feature of each signal node sequence to obtain signal graph data; the nodes of the adjacency matrix are the signal node sequence, and the signal graph data includes Adjacency matrix and node features of each node; input the signal graph data into the graph convolution network, and output the classification result corresponding to each node in the graph convolution network; the classification result of each node is the target signal or clutter Signal. The present invention can improve the performance of target detection.

Description

technical field [0001] The invention relates to the field of radar signal processing, in particular to a radar target detection method and system based on graph data and GCN. Background technique [0002] Target detection is widely used in military and civilian fields. Radar is an important means of target detection and surveillance. However, due to the influence of clutter generated in complex environments and the diversity of target types, reliable and robust target detection always needs to be studied. One of the key technologies. In recent years, deep learning technology has developed rapidly and has been widely used in the field of signal processing. The deep learning method not only has the function of feature extraction, but also has a strong generalization ability, which provides a new way for target detection. In the field of radar signal processing, deep learning methods have been widely used in the processing of SAR images, Doppler radar signals, and high-resolu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S17/89
CPCG01S17/89G01S17/02
Inventor 陈小龙苏宁远关键宋杰张财生薛永华
Owner NAVAL AVIATION UNIV
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