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A flexible networking method for shortwave direction finding based on deep learning

A technology of deep learning and flexible grouping, applied in the field of flexible networking of shortwave direction finding based on deep learning, can solve the problems of missing and out of control of important signals, poor measurement, lack of objective scientificity, etc., to improve accuracy and timeliness, and evenly The effect of low square root error and improving generalization performance

Active Publication Date: 2021-12-10
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] 1. The direction finding method of the whole network wastes resources and increases the task load of sites with poor direction indication quality, resulting in low completion rate of direction finding tasks and loss of important signals out of control
[0005] 2. The short-wave propagation channel is complex and time-varying. When multiple target signals are concurrent, and the number of direction-finding stations is large and widely distributed, manual assignment and selection of stations is time-consuming and laborious, lacking objective scientificity, and may cause poor and inaccurate measurements

Method used

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  • A flexible networking method for shortwave direction finding based on deep learning
  • A flexible networking method for shortwave direction finding based on deep learning
  • A flexible networking method for shortwave direction finding based on deep learning

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Experimental program
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Effect test

Embodiment 1

[0036] Such as figure 1 As shown, a flexible networking method for shortwave direction finding based on deep learning includes the following steps:

[0037] Step S101: Establishing a shortwave direction finding database for storing shortwave direction finding historical data, said shortwave direction finding historical data including direction finding quality and direction finding station selection networking scheme;

[0038] Step S102: Preprocessing the historical shortwave direction finding data in the shortwave direction finding database;

[0039] The step S102 is specifically:

[0040] The data preprocessing method based on fuzzy mathematics is used to preprocess the historical shortwave direction finding data in the shortwave direction finding database.

[0041] Step S103: Based on the historical short-wave direction-finding data after data preprocessing, for each target radiation source signal, an effective prediction of the site direction-finding quality based on the ...

Embodiment 2

[0061] Such as figure 2 As shown, another flexible networking method for shortwave direction finding based on deep learning includes:

[0062] Step S201: Establish a shortwave direction finding database for storing shortwave direction finding historical data; the shortwave direction finding historical data consists of the characteristic parameters of the radiation source signal, direction finding time, direction finding station, direction finding quality and direction finding station selection network The composition of the scheme, the quality of direction finding is measured by the deviation degree of direction indication, and the network scheme of direction finding station selection specifically refers to the combination of shortwave lateral station selection.

[0063] Step S202: Preprocessing the historical shortwave direction finding data in the shortwave direction finding database.

[0064] Specifically, the present invention adopts a preprocessing method based on fuzzy...

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Abstract

The invention relates to the technical field of shortwave network direction finding, and discloses a flexible networking method for shortwave direction finding based on deep learning. The invention establishes a DBN neural network model for high-precision training on shortwave direction-finding sample data sets, and learns ionospheric propagation characteristics and flexible networking behavior rules for station selection from historical direction-finding data, thereby realizing direction-finding and selection of radiation source signals. The fast and accurate prediction and recommendation of the station networking scheme not only improves the scientific and intelligent level of shortwave direction finding, but also enables comprehensive utilization, dynamic configuration, and collaborative sharing of direction finding resources, improving the direction finding of flexible networking of shortwave direction finding stations efficacy.

Description

technical field [0001] The invention relates to the technical field of shortwave network direction finding, in particular to a flexible networking method for shortwave direction finding based on deep learning. Background technique [0002] Shortwave direction finding and positioning is an important means of shortwave signal monitoring. At present, the short wave mainly adopts AOA (Angle of Arrival) passive direction-finding positioning technology, that is, the direction-finding station does not actively transmit signals, but uses an array antenna to estimate the direction of arrival of the target radiation source signal for positioning. An AOA measurement value can determine an angular direction of the target radiation source, and if there are at least two effective measurements at different locations, the position of the radiation source can be determined by the intersection of orientation lines at multiple angles. Therefore, it is very important to select a suitable netwo...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W84/18G06N3/08G01S3/14
Inventor 张静沈明冉晓旻孙桂斌徐峥张力佳江建军王雯霞李崇傅敏
Owner PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU