Unmanned aerial vehicle information monitoring method based on generalized tensor compression

A technology for information monitoring and unmanned aerial vehicles, applied in radio transmission systems, complex mathematical operations, electrical components, etc.

Inactive Publication Date: 2021-09-10
NORTH CHINA UNIVERSITY OF TECHNOLOGY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a kind of UAV information monitoring method based on generalized tensor compression, t

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  • Unmanned aerial vehicle information monitoring method based on generalized tensor compression
  • Unmanned aerial vehicle information monitoring method based on generalized tensor compression
  • Unmanned aerial vehicle information monitoring method based on generalized tensor compression

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[0015] The present invention will be described in detail below in conjunction with the implementations shown in the drawings, but it should be noted that these implementations are not limitations of the present invention, and those of ordinary skill in the art based on the functions, methods, or structural changes made by these implementations Equivalent transformations or substitutions all fall within the protection scope of the present invention.

[0016] The present embodiment provides a method for monitoring UAV information based on generalized tensor compression, comprising the following steps:

[0017] Step 1, randomly initialize the signal matrix and channel matrix;

[0018] Step 2, calculate the least squares estimation of the Khatri-Rao product;

[0019] Step 3, use the Khatri-Rao product inverse operation to calculate the signal matrix;

[0020] Step 4, calculate the channel matrix H according to tensor generalized expansion and Khatri-Rao inverse operation 1 ;

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Abstract

The invention discloses an unmanned aerial vehicle information monitoring method based on generalized tensor compression. The method comprises the following steps of 1, performing random initialization on a signal matrix and a channel matrix acquired by an unmanned aerial vehicle; 2, calculating least square method estimation of the Khatri-Rao product of the signal matrix and the coding matrix; 3, calculating a signal matrix by using inverse operation of the Khatri-Rao product; 4, solving a use-to-base-station channel matrix by using generalized expansion of the tensor of the received signal of the unmanned aerial vehicle and Khatri-Rao product inverse operation; 5, calculating least square method estimation of a channel matrix from the base station to the unmanned aerial vehicle; and 6, repeating the previous steps until the convergence condition is met, wherein the difference of the absolute values of the iterated cost function is smaller than the minimum value. According to the unmanned aerial vehicle information monitoring method based on generalized tensor compression, the use of a training sequence is effectively avoided, accurate information can be obtained, the convergence speed is high, and prior information is not needed.

Description

technical field [0001] The invention belongs to the field of information monitoring, and in particular relates to a method for monitoring information of an unmanned aerial vehicle based on generalized tensor compression. Background technique [0002] The application of information technology is playing an increasingly important role in the modern military field. As one of the key technologies of modern wireless communication, UAV plays an important role in military conflicts, especially in harsh battlefield environments. UAVs need to obtain information at high altitudes and complete massive image, video, remote sensing measurement data and other intelligence transmission tasks. It is very important to obtain accurate information in this process. Some information acquisition methods have been used to monitor information, such as time-varying Signal acquisition in fading channels requires training sequences, and semi-blind signal estimation algorithms require prior information...

Claims

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Application Information

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IPC IPC(8): H04B7/185G06F17/16
CPCH04B7/18506G06F17/16
Inventor 韩曦师嘉晨刘芹虞欣王立军
Owner NORTH CHINA UNIVERSITY OF TECHNOLOGY
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