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Unmanned aerial vehicle signal extraction and identification method and system

A signal extraction and identification method technology, applied in the field of UAV signal detection and identification, can solve the problems of difficult identification, high overlap with Wifi signal frequency band, etc., and achieve the effect of low cost and strong concealment

Pending Publication Date: 2021-07-30
长沙泰聘信息科技有限公司
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Problems solved by technology

[0007] Aiming at the problems existing in the prior art, the present invention provides a UAV signal extraction and recognition method and system, especially relates to a UAV signal extraction and recognition method and system based on signal frequency domain characteristics, aiming to solve the current The UAV transmission signal frequency band highly overlaps with the Wifi signal frequency band, making it difficult to identify the problem

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  • Unmanned aerial vehicle signal extraction and identification method and system
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Embodiment 1

[0103] In order to solve the problem that the UAV transmission signal frequency band and the Wifi signal frequency band are highly overlapped and difficult to identify, this paper proposes a UAV signal extraction and identification method based on signal frequency domain characteristics. Perform passive detection and identification. First, based on the difference between the UAV image transmission signal and other interfering signal intermediate frequency characteristics, the envelope detection and envelope extraction are performed on the intermediate frequency signal, and then the fast Fourier transform is performed to extract the intermediate frequency characteristics of each pulse signal; then the extracted Based on the improved fuzzy C-means clustering of the intermediate frequency characteristic signals, the outlier processing is performed on each cluster signal based on the Euclidean distance, and the interfering spurious signals are eliminated.

[0104] The present inve...

Embodiment 2

[0113] The invention is based on the characteristics of the intrapulse intermediate frequency frequency domain, and uses methods such as data clustering and outlier processing to realize the detection, feature extraction and target recognition of the UAV signal. The actual measurement data test shows that the present invention can not only identify drones of different brands and types in the same series (DJI series), but also identify drones of different series (DJI and Xiaomi series). In the absence of any prior information, a relatively "pure" UAV pulse signal is extracted to provide a basis for subsequent modulation signal parameter estimation. It mainly includes the following contents:

[0114] (1) UAV pulse signal envelope detection (see Figure 4 )

[0115] Pulse signal envelope detection is based on the algorithm that the signal amplitude is greater than the noise amplitude, the envelope is extracted, and the corresponding threshold is set to distinguish the signal fr...

Embodiment 3

[0146] In order to verify the feasibility and reliability of the present invention in practical engineering applications, HackRF equipment is selected to collect UAV transmission signals. The sampling rate of the equipment is 20MHZ, and the bandwidth can cover the frequency range of 2.4GHZ and 5.8GHZ of current drones. In order to increase the contrast of the experiment, in the field test, DJI series "Xiao" UAV (2), "Yu" UAV (1), "Phantom 3S" UAV (2), A certain type of drone (1) and Xiaomi series drones (2) were tested. The measured results are as follows:

[0147] (1) The identification test of the same type (DJI series) UAV based on the frequency domain characteristics of pulse intermediate frequency

[0148] The purpose of the experiment: to test the recognition effect of the present invention on the "DJI" series of unmanned aerial vehicles in the field test.

[0149] Field measurement data: DJI series "Xiao" UAV (2), "Yu" UAV (1), "Phantom 3S" UAV (2), a certain type of...

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Abstract

The invention belongs to the technical field of unmanned aerial vehicle signal detection and identification, and discloses an unmanned aerial vehicle signal extraction and identification method and system. The unmanned aerial vehicle signal extraction and identification method comprises the following steps: firstly, performing envelope detection and envelope extraction on an intermediate frequency signal based on the difference between the intermediate frequency characteristics of an unmanned aerial vehicle image transmission signal and other interference signals; secondly, carrying out fast Fourier transform processing and extracting the intermediate frequency features of each pulse signal; and then, carrying out improved fuzzy C-means clustering on the extracted intermediate frequency characteristic signals, carrying out outlier removal processing on each cluster of signals based on Euclidean distance, and removing the interfering spurious signals. According to the unmanned aerial vehicle signal extraction and identification method provided by the invention, the intermediate frequency signal characteristics of the unmanned aerial vehicle are extracted by adopting data averaging, and a high-quality pulse signal is provided for subsequent parameter estimation. Actual measurement data tests prove that the method has obvious effects of extracting, separating and identifying unmanned aerial vehicle signals in a complex electromagnetic environment, and has relatively strong practical engineering application capability.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicle signal detection and identification, and in particular relates to a method and system for unmanned aerial vehicle signal extraction and identification. Background technique [0002] At present, with the rapid development of drone technology and the popularization of domestic drones, while drones bring convenience to the people, accidents related to them frequently appear in people's vision. At home and abroad, there are phenomena of using drones to carry out criminal activities. The "black flying" drone has aroused concern and concern from all walks of life, and the need for effective control of it is very urgent. [0003] In the face of "black flying" drones, it is not only necessary to set norms and formulate policies to "not allow them to fly", but also to study countermeasures at the technical level to achieve "dare not to fly". The premise and key to countering UAVs is to ac...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06F2218/00G06F2218/04G06F2218/08G06F18/23213
Inventor 朱守中李明刘洪雷刘思意
Owner 长沙泰聘信息科技有限公司