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A Classification and Recognition Method of GNSS Receiver Combination Interference Based on Two-level Neural Network

A technology of classification identification and combined interference, applied in the field of signal processing, to achieve good results, fast and accurate identification

Active Publication Date: 2022-06-07
XI AN JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, suppressive and deceptive interference will alternate in the same scene, and may switch randomly

Method used

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  • A Classification and Recognition Method of GNSS Receiver Combination Interference Based on Two-level Neural Network
  • A Classification and Recognition Method of GNSS Receiver Combination Interference Based on Two-level Neural Network
  • A Classification and Recognition Method of GNSS Receiver Combination Interference Based on Two-level Neural Network

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Experimental program
Comparison scheme
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Embodiment

[0132] Consider scenarios where both oppressive and deceptive jamming exist, such as figure 1 shown. In the simulation experiment, using the simulated intermediate frequency data of GPSL1 frequency point and BDS B1 frequency point, the receiver can receive signals from 6 to 8 visible satellites, the receiving signal-to-noise ratio is -20dB, and the sampling frequency is 10.23MHz. The number of satellites is 2 to 4, the pseudo-code phase difference between the multipath signal and the direct signal is 0.1 to 1 chip, and the Doppler frequency shift difference with the direct signal is ±100Hz. Other related simulation parameters are shown in Table 4.

[0133] The detailed simulation parameters are shown in Table 1.

[0134] Table 4 Simulation parameters

[0135]

[0136]

[0137] Comparison scheme:

[0138] Since there is no unified scheme considering both suppressive and deceptive jamming in the existing work, in order to illustrate the effectiveness of the proposed sche...

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Abstract

The invention discloses a GNSS receiver combined interference classification and identification method based on a two-level neural network. The receiver receives navigation signals sent by N visible satellites, and adopts a method based on BP neural network according to the received GNSS signal model and interference source. The two-level identification scheme uses the first-level identification module to extract the time-domain and frequency-domain features of the digital intermediate frequency signal after A / D conversion, and sends it to the BP neural network for suppressive interference detection and classification; if the first-level identification module identifies When the result is no interference or there is deception interference, then capture the digital intermediate frequency signal, use the captured two-dimensional search matrix to extract the correlation peak features, and send it to the second-level identification module for deception interference detection; when the two-level identification module finally identifies When the result is no interference, it is determined that the received signal is a real satellite signal, and when the type of interference is identified, corresponding interference processing measures are taken. The invention can quickly and accurately identify interference.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a method for classifying and identifying GNSS receiver combined interference based on a two-stage neural network. Background technique [0002] Global Navigation Satellite System (GNSS) is a wide-coverage, all-weather, real-time, high-precision navigation system. With the continuous development of satellite navigation technology, GNSS has been widely used in various military and civilian fields. GNSS mainly includes the Global Positioning System (GPS) of the United States, Galileo (GALILEO) of the European Union, GLONASS of Russia, and the Beidou Navigation Satellite System (BDS) of my country. Due to its wide application and large influence, it is particularly important to ensure the safety of the global satellite navigation system. Because navigation satellites are generally far away from the earth's surface, when the navigation signals transmitted by sa...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S19/21G06K9/00G06N3/04G06N3/08
CPCG01S19/21G06N3/08G06N3/045G06F2218/12
Inventor 张国梅张欣李国兵贾小林马小辉
Owner XI AN JIAOTONG UNIV