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GNSS receiver combined interference classification and identification method based on two-stage neural network

A technology of combined interference and neural network, applied in the field of classification and identification of combined interference of GNSS receivers

Active Publication Date: 2020-07-10
XI AN JIAOTONG UNIV
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  • Application Information

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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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  • GNSS receiver combined interference classification and identification method based on two-stage neural network
  • GNSS receiver combined interference classification and identification method based on two-stage neural network
  • GNSS receiver combined interference classification and identification method based on two-stage neural network

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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 that considers suppressive and deceptive jamming at the same time in the existing work, in order to illustrate the effectiveness of th...

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Abstract

The invention discloses a GNSS receiver combined interference classification and identification method based on a two-stage neural network. A receiver receives navigation signals sent by N visible satellites; according to a received GNSS signal model and interference source, a two-stage identification scheme based on a BP neural network is adopted to extract time domain and frequency domain characteristics of a digital intermediate frequency signal after A / D conversion through a first-stage identification module, and the time domain and frequency domain characteristics are sent to the BP neural network for suppressing interference detection and classification; if an identification result of the first-stage recognition module is that there is no interference or deception jamming, the digital intermediate frequency signal is captured, related peak characteristics are extracted by using a captured two-dimensional search matrix, and the related peak characteristics are sent to the second-stage recognition module for deception jamming detection; and when a final identification result of the two stages of identification modules is that there is no interference, it is determined that thereceived signal is a real satellite signal, and after the interference type is identified, a corresponding interference processing means is adopted. The method can be used to 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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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
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