Multi-level identification detection system and method for GNSS interference signals

Abstract

The invention discloses a multi-level identification detection system for GNSS interference signals. The system comprises a radio frequency front-end module, a first-level detector, an acquiring and processing module, a second-level detector, a multi-channel tracking and processing module, a third-level detector, an interference determination module and a positioning and resolving module. The output ends of the first-level detector, the second-level detector and the third-level detector are respectively connected with the interference determination module. The invention further discloses a multi-level identification detection method for GNSS interference signals. Based on the system or the method, the influence characteristics of different interference signals on each link of the signal processing procedure of a receiver can be comprehensively analyzed, and interference feature parameters are extracted. The detection algorithm of each link is optimized and the detection accuracy is improved. Meanwhile, the detection is synchronously done during the received signal processing step, the baseband signal capturing step and the tracking step of a radio frequency front end. As a result, the real-time property, the rapidness and the low cost of the interference detection can be ensured.

Description

technical field [0001] The invention belongs to the field of GNSS interference signal detection, in particular to a multi-stage identification and detection system and method for GNSS interference signals. Background technique [0002] The rapid development of the Internet of Things and smart devices has prompted people to put forward higher requirements for the reliability of positioning and navigation technology. Global Navigation Satellite System (GNSS), as a positioning system widely used in daily life, its reliability is affected by many factors. The satellite signal propagates to the ground after a distance of more than 20,000 kilometers, and the power is only -130dBm, which is easily subject to various intentional or unintentional interference. These interferences are further divided into two categories: spoofing interference and suppression interference. Deceptive jamming is to transmit jamming signals similar to satellite signals to deceive the receiver, so that t...

AI Technical Summary

Problems solved by technology

Deceptive jamming is to transmit jamming signals similar to satellite signals to deceive the receiver, so that the receiver can solve the wrong positioning information; while suppressing jamming is to use high-power in-band noise, continuous wave, sweep wave and other jamming signals Suppresses satellite signals, making GNSS receivers unable to work properly

[0003] In GNSS interference detection, the energy detection method and the output of the front-end AGC module are mainly used to detect the existence of interference, but the type of interference cannot be detected; the improved DFT algorithm is also used to detect narrow-band interference, but the detection is only applicable It is used for narrowband interference; the method of multi-correlator can be used to monitor the signal quality, but the cause of signal abnormality has not been realized

[0004] The automatic interference detection based on the output power of the correlator, carrier phase fluctuation, pseudo-range change and other parameters can detect Gaussian white noise, continuous wave, pulse wave and other interference, but the parameters required for detection are in the signal tracking part, which is subject to capture The limitation of the success rate requires further research on the realization of the detection work

[0005] In general, a large number of interference detection technologies currently have a relatively single scope of use. In the detection of different types of suppressive interference and deception interference, the comprehensiveness is still insufficient, and the identification and detection of various interferences cannot be realized.

The ultimate goal of interference detection is to suppress interference, but at present, a large number of interference suppression algorithms only have a good suppression effect on one or several kinds of interference, and cannot suppress all kinds of interference well. It is difficult to suppress the interference accurately and comprehensively

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