Expected trajectory signal attack detection method based on multi-feature fusion

Abstract

The invention relates to an expected trajectory signal attack detection method based on multi-feature fusion, and aims to solve the problem that an expected trajectory signal sent to an unmanned aerial vehicle by a ground control station is attacked and detected by false information injection in the transmission process. The method comprises: first, designing virtual unmanned aerial vehicle systemmodel containing nominal signals; secondly, designing a nominal signal observer, and estimating a nominal signal in the virtual unmanned aerial vehicle system; thirdly, calculating expected track signal power received by a receiving end of the unmanned aerial vehicle, and comparing the expected track signal power with a power threshold value; and finally, designing an expected trajectory signal attack detection mechanism based on multi-feature fusion according to the power of the received expected trajectory signal and the nominal signal estimation error. The method has the characteristics ofhigh attack detection accuracy and low false alarm rate, and is suitable for attack detection of an attacked unmanned aerial vehicle system in a process of transmitting an expected track signal through a direct sequence spread spectrum communication technology.

Description

technical field [0001] The invention relates to an attack detection method of an expected trajectory signal based on multi-feature fusion, which can realize the attack detection that the expected trajectory signal is attacked by false information injection during the transmission process. Background technique [0002] In recent years, as drones have played an increasingly important role in the military and civilian fields, attacks against drone systems have also occurred frequently. Due to the open communication mechanism of the UAV system, the UAV is vulnerable to malicious attacks during the communication process with the ground control station, satellite navigation system and other cooperative UAVs. Attacks on UAV communication are generally divided into two types: one is attacks on information availability, such as denial of service attacks; the other is attacks on information integrity, such as spoofing attacks, replay attacks, etc. When responding to an attack, the fi...

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Problems solved by technology

However, the above patents all use the residual between the predicted value and the real value as the criterion for attack detection, but factors other than GPS spoofing attacks will also lead to an increase in the error between the predicted value and the real value

At the same time, the above-mentioned patents are all aimed at detecting the GPS spoofing attack of the UAV system, without considering the situation that the expected trajectory signal is attacked during the transmission process

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