CN110646814A - Unmanned aerial vehicle deception method under combined navigation mode - Google Patents

Unmanned aerial vehicle deception method under combined navigation mode Download PDF

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Publication number
CN110646814A
CN110646814A CN201910870942.8A CN201910870942A CN110646814A CN 110646814 A CN110646814 A CN 110646814A CN 201910870942 A CN201910870942 A CN 201910870942A CN 110646814 A CN110646814 A CN 110646814A
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unmanned aerial
aerial vehicle
information
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navigation mode
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唐康华
郭妍
吴美平
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National University of Defense Technology
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/21—Interference related issues ; Issues related to cross-correlation, spoofing or other methods of denial of service

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Abstract

An unmanned aerial vehicle deception method under a combined navigation mode comprises the following steps: step S1: the attacker utilizes the third-party measuring equipment to observe and estimate the flight state information of the unmanned aerial vehicle, including the position of the unmanned aerial vehicle
Figure DDA0002202787260000011
Speed of rotation
Figure DDA0002202787260000012
And acceleration
Figure DDA0002202787260000013
Information; step S2: based on estimated flight status information
Figure DDA0002202787260000014
The attacker calculates a deception trajectory forcing the unmanned aerial vehicle to track by adopting a PID control algorithm
Figure DDA0002202787260000015
Control input amount a ofs(ii) a Step S3: the information of the estimated flight state of the unmanned aerial vehicle obtained in step S1 is combined
Figure DDA0002202787260000016
And the spoofed control input amount a acquired in step S2sAnd the attack party calculates and obtains the acceleration component a of the false satellite signal*(ii) a Step S4: the attacker obtains the position x of the false satellite signal at each moment through integral operation*And velocity v*And (4) information. The invention has the advantages of easy realization, wide application range, high control precision and the like.

Description

Unmanned aerial vehicle deception method under combined navigation mode
Technical Field
The invention mainly relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle deception method under a combined navigation mode.
Background
With the progress of scientific technology and the rapid development of economy, as the unmanned aerial vehicle has unique advantages in the aspects of persistence, maneuverability, life risk reduction and the like, the unmanned aerial vehicle is widely applied in various industries, some unmanned aerial vehicles belong to normal application, some unmanned aerial vehicles belong to abnormal application, and the anti-unmanned aerial vehicle technology under some application environments is also divided into normal application and abnormal application. Some interference techniques can suppress the unmanned aerial vehicle under normal application, thereby influencing normal application. For example relating to security issues. Covert spoofing means that the unmanned plane tracks a spoofing track after receiving a false GPS signal although in its real flight state.
The integrated Navigation of the Global Positioning System (GPS)/Inertial Navigation System (INS) is one of the core technologies of the Navigation, guidance and control of the unmanned aerial vehicle System. However, because the navigation satellite signal is very weak, the unmanned aerial vehicle GPS/INS integrated navigation system using the satellite navigation terminal is easily subjected to malicious interference such as suppression interference or deception interference.
Different from suppression type interference, the power level, the signal format and the frequency spectrum structure of the deception jamming signal are similar to those of a real satellite signal, and the purpose is to force a receiver to be locked on the deception jamming signal without consciousness, so that a seemingly reliable and true and false navigation positioning result is generated, and the purpose of the satellite receiver is further achieved. The receiver often does not perceive the deceptive interference when the deceptive interference is received, so the deceptive interference is more serious than the compressive interference.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems in the prior art, the invention provides the unmanned aerial vehicle deception method under the combined navigation mode, which is easy to realize, wide in application range and high in control precision.
In order to solve the technical problems, the invention adopts the following technical scheme:
an unmanned aerial vehicle deception method under a combined navigation mode comprises the following steps:
step S1: the attacker utilizes the third-party measuring equipment to observe and estimate the flight state information of the unmanned aerial vehicle, including the position of the unmanned aerial vehicle
Figure BDA0002202787240000011
Speed of rotation
Figure BDA0002202787240000012
And accelerationInformation;
step S2: based on estimated flight status information
Figure BDA0002202787240000021
The attacker calculates a deception trajectory forcing the unmanned aerial vehicle to track by adopting a PID control algorithm
Figure BDA0002202787240000022
Control input amount a ofs；
Step S3: the information of the estimated flight state of the unmanned aerial vehicle obtained in step S1 is combined
Figure BDA0002202787240000023
And the spoofed control input amount a acquired in step S2sAnd the attack party calculates and obtains the acceleration component a of the false satellite signal*；
Step S4: the attacker obtains the position x of the false satellite signal at each moment through integral operation*And velocity v*And (4) information.
As a further improvement of the invention: in said step S1, a linear estimator is employed, namely:
wherein A iseIs a state observer system matrix, and:
Figure BDA0002202787240000025
Lsfor the steady state gain matrix of the estimator, the following equations can be used:
AePs+PsAe+Qs-PsCT(Rs)-1CPs＝0
and solving to obtain the following result:
Ls＝PsCT(Rs)-1
Qsand RsAnd respectively estimating a system noise matrix and an observation noise matrix of the flight state of the unmanned aerial vehicle for the linear estimator of the attack party.
As a further improvement of the invention: in the step S2, the attacker aims to make the unmanned aerial vehicle track the deception trajectory
Figure BDA0002202787240000026
Calculating the control input quantity a by adopting a PID control algorithmsComprises the following steps:
wherein the content of the first and second substances,
Figure BDA0002202787240000028
the parameter matrix is controlled for spoofing.
As a further improvement of the invention: in the step S3, the estimated flight state information of the unmanned aerial vehicle obtained in the step S1 is combinedStep (a) and (b)The spoof control input amount a acquired in step S2sThe attacker adopts the acceleration component a of the false satellite signal*Namely:
Figure BDA0002202787240000031
as a further improvement of the invention: in step S4, the attacker obtains the position x of the false satellite signal at each time by means of integration*And velocity v*Information, i.e.
Figure BDA0002202787240000032
Compared with the prior art, the invention has the advantages that:
1. the unmanned aerial vehicle deception method under the combined navigation mode not only provides a complete combat scheme for capturing the unmanned aerial vehicle by using the false satellite signal for an attacker, but also provides a theoretical basis and a technical route for detecting or inhibiting the deception jamming technology for a defender. Meanwhile, the cheating method provided by the invention can be popularized to other unmanned aerial vehicle systems (unmanned vehicles, unmanned ships and the like), and has higher application value.
2. The unmanned aerial vehicle deception method under the combined navigation mode comprehensively considers an unmanned aerial vehicle system comprising a GPS/INS combined navigation and flight control closed loop feedback loop, and designs and constructs false satellite signals at all moments by combining all possible acquired unmanned aerial vehicle flight state information so as to realize the unconscious position deception offset of the unmanned aerial vehicle.
3. The invention discloses an unmanned aerial vehicle deception method under a combined navigation mode, which comprises the steps of firstly constructing an unmanned aerial vehicle system model containing a GPS/INS combined navigation and flight control closed-loop feedback loop, then combining with third-party measuring equipment to observe estimated unmanned aerial vehicle flight state information, deception track information planned by an attacker and predicted unmanned aerial vehicle flight tracking control information to obtain acceleration component information of a false satellite signal in real time, and obtaining the false satellite signal at each moment through integral operation to realize that the unmanned aerial vehicle unconsciously deviates from a self originally planned reference track and slowly approaches to the deception track planned by the attacker.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention.
Fig. 2 is a schematic diagram of the principle of the invention in a specific application example.
Detailed Description
The invention will be described in further detail below with reference to the drawings and specific examples.
As shown in fig. 1 and fig. 2, the method for spoofing an unmanned aerial vehicle in a combined navigation mode of the invention comprises the following steps:
step S1: the attacker utilizes the third-party measuring equipment (such as ground radar and the like) to observe and estimate the flight state information of the unmanned aerial vehicle, including the position of the unmanned aerial vehicle
Figure BDA0002202787240000041
Speed of rotation
Figure BDA0002202787240000042
And acceleration
Figure BDA0002202787240000043
Information;
step S2: based on estimated flight status information
Figure BDA0002202787240000044
The attacker calculates a deception trajectory forcing the unmanned aerial vehicle to track by adopting a PID control algorithm
Figure BDA0002202787240000045
Control input amount a ofs；
Step S3: the information of the estimated flight state of the unmanned aerial vehicle obtained in step S1 is combined
Figure BDA0002202787240000046
And the spoofed control input amount a acquired in step S2sAnd the attack party calculates and obtains the acceleration component a of the false satellite signal*；
Step S4: the attacker obtains the position x of the false satellite signal at each moment through integral operation*And velocity v*And (4) information.
In a specific embodiment of the invention, the position, velocity and acceleration of the drone may be described by the following integral equations:
wherein the content of the first and second substances,
x＝[rx ry rz vx vy vz]T，a＝[ax ay az]T，
Figure BDA0002202787240000048
while specifying the original reference trajectory planned in advance by the drone
Figure BDA0002202787240000049
And cheating trajectories planned by the attackerAlso satisfies:
Figure BDA00022027872400000411
in a specific embodiment, in step S1, the present invention employs a linear estimator, i.e., a linear estimator
Figure BDA00022027872400000412
Wherein A iseIs a state observer system matrix, and:
Lsfor the steady state gain matrix of the estimator, the following equations can be used:
AePs+PsAe+Qs-PsCT(Rs)-1CPs＝0
and solving to obtain the following result:
Ls＝PsCT(Rs)-1
Qsand RsRespectively estimating a system noise matrix and an observation noise matrix of the flight state of the unmanned aerial vehicle for an attack side linear estimator, wherein the specific forms are as follows:
Figure BDA0002202787240000052
Figure BDA0002202787240000053
Figure BDA0002202787240000054
Figure BDA0002202787240000055
Figure BDA0002202787240000056
and
Figure BDA0002202787240000057
the measured noise variance of X, Y and Z-axis acceleration are estimated separately for the aggressor linear estimator,
Figure BDA0002202787240000058
and
Figure BDA0002202787240000059
the positional errors of X, Y and the Z-axis are observed separately for the aggressor linear estimator,
Figure BDA00022027872400000510
Figure BDA00022027872400000511
and
Figure BDA00022027872400000512
velocity errors are observed X, Y and the Z-axis for the aggressor linear estimator, respectively.
In a specific embodiment, in step S2, the attacker of the present invention aims to make the drone track the deception trajectoryCalculating the control input quantity a by adopting a PID control algorithmsComprises the following steps:
Figure BDA00022027872400000514
wherein the content of the first and second substances,
Figure BDA00022027872400000515
the parameter matrix is controlled for spoofing.
In the specific embodiment, in step S3, the invention combines the estimated flight status information of the drone obtained in step S1And the spoofed control input amount a acquired in step S2sThe attacker designs the acceleration component a of the false satellite signal as shown below*Namely:
Figure BDA0002202787240000062
in the specific embodiment, in step S4, the attacker obtains the position x of the false satellite signal at each time by integral calculation*And velocity v*Information, i.e.
Figure BDA0002202787240000063
And simulating a navigation positioning result after the unmanned aerial vehicle receives the false satellite signal.
The unmanned aerial vehicle utilizes a linear filter to fuse the received false satellite signal and flight state information measured by an inertial device of the unmanned aerial vehicle, and the following results can be obtained:
Figure BDA0002202787240000064
wherein the content of the first and second substances,
Figure BDA0002202787240000065
and
Figure BDA0002202787240000066
respectively as the state estimation value of the unmanned aerial vehicle and the constant zero-bias estimation value of the inertial device, L is the Kalman filtering steady-state gain of the unmanned aerial vehicle, and can also be calculated by using a continuous algebra Riccati equation, amAcceleration components of the drone obtained for actual measurement of inertial devices, i.e.
am＝a-b
b is the constant zero offset of the accelerometer in the inertial device.
The flight controller on the unmanned aerial vehicle calculates the flight control input quantity by comparing the difference value between the filtering estimation state and the target state point on the original reference track and utilizing a PID control algorithm:
Figure BDA0002202787240000067
wherein, K ═ Kp Kd]>And 0 is an unmanned aerial vehicle control parameter matrix.
The spatial relationships between the six key points and their associated vectors in a particular spoofing process. After receiving the false satellite signal, the unmanned aerial vehicle determines that the unmanned aerial vehicle is in another position point by mistake due to the result output by the self inertia/satellite combined navigation filtering
Figure BDA0002202787240000068
Rather than its true position x. At this time, the drone generates a control input a to make it approach the target point on the original reference trajectoryHowever, when the control input effect is applied in the real state, no one has a chance to track the target point on the spoofed trajectory
Figure BDA00022027872400000610
I.e. has deviated from the original reference trajectory and slowly approached the spoofed trajectory.
The concealment of the spoofing algorithm will be theoretically verified below.
Substituting formula (5) into formula (4) can yield:
Figure BDA0002202787240000071
the derivation of the above formula can be obtained:
further solving according to equation (2) can result in:
Figure BDA0002202787240000073
according to the formula (8), a
Figure BDA0002202787240000074
Comparing equation (11) and equation (12), we can obtain:
Figure BDA0002202787240000075
wherein, gamma (K)s)＝[(Ks)TKs]-1(Ks)T。
According to the formula (3), a
Figure BDA0002202787240000076
And
Figure BDA0002202787240000077
wherein the content of the first and second substances,
Figure BDA0002202787240000078
from equations (14) and (15), equation (13) can be further solved to obtain:
Figure BDA0002202787240000081
due to the fact that
Figure BDA0002202787240000082
And
Figure BDA0002202787240000083
is an estimated value of the real flight state of the unmanned aerial vehicle, so the following equation holds:
Figure BDA0002202787240000084
meanwhile, the false satellite signal is a low-frequency signal, then the false satellite signal exists
Figure BDA0002202787240000085
Substituting the above setting conditions into equation (16) can be further simplified as follows:
namely, when the initial real flight state of the unmanned aerial vehicle is the same as the initial state of the deception trajectory of the attacker, the unmanned aerial vehicle can track the target point on the deception trajectory, namely, the purpose of deception position deviation is achieved, and therefore the effectiveness of the deception algorithm is verified.
By performing a derivation operation on equation (8), it is possible to obtain:
Figure BDA0002202787240000087
further solving, can obtain
When the flight state of the unmanned aerial vehicle is stable, the acceleration generated by the controller is approximately constant, namely
Figure BDA0002202787240000089
That is, when the initial estimation state of the drone filter is the same as the initial state of the reference trajectory, the drone combined navigation filter output always surrounds the original reference trajectory.
Covert spoofing means that after receiving false GPS information, although the drone tracks a spoofed trajectory in its real flight state, its combined navigation output is still close to the reference trajectory. Combining equation (18) and equation (20) can result in covert spoofing of the drone by introducing false GPS signals as described by equations (5) and (6). And (5) finishing the certification.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.

Claims (5)

1. An unmanned aerial vehicle deception method under a combined navigation mode is characterized by comprising the following steps:
step S1: the attacker utilizes the third-party measuring equipment to observe and estimate the flight state information of the unmanned aerial vehicle, including the position of the unmanned aerial vehicle
Figure FDA0002202787230000011
Speed of rotation
Figure FDA0002202787230000012
And acceleration
Figure FDA0002202787230000013
Information;
step S2: based on estimated flight status information
Figure FDA0002202787230000014
The attacker calculates a deception trajectory forcing the unmanned aerial vehicle to track by adopting a PID control algorithm
Figure FDA0002202787230000015
Control input amount a ofs；
Step S3: the information of the estimated flight state of the unmanned aerial vehicle obtained in step S1 is combinedAnd the spoofed control input amount a acquired in step S2sAnd the attack party calculates and obtains the acceleration component a of the false satellite signal*；
Step S4: the attacker obtains the position x of the false satellite signal at each moment through integral operation*And velocity v*And (4) information.
2. Method of drone spoofing in combined navigation mode according to claim 1, characterised in that in said step S1 a linear estimator is used, namely:
Figure FDA0002202787230000017
wherein A iseIs a state observer system matrix, and:
Figure FDA0002202787230000018
Lsfor the steady state gain matrix of the estimator, the following equations can be used:
AePs+PsAe+Qs-PsCT(Rs)-1CPs＝0
and solving to obtain the following result:
Ls＝PsCT(Rs)-1
Qsand RsAnd respectively estimating a system noise matrix and an observation noise matrix of the flight state of the unmanned aerial vehicle for the linear estimator of the attack party.
3. The drone spoofing method in combined navigation mode of claim 1, wherein in said step S2, the goal of the attacker is to make the drone follow a spoofing trajectory
Figure FDA0002202787230000019
Calculating the control input quantity a by adopting a PID control algorithmsComprises the following steps:
Figure FDA0002202787230000021
wherein the content of the first and second substances,
Figure FDA0002202787230000022
the parameter matrix is controlled for spoofing.
4. The drone spoofing method in combined navigation mode of claim 1, wherein in said step S3, the estimated flight status information of the drone obtained in connection with the step S1 is obtained
Figure FDA0002202787230000023
And the spoofed control input amount a acquired in step S2sThe attacker adopts the acceleration component a of the false satellite signal*Namely:
Figure FDA0002202787230000024
5. the unmanned aerial vehicle deception method under the integrated navigation mode of claim 1, wherein in step S4, the attacker obtains the position x of the false satellite signal at each time through integration*And velocity v*Information, i.e.
Figure FDA0002202787230000025
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CN113138399A (en) * 2021-04-22 2021-07-20 中国人民解放军国防科技大学 Unmanned aerial vehicle track tracking identification method based on machine learning
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CN113721280A (en) * 2021-07-30 2021-11-30 中国人民解放军国防科技大学 Method for realizing directional driving under combined navigation condition
CN115236702A (en) * 2022-07-07 2022-10-25 中国人民解放军国防科技大学 Concealed directional deception method based on exponential type deception signal model

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Cited By (12)

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CN111650620A (en) * 2020-05-29 2020-09-11 电子科技大学 Track deception method based on GPS navigation
CN111650620B (en) * 2020-05-29 2023-04-18 电子科技大学 Track deception method based on GPS navigation
CN111736180A (en) * 2020-06-24 2020-10-02 北京航空航天大学 Quasi-generation type unmanned aerial vehicle induction method and system
CN111736180B (en) * 2020-06-24 2022-07-12 北京航空航天大学 Quasi-generation type unmanned aerial vehicle induction method and system
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CN113625324A (en) * 2021-07-30 2021-11-09 中国人民解放军国防科技大学 Deception method for realizing precise fixed point offset of unmanned aerial vehicle in integrated navigation mode
CN113721280A (en) * 2021-07-30 2021-11-30 中国人民解放军国防科技大学 Method for realizing directional driving under combined navigation condition
CN113721280B (en) * 2021-07-30 2023-08-15 中国人民解放军国防科技大学 Method for realizing directional driving-away under combined navigation condition
CN115236702A (en) * 2022-07-07 2022-10-25 中国人民解放军国防科技大学 Concealed directional deception method based on exponential type deception signal model
CN115236702B (en) * 2022-07-07 2024-04-19 中国人民解放军国防科技大学 Hidden directional spoofing method based on exponential spoofing signal model

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