CN117269989A - GNSS spoofing detection method and system based on ins assistance - Google Patents
GNSS spoofing detection method and system based on ins assistance Download PDFInfo
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- 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
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Abstract
The invention discloses a GNSS spoofing detection method and system based on ins assistance, wherein the method comprises the following steps: acquiring a first satellite signal at the last moment transmitted by a satellite, and calculating the position information at the last moment of a receiver according to the signal power and the carrier-to-noise ratio of the first satellite signal; mechanically arranging the receiver with the aid of ins to obtain the position information of the receiver at the current moment; according to the signal power and the carrier-to-noise ratio of the first satellite signal, obtaining the signal power and the carrier-to-noise ratio of a second satellite signal at the current moment through a preset prediction model; and according to the position information of the receiver at the current moment, the signal power and the carrier-to-noise ratio of the second satellite signal, generating a combined trust function through fusion by a DS evidence theory, and then detecting whether the satellite signal is a deception signal or not through a preset judging condition. The invention can accurately detect the satellite signals with weaker strength, reduces the false alarm rate and improves the detection precision of the deception signals.
Description
Technical Field
The invention belongs to the field of satellite navigation application, and particularly relates to a GNSS spoofing detection method and system based on ins assistance.
Background
Satellites play a relevant role in several fields of communication, early warning systems, global broadcasting, weather, navigation, reconnaissance, remote sensing, monitoring and the like. Their service covers almost every department from mobile cellular communication to telemedicine, so any interference to them can have a serious impact on the end user. For this reason, new demands are emerging for optimizing physical and mechanical constraints, costs, consumption, performance, robustness and protection. Global satellite navigation systems (GNSS) have been the main participant in spatial navigation in the last decade. It can be used in different applications such as precise orbit determination, attitude determination, remote sensing and tracking of transmitters or reentry of spacecraft. The GNSS signals are low-power signals, the signal-to-noise ratio is about-20 db, the strength of the GNSS signals is very weak, so that the received signals on the ground are easily interfered by the surrounding environment, and the carrier-to-noise ratio of the GNSS signals is reduced due to natural interference and artificial interference, so that the receiver is deceptively damaged.
Currently, many detection methods for GNSS spoofing are performed from the internal structure of the receiver, such as from the signal system, the array antenna, the signal processing layer, and the information processing layer. Specific methods include AGC automatic gain control, multimodal detection, residual signal detection, external data assistance, etc., but these detection methods have large requirements on signal quality and hardware level, and single channel detection is usually accompanied by a large false alarm rate, which is prone to cause false detection of fraud.
Disclosure of Invention
The invention provides a GNSS spoofing detection method and system based on ins assistance, which can accurately detect satellite signals with weaker strength, reduce false alarm rate and improve detection accuracy of spoofing signals.
A first aspect of the present invention provides a method for detecting GNSS fraud based on ins assistance, the method comprising:
acquiring a first satellite signal at the last moment transmitted by a satellite, and calculating the position information at the last moment of a receiver according to the signal power and the carrier-to-noise ratio of the first satellite signal;
according to the position information of the receiver at the moment, mechanical arrangement is carried out through ins assistance, and the position information of the receiver at the current moment is obtained; wherein the location information includes location coordinates;
according to the signal power and the carrier-to-noise ratio of the first satellite signal, obtaining the signal power and the carrier-to-noise ratio of a second satellite signal at the current moment through a preset prediction model;
according to the position information of the receiver at the current moment and the signal power and the carrier-to-noise ratio of the second satellite signal, generating a combined trust function through fusion by a DS evidence theory;
and detecting whether the satellite signal is a deception signal or not according to the combined trust function and a preset judging condition.
According to the scheme, the satellite signals transmitted by the satellites are acquired, the position information of the receiver at the current moment and the information of the satellite signals at the current moment are obtained, the two information are combined through the DS evidence theory to obtain a combined trust function, then the numerical value of the combined trust function is compared with the preset threshold value to determine whether the current satellite signals are deception signals, deception signals are detected according to fusion of three indexes, the false alarm rate in the detection process is reduced, and whether the current satellite signals are deception signals is judged more accurately.
In one possible implementation method of the first aspect, according to the position information of the receiver at a time, mechanical arrangement is performed with the aid of ins to obtain the position information of the receiver at the current time, specifically:
according to the specific force acceleration and the harmful acceleration of the receiver at the moment, mechanical arrangement is carried out through the aid of ins, and the specific force acceleration and the harmful acceleration of the receiver at the current moment are obtained;
and according to the specific force acceleration and the harmful acceleration of the current moment of the receiver, combining the position coordinate of the current moment of the receiver, and calculating to obtain the position coordinate of the current moment of the receiver.
According to the scheme, mechanical arrangement is performed through ins assistance, the specific force acceleration and the harmful acceleration of the receiver are combined, then the position information of the current moment of the receiver is predicted according to the position information of the last moment of the receiver, the predicted position information of the current moment is more accurate, and data support is provided for judging whether the satellite signal is a deception signal or not.
In one possible implementation method of the first aspect, according to the specific force acceleration and the harmful acceleration at the current moment of the receiver, the position coordinate at the current moment of the receiver is calculated by combining the position coordinate at the previous moment of the receiver, which specifically includes:
position coordinates of the receiver at a timeAnd the position coordinates of the receiver at the current timeThe following relationship is satisfied:
wherein Deltar isAnd->Δr obeys a chi-square distribution with a degree of freedom of 3.
In one possible implementation method of the first aspect, according to the signal power and the carrier-to-noise ratio of the first satellite signal, the signal power and the carrier-to-noise ratio of the second satellite signal at the current moment are obtained through a preset prediction model, which specifically includes:
according to the signal power of the first satellite signal, calculating the AGC gain of the second satellite signal at the current moment through a FSPL model of a preset prediction model to obtain the signal power of the second satellite signal at the current moment;
according to the carrier-to-noise ratio of the first satellite signal, a carrier-to-noise ratio of a second satellite signal at the current moment is obtained through a filter of a preset prediction model;
the preset prediction model is formed by modeling and calculating a plurality of influence factors, wherein the influence factors comprise satellite positions, antenna directions and gains, satellite signal power and frequency and the like.
According to the scheme, the signal power of the satellite signal at the current moment and the carrier-to-noise ratio of the satellite signal at the current moment are respectively obtained through the preset prediction model according to the information power and the carrier-to-noise ratio of the satellite signal at the previous moment, and as the preset prediction model considers a plurality of influence factors related to satellite signal propagation when predicting data, the obtained information of the current satellite signal is more accurate, and data support is provided for judging whether the current satellite signal is deceptively or not.
In one possible implementation method of the first aspect, according to the signal power of the first satellite signal, calculating an AGC gain of the second satellite signal at the current moment through an FSPL model of a preset prediction model, to obtain the signal power of the second satellite signal at the current moment; according to the carrier-to-noise ratio of the first satellite signal, the carrier-to-noise ratio of the second satellite signal at the current moment is obtained through a filter of a preset prediction model, specifically:
AGC gain P of second satellite signal at current time A The specific expression formula of (2) is as follows:
P A ＝P t G t A t A r λ 2 /4πd 2 LG r
wherein m is the set G of all fraud-free signals A Random m samples, G A For historical test data, P t Is GPS transmitter power, G t Is GPS transmitting antenna gain, A t Is the effective area of the GPS transmitting antenna, A r Is the effective area of the GPS receiving antenna, lambda is the GPS signal wavelength, d is the distance between the receiver and the satellite, L is the free space loss coefficient, G r Is the GPS receiving antenna gain;
carrier-to-noise ratio X of second satellite signal at current moment k+1 The specific formula of (2) is:
X k+1 ＝P k+1|k X k +w k
wherein X is k For the carrier-to-noise ratio, P, of the first satellite signal at the previous moment k+1 State transition matrix at time k+1, w k Is system noise.
In one possible implementation method of the first aspect, according to the position information of the current moment of the receiver and the signal power and the carrier-to-noise ratio of the second satellite signal, a combined trust function is generated by fusing by DS evidence theory, which specifically includes:
fitting a distribution function through a preset KS test according to the position coordinate of the current time of the receiver and the signal power and the carrier-to-noise ratio of the second satellite signal to obtain a first threshold value of the position coordinate of the current time of the receiver, a second threshold value of the signal power of the second satellite signal and a third threshold value of the carrier-to-noise ratio of the second satellite signal, and obtaining a trust function of the position coordinate of the current time of the receiver, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
Obtaining a conflict coefficient according to a trust function of the position coordinates of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
and according to the conflict coefficient and DS evidence theory, fusing a trust function of the position coordinate of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal to generate a combined trust function.
According to the scheme, fitting of the distribution function is carried out through preset KS test according to the position coordinate of the receiver at the current moment and the signal power and the carrier-to-noise ratio of the satellite signal at the current moment, the trust function corresponding to the three indexes is obtained, and then the trust function is fused into a combined trust function through DS evidence theory, so that data support is provided for judging the deception signal.
In one possible implementation method of the first aspect, according to the collision coefficient and DS evidence theory, a trust function of a position coordinate of a current moment of the receiver, a trust function of signal power of the second satellite signal, and a trust function of a carrier-to-noise ratio of the second satellite signal are fused to generate a combined trust function, which specifically is:
the specific formula of the collision coefficient k is:
Wherein m is 1 M is a trust function of the position coordinates of the receiver at the current moment 2 M is a trust function of the signal power of the second satellite signal 3 A, B and C are m respectively, as a trust function of the carrier-to-noise ratio of the second satellite signal 1 、m 2 And m 3 Is a focal point of (2);
wherein the trust function should satisfy the following constraints:
m i (θ 1 )+m i (θ 2 )＝1
m i (Φ)＝0
wherein θ 1 And theta 2 To be the focus of the trust function, m i (θ 1 ) M for trust functions with spoofing i (θ 2 ) To be trust function without fraud, m i (Φ) is a trust function that does not determine whether spoofing exists;
according to the conflict coefficient k and DS evidence theory, fusing m 1 、m 2 And m 3 Generating a combined trust function m (θ 1 ) The specific formula is as follows:
wherein w is i For the weight of each index, Λ i Statistics of historical fraud tests for each index correspondence c i And (3) for the threshold value corresponding to each index, wherein the index comprises the position coordinate of the current moment of the receiver, the signal power of the second satellite signal and the carrier-to-noise ratio of the second satellite signal.
In a second aspect, the present invention provides a system for detecting GNSS fraud based on ins assistance, said system comprising: the system comprises a receiver information calculation module, a satellite signal information calculation module, a trust function combination module and a deception signal judgment module;
The data acquisition module is used for acquiring a first satellite signal at the last moment sent by a satellite and calculating the position information at the last moment of a receiver according to the signal power and the carrier-to-noise ratio of the first satellite signal;
the receiver information calculation module is used for carrying out mechanical arrangement through ins assistance according to the position information of the receiver at the moment to obtain the position information of the receiver at the current moment; wherein the location information includes location coordinates;
the satellite signal information calculation module is used for obtaining the signal power and the carrier-to-noise ratio of the second satellite signal at the current moment through a preset prediction model according to the signal power and the carrier-to-noise ratio of the first satellite signal;
the trust function combination module is used for generating a combined trust function through fusion according to the position information of the receiver at the current moment, the signal power and the carrier-to-noise ratio of the second satellite signal and DS evidence theory;
the deception signal judging module is used for detecting whether the satellite signal is deception signal according to the combined trust function and a preset judging condition.
In a possible implementation manner of the second aspect, the receiver information calculation module includes: a receiver coordinate calculation unit;
The receiver coordinate calculation unit is used for carrying out mechanical arrangement through ins assistance according to the specific force acceleration and the harmful acceleration at the moment on the receiver to obtain the specific force acceleration and the harmful acceleration at the current moment of the receiver; and according to the specific force acceleration and the harmful acceleration of the current moment of the receiver, combining the position coordinate of the current moment of the receiver, and calculating to obtain the position coordinate of the current moment of the receiver.
In a possible implementation manner of the second aspect, according to the specific force acceleration and the harmful acceleration at the current moment of the receiver, the position coordinates of the current moment of the receiver are calculated by combining the position coordinates of the last moment of the receiver, and specifically:
position coordinates of the receiver at a timeAnd the position coordinates of the receiver at the current timeThe following relationship is satisfied:
wherein Deltar isAnd->Δr obeys a chi-square distribution with a degree of freedom of 3.
In a possible implementation manner of the second aspect, the satellite signal information calculating module includes: a power and carrier-to-noise ratio calculation unit;
the power and carrier-to-noise ratio calculating unit is used for calculating the AGC gain of the second satellite signal at the current moment through a FSPL model of a preset prediction model according to the signal power of the first satellite signal to obtain the signal power of the second satellite signal at the current moment;
According to the carrier-to-noise ratio of the first satellite signal, a carrier-to-noise ratio of a second satellite signal at the current moment is obtained through a filter of a preset prediction model;
the preset prediction model is formed by modeling and calculating a plurality of influence factors, wherein the influence factors comprise satellite positions, antenna directions and gains, satellite signal power and frequency and the like.
In one possible implementation manner of the second aspect, according to the signal power of the first satellite signal, calculating the AGC gain of the second satellite signal at the current moment through an FSPL model of a preset prediction model, to obtain the signal power of the second satellite signal at the current moment; according to the carrier-to-noise ratio of the first satellite signal, the carrier-to-noise ratio of the second satellite signal at the current moment is obtained through a filter of a preset prediction model, specifically:
AGC gain P of second satellite signal at current time A The specific expression formula of (2) is as follows:
P A ＝P t G t A t A r λ 2 /4πd 2 LG r
wherein m is the set G of all fraud-free signals A Random m samples, G A For historical test data, P t Is GPS transmitter power, G t Is GPS transmitting antenna gain, A t Is the effective area of the GPS transmitting antenna, A r Is the effective area of the GPS receiving antenna, lambda is the GPS signal wavelength, d is the distance between the receiver and the satellite, L is the free space loss coefficient, G r Is GPS connectorReceiving antenna gain;
carrier-to-noise ratio X of second satellite signal at current moment k+1 The specific formula of (2) is:
X k+1 ＝P k+1|k X k +w k
wherein X is k For the carrier-to-noise ratio, P, of the first satellite signal at the previous moment k+1 State transition matrix at time k+1, w k Is system noise.
In a possible implementation manner of the second aspect, the trust function combination module includes: a trust function combining unit;
the trust function combination unit is used for fitting a distribution function through a preset KS test according to the position coordinate of the current time of the receiver and the signal power and the carrier-to-noise ratio of the second satellite signal, obtaining a first threshold value of the position coordinate of the current time of the receiver, a second threshold value of the signal power of the second satellite signal and a third threshold value of the carrier-to-noise ratio of the second satellite signal, and obtaining a trust function of the position coordinate of the current time of the receiver, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
obtaining a conflict coefficient according to a trust function of the position coordinates of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
And according to the conflict coefficient and DS evidence theory, fusing a trust function of the position coordinate of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal to generate a combined trust function.
In a possible implementation manner of the second aspect, according to the collision coefficient and DS evidence theory, a trust function of a position coordinate of a current moment of the receiver, a trust function of a signal power of the second satellite signal, and a trust function of a carrier-to-noise ratio of the second satellite signal are fused to generate a combined trust function, which specifically is:
the specific formula of the collision coefficient k is:
wherein m is 1 M is a trust function of the position coordinates of the receiver at the current moment 2 M is a trust function of the signal power of the second satellite signal 3 A, B and C are m respectively, as a trust function of the carrier-to-noise ratio of the second satellite signal 1 、m 2 And m 3 Is a focal point of (2);
wherein the trust function should satisfy the following constraints:
m i (θ 1 )+m i (θ 2 )＝1
m i (Φ)＝0
wherein θ 1 And theta 2 To be the focus of the trust function, m i (θ 1 ) M for trust functions with spoofing i (θ 2 ) To be trust function without fraud, m i (Φ) is a trust function that does not determine whether spoofing exists;
according to the conflict coefficient k and DS evidence theory, fusing m 1 、m 2 And m 3 Generating a combined trust function m (θ 1 ) The specific formula is as follows:
wherein w is i For the weight of each index, Λ i Statistics of historical fraud tests for each index correspondence c i And (3) for the threshold value corresponding to each index, wherein the index comprises the position coordinate of the current moment of the receiver, the signal power of the second satellite signal and the carrier-to-noise ratio of the second satellite signal.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for detecting GNSS fraud based on ins assistance according to an embodiment of the present invention;
FIG. 2 is a block diagram of a GNSS fraud detection system based on ins assistance according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the step numbers used herein are for convenience of description only and are not intended as a limitation on the order in which the steps are performed.
Referring to fig. 1, fig. 1 is a specific flow chart of a method for detecting GNSS fraud based on ins assistance according to an embodiment of the present invention, where the method for detecting GNSS fraud based on ins assistance includes steps S1 to S5, and is described in detail as follows:
step S1, a first satellite signal at the last moment sent by a satellite is obtained, and position information at the last moment of a receiver is calculated according to the signal power and the carrier-to-noise ratio of the first satellite signal;
in this step, the receiver observes the satellite and receives the first satellite signal transmitted by the satellite at the previous moment; and solving the position coordinates of the receiver based on the geocentric fixed coordinates by positioning according to the first satellite signals of the last moment and ephemeris, wherein the ephemeris is a description of the position and the movement of the celestial body (such as planets, satellites and the like), and records the information of the position, orbit parameters, speed and the like of the celestial body in a specific time period.
Step S2, mechanical arrangement is carried out through ins assistance according to the position information of the receiver at the moment, and the position information of the receiver at the current moment is obtained;
In the step, firstly, mechanically arranging the position coordinate, the speed and the gesture of the receiver at the current moment through the aid of ins, and calculating the position coordinate of the receiver at the current moment;
further, according to the specific force acceleration and the harmful acceleration at the last moment of the receiver and the gesture matrix at the last moment, the inertial navigation device is used for mechanical arrangement to obtain the specific force acceleration, the harmful acceleration and the gesture matrix at the current moment of the receiver;
and then, according to the specific force acceleration, the harmful acceleration and the attitude matrix of the current moment of the receiver, combining the position coordinate of the last moment of the receiver, and calculating to obtain the position coordinate of the current moment of the receiver.
In some embodiments, the step S2 includes:
specific force acceleration, harmful acceleration and attitude matrix at the current moment of the receiver are specifically expressed as follows:
wherein,for the current-time pose matrix for determining the pose of the inertial navigation device, < >>For the current momentSpecific force acceleration, < >>The harmful acceleration at the current moment comprises the influence of the rotation of the earth and the gravity acceleration on the gyroscope and the accelerometer of the inertial navigator. Δp is the amount of change (longitude and latitude height) of the position in the earth coordinate system, +. >Respectively calculating the speeds of the last moment and the current moment under a navigation coordinate system, M pv The transition matrix for speed and position, w is the rotation vector, is the action of transforming the position coordinates from one coordinate system to the other, and T represents the time interval between the last moment and the current moment.
Because of the high-precision calculation of the inertial navigation device in a short time, the predicted data can be regarded as real data according to the above formula.
For the position information of the receiver, the position coordinates of the receiver at the moment in timeAnd the position coordinates of the receiver at the current moment +.>Satisfy the following relation
Wherein Deltar isAnd->Δr obeys a chi-square distribution with a degree of freedom of 3.
Step S3, obtaining the signal power and the carrier-to-noise ratio of the second satellite signal at the current moment through a preset prediction model according to the signal power and the carrier-to-noise ratio of the first satellite signal;
in the step, according to the signal power of the first satellite signal, calculating the AGC gain of the second satellite signal at the current moment through a FSPL model of a preset prediction model to obtain the signal power of the second satellite signal at the current moment; and obtaining the carrier-to-noise ratio of the second satellite signal at the current moment through a filter of a preset prediction model according to the carrier-to-noise ratio of the first satellite signal.
The preset prediction model considers a plurality of influence factors including the position of a satellite, the direction and gain of an antenna, the power and frequency of a signal and the like. Predicting the strength of the satellite signal at the receiver by modeling and calculating these influencing factors, i.e. calculating the AGC gain of the satellite signal to calculate the frequency of the satellite signal at the receiver; when the AGC gain becomes large, it is explained that the satellite signal strength decreases.
In calculating the strength of the satellite signal propagating to the receiver, the propagation path and attenuation of the satellite signal need to be considered, so the FSPL model is required to calculate the attenuation of the satellite signal; the FSPL model considers the influence factors such as obstacles, weather, atmosphere and the like encountered by satellite signals in the propagation process.
When the carrier-to-noise ratio of the satellite signals is calculated, a Kalman filter-based method is used for predicting the carrier-to-noise ratio, and the sum of energy of two paths of signals of I, Q is used as a state quantity for tracking to obtain the carrier-to-noise ratio of the second satellite signals at the current moment; the I, Q two paths of signals come from two orthogonal carrier signals generated locally, are multiplied by satellite signals despreaded by the lead code and the lag code respectively, and are obtained by coherent integration, so that the sampling rate can be reduced, and collected data can be utilized more efficiently.
In some embodiments, the step S3 includes:
AGC gain P of second satellite signal at current time A The specific expression formula of (2) is as follows:
P A ＝P t G t A t A r λ 2 /4πd 2 LG r
wherein m is the set G of all fraud-free signals A Random m samples, G A For historical test data, P t Is GPS transmitter power, G t Is GPS transmitting antenna gain, A t Is the effective area of the GPS transmitting antenna, A r Is the effective area of the GPS receiving antenna, lambda is the GPS signal wavelength, d is the distance between the receiver and the satellite, L is the free space loss coefficient, G r Is the GPS receiving antenna gain;
carrier-to-noise ratio X of second satellite signal at current moment k+1 The specific formula of (2) is:
X k+1 ＝P k+1|k X k +w k
Z k+1 ＝IP k+1 +QP k+1 +v k
wherein X is k For the carrier-to-noise ratio, P, of the first satellite signal at the previous moment k+1 State transition matrix at time k+1, w k Z is system noise k+1 The sum of the energy of the two paths of signals at the time k+1 is I, Q; wherein w is k Representing the noise contribution present in the current prediction model.
And S4, generating a combined trust function through fusion according to the position information of the receiver at the current moment, the signal power and the carrier-to-noise ratio of the second satellite signal and through DS evidence theory.
In the step, fitting a distribution function through a preset KS test according to the position coordinate of the receiver at the current moment and the signal power and the carrier-to-noise ratio of the second satellite signal to obtain a first threshold value of the position coordinate of the receiver at the current moment, a second threshold value of the signal power of the second satellite signal and a third threshold value of the carrier-to-noise ratio of the second satellite signal; wherein the first threshold, the second threshold and the third threshold are determined according to the false alarm rate of the historical test data;
And then obtaining a trust function of the position coordinates of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal according to the first threshold, the second threshold and the third threshold.
Obtaining a conflict coefficient according to a trust function of the position coordinates of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
and according to the conflict coefficient and DS evidence theory, fusing a trust function of the position coordinate of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal to generate a combined trust function.
In some embodiments, the step S4 includes:
for fraud detection, there are only two cases, there are fraud (θ 1 ) And no fraud (theta 2 ) Thus trust function m of this example i The following constraints should be met:
m i (θ 1 )+m i (θ 2 )＝1
m i (Φ)＝0
wherein θ 1 And theta 2 To be the focus of the trust function, m i (θ 1 ) M for trust functions with spoofing i (θ 2 ) To be trust function without fraud, m i (Φ) is a trust function that does not determine whether spoofing exists.
For three consistency indicators: the position coordinate of the receiver at the current moment, the signal power of the second satellite signal and the carrier-to-noise ratio of the second satellite signal, the corresponding threshold value is c i ，Λ i Statistics for fraud tests; when lambda i >c i When the signal is considered to be a deceptive signal, the trust function cannot be set, when Λ i <c i When the signal is not a deception signal, a trust function can be set, and the specific expression of the trust function is as follows:
in addition, for the receiverPosition coordinates at the current timeFitting the distribution function by KS test to makeThe compliance mean is +.>Obtaining a trust function m of the position coordinates of the receiver at the current moment 1 ；
AGC gain P for second satellite signal A Fitting the distribution function by KS test to make P A Obeying mean value ofVariance is->Obtaining a trust function m of the signal power of the second satellite signal 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>And->The specific formula of (2) is: />
Carrier-to-noise ratio X for a second satellite signal k+1 Fitting the distribution function by KS test to make X k+1 Obeying mean value ofVariance is->Obtaining a trust function m of the carrier-to-noise ratio of the second satellite signal 3 。
According to m 1 、m 2 And m 3 The collision coefficient k is obtained, and the specific formula is as follows:
wherein A, B and C are each m 1 、m 2 And m 3 Is a focus of (a).
According to the conflict coefficient k and DS evidence theory, fusing m 1 、m 2 And m 3 Generating a combined trust function m (θ 1 ) The specific formula is as follows:
wherein w is i For the weight of each index, the weight of each index can be adjusted according to the actual detection requirement, and Λ i Statistics of historical fraud tests for each index correspondence c i And (3) for the threshold value corresponding to each index, wherein the index comprises the position coordinate of the current moment of the receiver, the signal power of the second satellite signal and the carrier-to-noise ratio of the second satellite signal.
Step S5, detecting whether the satellite signal is a deception signal or not according to the combined trust function and a preset judging condition;
in the step, a preset judgment condition sets a judgment threshold value to be 0.5;
when m (theta) 1 )>When=0.5, the satellite signal is considered to be a rogue signal;
when m (theta) 1 )<0.5, the satellite signal is considered not to be a rogue signal.
Further, in order to implement the ins-assisted GNSS fraud detection system corresponding to the above method embodiment to implement the response function and technical effect, fig. 2 provides a block diagram of an ins-assisted GNSS fraud detection system. For convenience of explanation, only the parts related to this embodiment are shown, and the detection system for GNSS fraud based on ins assistance provided in the embodiment of the present invention includes:
the data acquisition module 201 is configured to acquire a first satellite signal at a previous moment sent by a satellite, and calculate position information at the previous moment of a receiver according to signal power and carrier-to-noise ratio of the first satellite signal;
The receiver information calculation module 202 is configured to perform mechanical arrangement with the aid of ins according to the position information of the receiver at a previous time, so as to obtain the position information of the receiver at the current time; wherein the location information includes location coordinates;
the satellite signal information calculation module 203 is configured to obtain, according to the signal power and the carrier-to-noise ratio of the first satellite signal, the signal power and the carrier-to-noise ratio of the second satellite signal at the current moment through a preset prediction model;
the trust function combination module 204 is configured to generate a combined trust function by fusing according to the position information of the receiver at the current moment, the signal power and the carrier-to-noise ratio of the second satellite signal, and the DS evidence theory;
and the spoofing signal determining module 205 is configured to detect whether the satellite signal is a spoofing signal according to the combined trust function and a preset judgment condition.
In some embodiments, the receiver information calculation module 202 includes:
the receiver coordinate calculation unit is used for carrying out mechanical arrangement through ins assistance according to the specific force acceleration and the harmful acceleration at the moment on the receiver to obtain the specific force acceleration and the harmful acceleration at the current moment of the receiver; and according to the specific force acceleration and the harmful acceleration of the current moment of the receiver, combining the position coordinate of the current moment of the receiver, and calculating to obtain the position coordinate of the current moment of the receiver.
In some embodiments, the receiver coordinate calculation unit is specifically configured to:
specific force acceleration, harmful acceleration and attitude matrix at the current moment of the receiver are specifically expressed as follows:
wherein,for the current-time pose matrix for determining the pose of the inertial navigation device, < >>For the specific force acceleration at the present moment, +.>The harmful acceleration at the current moment comprises the influence of the rotation of the earth and the gravity acceleration on the gyroscope and the accelerometer of the inertial navigator. Δp is the amount of change (longitude and latitude height) of the position in the earth coordinate system, +.>Respectively calculating the speeds of the last moment and the current moment under a navigation coordinate system, M pv The transition matrix for speed and position, w is the rotation vector, is the action of transforming the position coordinates from one coordinate system to the other, and T represents the time interval between the last moment and the current moment.
Because of the high-precision calculation of the inertial navigation device in a short time, the predicted data can be regarded as real data according to the above formula.
For the position information of the receiver, the position coordinates of the receiver at the moment in timeAnd the position coordinates of the receiver at the current moment +.>Satisfy such as The following relationship:
wherein Deltar isAnd->Δr obeys a chi-square distribution with a degree of freedom of 3.
In some embodiments, the satellite signal information calculation module 203 includes:
the power and carrier-to-noise ratio calculation unit is used for calculating the AGC gain of the second satellite signal at the current moment through a FSPL model of a preset prediction model according to the signal power of the first satellite signal to obtain the signal power of the second satellite signal at the current moment;
according to the carrier-to-noise ratio of the first satellite signal, a carrier-to-noise ratio of a second satellite signal at the current moment is obtained through a filter of a preset prediction model;
the preset prediction model is formed by modeling and calculating a plurality of influence factors, wherein the influence factors comprise satellite positions, antenna directions and gains, satellite signal power and frequency and the like.
In some embodiments, the power and carrier-to-noise ratio calculating unit is specifically configured to:
in calculating the strength of the satellite signal propagating to the receiver, the propagation path and attenuation of the satellite signal need to be considered, so the FSPL model is required to calculate the attenuation of the satellite signal; the FSPL model considers the influence factors such as obstacles, weather, atmosphere and the like encountered by satellite signals in the propagation process.
When the carrier-to-noise ratio of the satellite signals is calculated, a Kalman filter-based method is used for predicting the carrier-to-noise ratio, and the sum of energy of two paths of signals of I, Q is used as a state quantity for tracking to obtain the carrier-to-noise ratio of the second satellite signals at the current moment; the I, Q two paths of signals come from two orthogonal carrier signals generated locally, are multiplied by satellite signals despreaded by the lead code and the lag code respectively, and are obtained by coherent integration, so that the sampling rate can be reduced, and collected data can be utilized more efficiently.
AGC gain P of second satellite signal at current time A The specific expression formula of (2) is as follows:
P A ＝P t G t A t A r λ 2 /4πd 2 LG r
wherein m is the set G of all fraud-free signals A Random m samples, G A For historical test data, P t Is GPS transmitter power, G t Is GPS transmitting antenna gain, A t Is the effective area of the GPS transmitting antenna, A r Is the effective area of the GPS receiving antenna, lambda is the GPS signal wavelength, d is the distance between the receiver and the satellite, L is the free space loss coefficient, G r Is the GPS receiving antenna gain;
carrier-to-noise ratio X of second satellite signal at current moment k+1 The specific formula of (2) is:
X k+1 ＝P k+1|k X k +w k
Z k+1 ＝IP k+1 +QP k+1 +v k
wherein X is k For the carrier-to-noise ratio, P, of the first satellite signal at the previous moment k+1 State transition matrix at time k+1, w k Z is system noise k+1 The sum of the energy of the two paths of signals at the time k+1 is I, Q; wherein w is k Representing the noise contribution present in the current prediction model.
In some embodiments, the trust function combination module 204 includes:
the trust function combination unit is used for fitting a distribution function through a preset KS test according to the position coordinate of the current moment of the receiver and the signal power and the carrier-to-noise ratio of the second satellite signal, obtaining a first threshold value of the position coordinate of the current moment of the receiver, a second threshold value of the signal power of the second satellite signal and a third threshold value of the carrier-to-noise ratio of the second satellite signal, and obtaining a trust function of the position coordinate of the current moment of the receiver, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
obtaining a conflict coefficient according to a trust function of the position coordinates of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
and according to the conflict coefficient and DS evidence theory, fusing a trust function of the position coordinate of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal to generate a combined trust function.
In some embodiments, the trust function combination unit is specifically configured to:
for fraud detection, there are only two cases, there are fraud (θ 1 ) And no fraud (theta 2 ) Thus trust function m of this example i The following constraints should be met:
m i (θ 1 )+m i (θ 2 )＝1
m i (Φ)＝0
wherein θ 1 And theta 2 To be the focus of the trust function, m i (θ 1 ) M for trust functions with spoofing i (θ 2 ) To be trust function without fraud, m i (Φ) is a trust function that does not determine whether spoofing exists.
For three consistency indicators: the position coordinate of the receiver at the current moment, the signal power of the second satellite signal and the carrier-to-noise ratio of the second satellite signal, the corresponding threshold value is c i ，Λ i Statistics for fraud tests; when lambda i >c i When the signal is considered to be a deceptive signal, the trust function cannot be set, when Λ i <c i When the signal is not a deception signal, a trust function can be set, and the specific expression of the trust function is as follows:
m i (θ 2 )＝1-f(Λ i ,c i )
in addition, for the position coordinates of the receiver at the current timeFitting the distribution function by KS test to makeThe compliance mean is +.>Obtaining a trust function m of the position coordinates of the receiver at the current moment 1 ；
AGC gain P for second satellite signal A Fitting the distribution function by KS test to make P A Obeying mean value ofVariance is->Obtaining a trust function m of the signal power of the second satellite signal 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>And->The specific formula of (2) is: />
Carrier-to-noise ratio X for a second satellite signal k+1 Fitting the distribution function by KS test to make X k+1 Obeying mean value ofVariance is->Gaussian distribution of (2) to obtainTrust function m of carrier-to-noise ratio of second satellite signal 3 。
According to m 1 、m 2 And m 3 The collision coefficient k is obtained, and the specific formula is as follows:
wherein A, B and C are each m 1 、m 2 And m 3 Is a focus of (a).
According to the conflict coefficient k and DS evidence theory, fusing m 1 、m 2 And m 3 Generating a combined trust function m (θ 1 ) The specific formula is as follows:
wherein w is i For the weight of each index, the weight of each index can be adjusted according to the actual detection requirement, and Λ i Statistics of historical fraud tests for each index correspondence c i And (3) for the threshold value corresponding to each index, wherein the index comprises the position coordinate of the current moment of the receiver, the signal power of the second satellite signal and the carrier-to-noise ratio of the second satellite signal.
In some embodiments, the fraud signal determination module 205 is specifically configured to:
setting a preset judging condition to be 0.5;
when m (theta) 1 )>When=0.5, the satellite signal is considered to be a rogue signal;
when m (theta) 1 )<0.5, the satellite signal is considered not to be a rogue signal.
The embodiment provides a GNSS spoofing detection method and system based on ins assistance: acquiring a first satellite signal at the last moment transmitted by a satellite, and calculating the position information at the last moment of a receiver according to the signal power and the carrier-to-noise ratio of the first satellite signal; according to the position information of the receiver at the moment, mechanical arrangement is carried out through ins assistance, and the position information of the receiver at the current moment is obtained; according to the signal power and the carrier-to-noise ratio of the first satellite signal, obtaining the signal power and the carrier-to-noise ratio of a second satellite signal at the current moment through a preset prediction model; according to the position information of the receiver at the current moment and the signal power and the carrier-to-noise ratio of the second satellite signal, generating a combined trust function through fusion by a DS evidence theory; and detecting whether the satellite signal is a deception signal or not according to the combined trust function and a preset judging condition. The beneficial effects are that: the satellite signal with weaker strength can be accurately detected, the false alarm rate is reduced, and the detection precision of the deception signal is improved.
The above embodiments are provided to further illustrate the objects, technical solutions and advantageous effects of the present invention. It should be understood that the foregoing is only illustrative of the present invention and is not intended to limit the scope of the present invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.
Claims (14)
1. A method for detecting GNSS fraud based on ins assistance, comprising:
acquiring a first satellite signal at the last moment transmitted by a satellite, and calculating the position information at the last moment of a receiver according to the signal power and the carrier-to-noise ratio of the first satellite signal;
according to the position information of the receiver at the moment, mechanical arrangement is carried out through ins assistance, and the position information of the receiver at the current moment is obtained; wherein the location information includes location coordinates;
according to the signal power and the carrier-to-noise ratio of the first satellite signal, obtaining the signal power and the carrier-to-noise ratio of a second satellite signal at the current moment through a preset prediction model;
according to the position information of the receiver at the current moment and the signal power and the carrier-to-noise ratio of the second satellite signal, generating a combined trust function through fusion by a DS evidence theory;
and detecting whether the satellite signal is a deception signal or not according to the combined trust function and a preset judging condition.
2. The method for detecting GNSS spoofing based on ins assist according to claim 1, wherein the step of mechanically arranging the receiver according to the position information of the receiver at a moment is performed by ins assist to obtain the position information of the receiver at the current moment, specifically:
According to the specific force acceleration and the harmful acceleration of the receiver at the moment, mechanical arrangement is carried out through the aid of ins, and the specific force acceleration and the harmful acceleration of the receiver at the current moment are obtained;
and according to the specific force acceleration and the harmful acceleration of the current moment of the receiver, combining the position coordinate of the current moment of the receiver, and calculating to obtain the position coordinate of the current moment of the receiver.
3. The ins-assisted GNSS fraud detection method according to claim 2, wherein the calculating, according to the specific force acceleration and the harmful acceleration at the current time of the receiver, by combining the position coordinates at the previous time of the receiver, obtains the position coordinates at the current time of the receiver specifically includes:
position coordinates of the receiver at a timeAnd the position coordinates of the receiver at the current moment +.>The following relationship is satisfied:
wherein Deltar isAnd->Δr obeys a chi-square distribution with a degree of freedom of 3.
4. The method for detecting GNSS spoofing based on ins-assist according to claim 1, wherein the obtaining the signal power and the carrier-to-noise ratio of the second satellite signal at the current moment according to the signal power and the carrier-to-noise ratio of the first satellite signal through a preset prediction model is specifically as follows:
According to the signal power of the first satellite signal, calculating the AGC gain of the second satellite signal at the current moment through a FSPL model of a preset prediction model to obtain the signal power of the second satellite signal at the current moment;
according to the carrier-to-noise ratio of the first satellite signal, a carrier-to-noise ratio of a second satellite signal at the current moment is obtained through a filter of a preset prediction model;
the preset prediction model is formed by modeling and calculating a plurality of influence factors, wherein the influence factors comprise satellite positions, antenna directions and gains, satellite signal power and frequency and the like.
5. The method for detecting GNSS spoofing based on ins-assist according to claim 4, wherein the AGC gain of the second satellite signal at the current moment is calculated according to the signal power of the first satellite signal by a FSPL model of a preset prediction model to obtain the signal power of the second satellite signal at the current moment; according to the carrier-to-noise ratio of the first satellite signal, the carrier-to-noise ratio of the second satellite signal at the current moment is obtained through a filter of a preset prediction model, specifically:
AGC gain P of second satellite signal at current time A The specific expression formula of (2) is as follows:
P A ＝P t G t A t A r λ 2 /4πd 2 LG r
wherein m is the set G of all fraud-free signals A Random m samples, G A For historical test data, P t Is GPS transmitter power, G t Is GPS transmitting antenna gain, A t Is the effective area of the GPS transmitting antenna, A r Is the effective area of the GPS receiving antenna, lambda is the GPS signal wavelength, d is the distance between the receiver and the satellite, L is the free space loss coefficient, G r Is the GPS receiving antenna gain;
carrier-to-noise ratio X of second satellite signal at current moment k+1 The specific formula of (2) is:
X k+1 ＝P k+1|k X k +w k
wherein X is k For the carrier-to-noise ratio, P, of the first satellite signal at the previous moment k+1 State transition matrix at time k+1, w k Is system noise.
6. The ins-assisted GNSS spoofing-based detection method according to claim 1, wherein the generating a combined trust function by means of DS evidence theory according to the position information of the receiver at the current moment and the signal power and carrier-to-noise ratio of the second satellite signal is specifically:
fitting a distribution function through a preset KS test according to the position coordinate of the current time of the receiver and the signal power and the carrier-to-noise ratio of the second satellite signal to obtain a first threshold value of the position coordinate of the current time of the receiver, a second threshold value of the signal power of the second satellite signal and a third threshold value of the carrier-to-noise ratio of the second satellite signal, and obtaining a trust function of the position coordinate of the current time of the receiver, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
Obtaining a conflict coefficient according to a trust function of the position coordinates of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
and according to the conflict coefficient and DS evidence theory, fusing a trust function of the position coordinate of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal to generate a combined trust function.
7. The ins-assisted GNSS spoofing detection method according to claim 6, wherein the combining trust function is generated by combining the trust function of the position coordinates of the receiver at the current moment, the trust function of the signal power of the second satellite signal and the trust function of the carrier-to-noise ratio of the second satellite signal according to the collision coefficient and DS evidence theory, specifically:
the specific formula of the collision coefficient k is:
wherein m is 1 M is a trust function of the position coordinates of the receiver at the current moment 2 M is a trust function of the signal power of the second satellite signal 3 A, B and C are m respectively, as a trust function of the carrier-to-noise ratio of the second satellite signal 1 、m 2 And m 3 Is a focal point of (2);
wherein the trust function should satisfy the following constraints:
m i (θ 1 )+m i (θ 2 )＝1
m i (Φ)＝0
Wherein θ 1 And theta 2 To be the focus of the trust function, m i (θ 1 ) M for trust functions with spoofing i (θ 2 ) To be trust function without fraud, m i (Φ) is a trust function that does not determine whether spoofing exists;
according to the conflict coefficient k and DS evidence theory, fusing m 1 、m 2 And m 3 Generating a combined trust function m (θ 1 ) The specific formula is as follows:
wherein w is i For the weight of each index, Λ i Statistics of historical fraud tests for each index correspondence c i For each indexThe corresponding threshold value, the index includes the position coordinate of the current moment of the receiver, the signal power of the second satellite signal and the carrier-to-noise ratio of the second satellite signal.
8. An ins-assisted GNSS fraud based detection system, comprising: the system comprises a data acquisition module, a receiver information calculation module, a satellite signal information calculation module, a trust function combination module and a deception signal judgment module;
the data acquisition module is used for acquiring a first satellite signal at the last moment sent by a satellite and calculating the position information at the last moment of a receiver according to the signal power and the carrier-to-noise ratio of the first satellite signal;
the receiver information calculation module is used for carrying out mechanical arrangement through ins assistance according to the position information of the receiver at the moment to obtain the position information of the receiver at the current moment; wherein the location information includes location coordinates;
The satellite signal information calculation module is used for obtaining the signal power and the carrier-to-noise ratio of the second satellite signal at the current moment through a preset prediction model according to the signal power and the carrier-to-noise ratio of the first satellite signal;
the trust function combination module is used for generating a combined trust function through fusion according to the position information of the receiver at the current moment, the signal power and the carrier-to-noise ratio of the second satellite signal and DS evidence theory;
the deception signal judging module is used for detecting whether the satellite signal is deception signal according to the combined trust function and a preset judging condition.
9. The ins-assisted GNSS fraud based detection system of claim 8, wherein the receiver information calculation module comprises: a receiver coordinate calculation unit;
the receiver coordinate calculation unit is used for carrying out mechanical arrangement through ins assistance according to the specific force acceleration and the harmful acceleration at the moment on the receiver to obtain the specific force acceleration and the harmful acceleration at the current moment of the receiver; and according to the specific force acceleration and the harmful acceleration of the current moment of the receiver, combining the position coordinate of the current moment of the receiver, and calculating to obtain the position coordinate of the current moment of the receiver.
10. The ins-assisted GNSS fraud detection system according to claim 9, wherein the calculating the position coordinates of the current moment of the receiver according to the specific force acceleration and the harmful acceleration of the current moment of the receiver and the position coordinates of the last moment of the receiver is performed specifically by:
position coordinates of the receiver at a timeAnd the position coordinates of the receiver at the current moment +.>The following relationship is satisfied:
wherein Deltar isAnd->Δr obeys a chi-square distribution with a degree of freedom of 3.
11. The ins-assisted GNSS fraud based detection system of claim 8, wherein the satellite signal information calculation module comprises: a power and carrier-to-noise ratio calculation unit;
the power and carrier-to-noise ratio calculating unit is used for calculating the AGC gain of the second satellite signal at the current moment through a FSPL model of a preset prediction model according to the signal power of the first satellite signal to obtain the signal power of the second satellite signal at the current moment;
according to the carrier-to-noise ratio of the first satellite signal, a carrier-to-noise ratio of a second satellite signal at the current moment is obtained through a filter of a preset prediction model;
the preset prediction model is formed by modeling and calculating a plurality of influence factors, wherein the influence factors comprise satellite positions, antenna directions and gains, satellite signal power and frequency and the like.
12. The system for detecting the GNSS fraud based on the ins-assist according to claim 11, wherein the AGC gain of the second satellite signal at the current moment is calculated according to the signal power of the first satellite signal through an FSPL model of a preset prediction model, so as to obtain the signal power of the second satellite signal at the current moment; according to the carrier-to-noise ratio of the first satellite signal, the carrier-to-noise ratio of the second satellite signal at the current moment is obtained through a filter of a preset prediction model, specifically:
AGC gain P of second satellite signal at current time A The specific expression formula of (2) is as follows:
P A ＝P t G t A t A r λ 2 /4πd 2 LG r
wherein m is the set G of all fraud-free signals A Random m samples, G A For historical test data, P t Is GPS transmitter power, G t Is GPS transmitting antenna gain, A t Is the effective area of the GPS transmitting antenna, A r Is the effective area of the GPS receiving antenna, lambda is the GPS signal wavelength, d is the distance between the receiver and the satellite, L is the free space loss coefficient, G r Is the GPS receiving antenna gain;
carrier-to-noise ratio X of second satellite signal at current moment k+1 The specific formula of (2) is:
X k+1 ＝P k+1|k X k +w k
wherein X is k For the carrier-to-noise ratio, P, of the first satellite signal at the previous moment k+1 State transition matrix at time k+1, w k Is a systemNoise.
13. The ins-assisted GNSS fraud detection system of claim 8, wherein the trust function combining module comprises: a trust function combining unit;
the trust function combination unit is used for fitting a distribution function through a preset KS test according to the position coordinate of the current time of the receiver and the signal power and the carrier-to-noise ratio of the second satellite signal, obtaining a first threshold value of the position coordinate of the current time of the receiver, a second threshold value of the signal power of the second satellite signal and a third threshold value of the carrier-to-noise ratio of the second satellite signal, and obtaining a trust function of the position coordinate of the current time of the receiver, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
obtaining a conflict coefficient according to a trust function of the position coordinates of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal;
and according to the conflict coefficient and DS evidence theory, fusing a trust function of the position coordinate of the receiver at the current moment, a trust function of the signal power of the second satellite signal and a trust function of the carrier-to-noise ratio of the second satellite signal to generate a combined trust function.
14. The ins-assisted GNSS spoofing detection system of claim 13, wherein the combining the trust function of the position coordinates at the current time of the receiver, the trust function of the signal power of the second satellite signal and the trust function of the carrier-to-noise ratio of the second satellite signal according to the collision coefficient and DS evidence theory generates a combined trust function, specifically:
the specific formula of the collision coefficient k is:
wherein m is 1 For the current time of the receiverTrust function of position coordinates of the engraving, m 2 M is a trust function of the signal power of the second satellite signal 3 A, B and C are m respectively, as a trust function of the carrier-to-noise ratio of the second satellite signal 1 、m 2 And m 3 Is a focal point of (2);
wherein the trust function should satisfy the following constraints:
m i (θ 1 )+m i (θ 2 )＝1
m i (Φ)＝0
wherein θ 1 And theta 2 To be the focus of the trust function, m i (θ 1 ) M for trust functions with spoofing i (θ 2 ) To be trust function without fraud, m i (Φ) is a trust function that does not determine whether spoofing exists;
according to the conflict coefficient k and DS evidence theory, fusing m 1 、m 2 And m 3 Generating a combined trust function m (θ 1 ) The specific formula is as follows:
wherein w is i For the weight of each index, Λ i Statistics of historical fraud tests for each index correspondence c i And (3) for the threshold value corresponding to each index, wherein the index comprises the position coordinate of the current moment of the receiver, the signal power of the second satellite signal and the carrier-to-noise ratio of the second satellite signal.
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| CN117991302B (en) * | 2024-04-02 | 2024-06-07 | 辽宁天衡智通防务科技有限公司 | Navigation spoofing detection method and system based on multiple information sources |
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