CN118131277A - GNSS spoofing detection system based on virtual anchor points - Google Patents
GNSS spoofing detection system based on virtual anchor points Download PDFInfo
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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
- G01S19/215—Interference related issues ; Issues related to cross-correlation, spoofing or other methods of denial of service issues related to spoofing
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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
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Abstract
The invention discloses a GNSS deception detection system based on a virtual anchor point, which can realize real-time and effective deception detection in a complex environment where multipath signals and deception signals coexist, and comprises a receiver, a virtual anchor point calculation module and a deception detection judgment module; the receiver is provided with a multichannel receiver resolving output module, the multichannel receiver resolving output module distributes a tracking channel for each signal which can be received under a PRN satellite, and converts the coherent integration result and the baseband observed quantity into satellite position data and pseudo-range data to the receiver; the virtual anchor point calculation module is respectively used for data simultaneous connection of each tracking channelSolving an equation set by using the values at each moment to obtain a set containing virtual anchor point positions corresponding to each tracking channel; the deception detection judgment module receives the solved position set of the virtual anchor point, calculates a skip list threshold value, a threshold value and the like, and judges whether deception signals exist or not.
Description
Technical Field
The invention relates to the technical field of global satellite positioning, in particular to a GNSS spoofing detection system based on a virtual anchor point.
Background
In recent years, the global satellite positioning system (Global Navigation SATELLITE SYSTEM, GNSS) has become an indispensable part of life of people due to the advantages of good continuity, high precision and the like, and is widely applied to the fields of power systems, financial systems, communication systems, traffic systems and the like. However, GNSS signals have a common characteristic: it is very weak on complex wireless channels due to propagation over long distances. Meanwhile, the civil GNSS signal structure and the modulation mode are disclosed to the outside, so that the GNSS signal structure is easy to be interfered, deceptively deceived and the like. Fraud against GNSS is extremely destructive, as it can lead to misleading time and location information for the target receiver and is difficult to discover.
In the past few years, many satellite navigation spoofing events have occurred both at home and abroad. Navigation systems present significant security risks in the face of spoofing attacks. With the rapid development of software radio technology, the cost of a deception device is lower and lower, deception attacks become more and more complex, GNSS service security faces a potential serious threat, and GNSS deception prevention research has important practical significance. The prior anti-deception technology is more focused on the post-processing of data, lacks of real-time performance and can only detect in a single environment, and does not consider the detection problem in a complex environment. At present, the navigation receiver directly utilizes observables in the signal processing process of the receiver to detect whether the navigation receiver is deception or not, which is a potential efficient and low-cost deception prevention scheme for users, but most of the existing hardware receivers only can output positioning results, but lack of utilization of intermediate observables. Therefore, there is a need for a system that can effectively enable real-time spoofing detection in complex environments where multipath signals coexist with spoofing signals, so as to meet increasingly complex spoofing detection scenarios and higher real-time spoofing detection requirements.
Disclosure of Invention
The invention aims to provide a GNSS spoofing detection system based on a virtual anchor point, which solves the problems existing in the prior art and can realize real-time and effective spoofing detection in a complex environment where multipath signals and spoofing signals exist simultaneously.
In order to achieve the above object, the solution of the present invention is:
A GNSS deception detection system based on a virtual anchor point comprises a receiver, a virtual anchor point calculation module and a deception detection judgment module; the receiver is provided with a multichannel receiver resolving output module with a plurality of tracking channels, and the multichannel receiver resolving output module distributes a tracking channel for each signal which can be received under a PRN satellite; each tracking channel receives a coherent integration result and a baseband observed quantity obtained in the process of tracking a satellite, and converts the coherent integration result and the baseband observed quantity into satellite position data of the tracked satellite and pseudo-range data of the tracked satellite to a receiver, so as to obtain a data set of each tracking channel; the virtual anchor point calculation module is respectively used for combining the data sets of each tracking channel Solving an equation set by using the values at each moment to obtain a set containing virtual anchor point positions corresponding to each tracking channel; the deception detection judgment module receives the solved position set of the virtual anchor points, and judges the jump table threshold value of the virtual anchor point position corresponding to each tracking channel respectively: if the virtual anchor point is abnormal, judging the signal corresponding to the tracking channel as a deception signal, and if the virtual anchor point is normal, storing the virtual anchor point position corresponding to the tracking channel to form a point set; then, the method carries out movement variance detection on the point sets of the same tracking channel and carries out distance/>, among the point sets of different tracking channelsAnd (3) performing binary hypothesis test, and judging that a deception signal exists if the fluctuation of the movement variance detection is larger than a threshold value or the distance between different point sets is larger than the threshold value.
The baseband observables include code phase and carrier phase.
The multi-channel receiver resolving output module converts the coherent integration result and the baseband observed quantity into the first oneWithin tracking channel/>Three-dimensional coordinate position of individual moments/>Pseudo range/>Clock-difference/>, obtained locally with the receiverAnd sending the virtual anchor points to the virtual anchor point calculation module.
Preferably, the virtual anchor point calculation module first establishes a virtual anchor point of the receiver with respect to the reflection surface for each PRN satellite, and converts satellite signals of each PRN satellite with respect to multipath of the reflection surface into a linear path from the satellite to the virtual anchor point; for every tracking channelAll at every moment/>Wherein/>Is/>Three-dimensional coordinate position/>, of VA obtained in each tracking channel; In obtaining the linear distance from VA to satellite/>And satellite position/>Then, solving the VA position for the same satellite/>Location of time, th/>The data in the individual trace channels are:
；
Wherein the method comprises the steps of Is the speed of light;
Calculating the position of a virtual anchor VA by using the data of different moments in a tracking channel, thereby obtaining a virtual anchor VA with the following characteristics A set of points for the/>There is/>, within each trace channelThe coordinate points solved by the satellite about the multipath signals of the same reflecting surface are as follows:
。
preferably, the processing of the spoofing detection decision module is as follows:
First step, real-time based on each tracking intra-channel solution set Whether or not exceeding a threshold value threshold/>Is detected for the first time, when/>When judging that there is a deception signal, wherein/>Taking the positioning error of the receiver;
second step, utilizing sliding window to pair The detection is performed on the points in (a), the window length is 10, if the moving variance/>, of the distance of the points stored in the windowExceeding a set threshold/>Judging that a deception signal exists;
Third step, when the signal state is normal, it will calculate The method comprises the steps of storing, for each PRN satellite, constructing a hypothesis testing model for the distance between virtual anchor points output by any two tracking channels:
；
Wherein, Represents the/>Statistics of geometric distance of virtual anchor point positions between any two tracking channels at each moment,/>And/>Respectively represent the/>Distances in the individual time-of-day spoofing scene and in the spoofing scene; /(I)Represents the/>Gaussian white noise at each instant. /(I)And/>Representing the assumption of no fraud and fraud in the satellite signal, respectively; constructed test statistic/>，/>；
Constructing a binary hypothesis test problem and setting a null hypothesisFor the signal to really have no deception signal, select hypothesisIf a spoofing signal exists for a signal anomaly, the decision problem is expressed as follows:
；
；
Wherein the method comprises the steps of For test statistics,/>To take absolute value,/>For detecting a threshold value; in case of fraud, probability of detection/>The method comprises the following steps:
；
If no deception signal exists, the distance between VA output by two tracking channels obeys the mean value to be 0 and the variance to be 0 Normal distribution/>The false alarm rate is:
；
And (3) obtaining a test result between every two tracking channels, and solving a plurality of tracking channels of the output module for the multichannel receiver, wherein when any one result is abnormal, the result represents that a deception signal exists.
After the technical scheme is adopted, the invention has the following technical effects:
The invention can realize real-time and effective deception detection in a complex environment where multipath signals and deception signals coexist; the invention effectively utilizes the multipath signal to assist in deception detection, maps a virtual anchor point for the first time in deception detection, and utilizes the virtual anchor point calculation module to model a reflected signal as a direct path to the VA for solving; compared with the existing deception detection scheme, the method and the device utilize the multichannel receiver resolving output module and the virtual anchor point calculating module to calculate the position of the virtual anchor point in real time, and utilize the characteristic that the geometric relationship between the deception source and the satellite relative to the receiver is different to formulate a scheme for detecting deception judgment, so that whether the receiver is deception in a complex environment can be judged in real time, thereby not only meeting the reliability of a deception detection system, but also meeting the requirement of real-time detection.
Drawings
FIG. 1 is a schematic view of a scene of an embodiment of the invention;
FIG. 2 is a schematic block diagram of an embodiment of the present invention;
FIG. 3 is a flow chart of a multi-channel receiver resolution output module according to an embodiment of the present invention;
FIG. 4 is a flow chart of a virtual anchor point calculation module according to an embodiment of the present invention;
FIG. 5 is a flowchart illustrating the execution of a fraud detection decision module according to an embodiment of the present invention;
FIG. 6 is a graph of the false alarm rate versus detection probability for a spoofing source VA and a receiver VA at different distances in accordance with an embodiment of the present invention;
fig. 7 is a graph of position calculation error versus detection probability in a virtual anchor point calculation module according to an embodiment of the present invention.
Detailed Description
In order to further explain the technical scheme of the invention, the invention is explained in detail by specific examples.
Referring to fig. 1 to 7, the invention discloses a GNSS spoofing detection system based on a virtual anchor point, which comprises a receiver, a virtual anchor point calculation module and a spoofing detection decision module;
the receiver is provided with a multichannel receiver resolving output module with a plurality of tracking channels, and the multichannel receiver resolving output module distributes a tracking channel to each signal (possibly a real signal, a multipath signal, a deception signal and the like) which can be received under a PRN satellite; each tracking channel receives a coherent integration result and a baseband observed quantity (comprising a code phase, a carrier phase and the like) obtained in the process of tracking a satellite, and converts the coherent integration result and the baseband observed quantity into satellite position data of the tracked satellite and pseudo-range data of the tracked satellite to a receiver to obtain a data set of each tracking channel;
The virtual anchor point calculation module calculates virtual anchor points of real signals, deception signals and multipath signals in the environment relative to the reflecting surface respectively, and particularly, the data sets of each tracking channel are combined Solving an equation set by using the values at each moment to obtain a set containing virtual anchor point positions corresponding to each tracking channel;
The deception detection judgment module receives the solved position set of the virtual anchor points, and judges the jump table threshold value of the virtual anchor point position corresponding to each tracking channel: if the virtual anchor point is abnormal, judging the signal corresponding to the tracking channel as a deception signal, and if the virtual anchor point is normal, storing the virtual anchor point position corresponding to the tracking channel to form a point set; then, the method carries out movement variance detection on the point sets of the same tracking channel and the distances between the point sets of different tracking channels And (3) performing binary hypothesis test, and judging that a deception signal exists if the fluctuation of the movement variance detection is larger than a threshold value or the distance between different point sets is larger than the threshold value.
Compared with the single-channel mode of the traditional receiver, the multi-channel receiver resolving output module adopts a multi-channel mode, can simultaneously receive the information of the multipath signals and the deception signals under one PRN satellite, and has the same processing in a single channel as the traditional processing, and is mainly used for acquiring more information so as to carry out subsequent detection.
In order to make it easier to understand the above technical solution, the system of the present invention is applied below in a scenario where both multipath signals and spoofing signals are present, the geometrical distribution of the reflecting surfaces of the scenario remaining unchanged, the spoofing signals being generated at the beginning. The spoofing detection process in this complex scenario is as follows:
(1) Referring to fig. 3, the tracking channels of the multi-channel receiver solution output module assign a tracking channel to each signal received by a PRN satellite; each tracking channel receives the coherent integration result and the baseband observed quantity of each signal respectively, converts the coherent integration result and the baseband observed quantity into a data group comprising satellite position data and pseudo-range data, and sends the data group to a virtual anchor point calculation module;
(2) Referring to fig. 4, the virtual anchor point calculation module receives the data set obtained in (1) and stores the data set, packages each 4 continuous data sets into a group for each data set in each tracking channel, and substitutes the groups into a position solving equation to obtain the position of a virtual anchor point;
(3) Referring to fig. 5, the spoofing detection decision module decides the change of the calculated virtual anchor point position, if there is no abnormality, the calculated virtual anchor point position is stored, and if there is an abnormality, an alarm for detecting the presence of a spoofing signal is sent; adding mobile variance detection to the stored point set of the virtual anchor points, and sending out an alarm for detecting a deception signal if the fluctuation is greater than a threshold value; and then, carrying out binary hypothesis test on the distance between the point sets of the virtual anchor points, and sending out an alarm for detecting the deception signal if the distance between the different point sets is larger than a threshold value.
Through the scheme, the invention can realize real-time and effective deception detection in a complex environment where multipath signals and deception signals coexist; the invention effectively utilizes the multipath signal to assist in deception detection, maps a virtual anchor point for the first time in deception detection, and utilizes the virtual anchor point calculation module to model a reflected signal as a direct path to the VA for solving; compared with the existing deception detection scheme, the method and the device utilize the multichannel receiver resolving output module and the virtual anchor point calculating module to calculate the position of the virtual anchor point in real time, and utilize the characteristic that the geometric relationship between the deception source and the satellite relative to the receiver is different to formulate a scheme for detecting deception judgment, so that whether the receiver is deception in a complex environment can be judged in real time, thereby not only meeting the reliability of a deception detection system, but also meeting the requirement of real-time detection.
Specific embodiments of the invention are shown below.
The processing of the multi-channel receiver resolving output module is as follows:
The module receives and processes the coherent integration result and the baseband observed quantity output by the multichannel receiver; for multi-channel data under a PRN satellite, the ephemeris of the satellite in the corresponding tracking channel is obtained according to the coherent integration result in each tracking channel, so that the three-dimensional coordinate position of the satellite is obtained Wherein/>Represents the/>Within tracking channel/>The three-dimensional position of each time satellite is obtained according to the same baseband observed quantityThe first tracking channelPseudo range of individual moments/>Clock-difference/>, obtained locally with the receiverTogether to the virtual anchor calculation module. At this time, since the multi-channel receiver solution output module has a plurality of tracking channels, multiple sets of data may be obtained under one PRN satellite for the subsequent fraud detection decision module, and the processing manners of the plurality of tracking channels under each PRN satellite are consistent.
The processing of the virtual anchor point calculation module is as follows:
Compared with the traditional method for solving the position of the receiver to be a simultaneous equation set of a plurality of satellites at the same time, the virtual anchor point calculation module converts the multipath distance from the satellite to the receiver into the distance from the mirror point after obtaining the satellite position through the observed quantity of the multipath signals output by the multichannel receiver calculation output module, and solves the position of the mirror point by using the simultaneous position of the same satellite at different times. Specifically, for the multi-channel output under each PRN satellite, a virtual anchor point of the GNSS receiver with respect to the reflection surface is first established, the satellite signal of each PRN satellite with respect to the reflection surface is converted into a linear path from the satellite to the virtual anchor point, and for the first tracking channel All at every moment/>Wherein/>Is/>Three-dimensional coordinate position/>, of VA obtained in each tracking channel. In obtaining the linear distance from VA to satellite/>And satellite position/>Then, solving the VA position for the same satellite/>Location of time, th/>The data in the individual trace channels are:
；
Wherein the method comprises the steps of Is the speed of light, the position of a virtual anchor point VA can be calculated by utilizing the data at different moments in a tracking channel, and as the observed quantity in each tracking channel can be continuously obtained, a useful/>, for a tracking channel can be obtainedPoint sets of individual points, e.g. proceed to the/>Individual moments have/>For the/>Within each tracking channel isThe coordinate points solved by the satellite about the multipath signals of the same reflecting surface are consistent, and the distance between the satellite and the multipath signals is smaller than a threshold value/>, in consideration of calculation errorsThen, there are:
；
the spatial position relationship between the deception source and the receiver is different from that between the real satellite and the receiver, so that the virtual anchor point position obtained by solving the multipath signals of the deception signals is caused Resolved from multipath signals of real satellites/>In contrast, we implement spoofing detection by detecting the distance between the calculated positions of virtual anchors within different tracking channels.
The processing of the deception detection judgment module is as follows:
First step, real-time based on each tracking intra-channel solution set Whether or not exceeding a threshold value threshold/>Is to perform first detection,/>Taking the positioning error of the receiver, if abnormal jump occurs, namelyJudging that a deception signal exists when the deception signal exists; this anomaly detection process is performed cyclically during the operation of the fraud detection decision module;
second step, utilizing sliding window to pair The detection is performed on the points in (a), the window length is 10, if the moving variance/>, of the distance of the points stored in the windowExceeding a set threshold/>Judging that a deception signal exists;
third step, the position of the virtual anchor VA is calculated when the signal state is normal (i.e. the above ) The relative positions of the deception sources and the reflecting surfaces are different due to the consistency of the coordinate points solved by the multipath signals of the same reflecting surface under each PRN satellite, and the virtual anchor points/>, which are solved by the multipath signals of the deception sources and are used for solving the reflecting surfaces, are storedVirtual anchor point/>, calculated by multipath signals of satelliteThere will be a distance/>. For each PRN satellite in the multi-channel receiver resolving output module, the information of several channels output by the multi-channel receiver resolving output module can obtain several groups of virtual anchor points in the virtual anchor point calculation module, and a hypothesis test model is constructed for the distance between the virtual anchor point positions output by any two tracking channels:
；
Wherein, Represents the/>Statistics of geometric distance of virtual anchor point positions between any two tracking channels at each moment,/>And/>Respectively represent the/>Distances in the individual time-of-day spoofing scene and in the spoofing scene; /(I)Represents the/>Gaussian white noise at each instant. /(I)And/>Representing the assumption of no fraud and fraud in the satellite signal, respectively.
Since the variable is the euclidean distance between two tracking channels, we can refer to the position of one of the tracking channels. The result of the tracking channel corresponding to the multipath signal is taken as a reference, the distribution of the calculation result of the virtual anchor points in the channel is approximately normal distribution due to the influence of the positioning error, if the tracking channel 1 tracks the multipath signal and the tracking channel 2 tracks the spoofing signal, the calculation result is as follows:
；
；
And/> The mean and variance representing the normal distribution of errors in the normal positioning state of the receiver can be obtained by positioning the true signal for a period of time by the receiver, wherein the values of the mean and variance are respectively used for positioning errors of the multichannel software receiver adopted by us. And/>Is determined by the geometric position of the spoofing source and has/>. What we need to check is whether the difference between the virtual anchor point positions output by two tracking channels is significant, so as to judge whether spoofing exists, so that the constructed test statistic/>，/>。
Specifically constructing a binary hypothesis test problem, setting a null hypothesisFor the signal to really have no deception signal, the hypothesis/>If a spoofing signal exists for a signal anomaly, the decision problem is expressed as follows:
；
；
Wherein the method comprises the steps of For test statistics,/>To take absolute value,/>For detecting a threshold value; in case of fraud, probability of detection/>The method comprises the following steps:
；
If no deception signal exists, the distance between VA output by two tracking channels obeys the mean value to be 0 and the variance to be 0 Normal distribution/>The false alarm rate can be obtained as follows:
；
For every two channels we can get a test result, if there is Individual channels can then be obtained/>And a result, when any result is abnormal, the result represents that a deception signal exists.
Fig. 6 is a graph showing the effect of the distance of the VA of the spoofing source relative to the (actual) VA of the receiver on the probability of detection of the present invention, the better the further the distance. The relation between the false alarm rate and the detection probability of the deception source VA and the receiver VA at different distances is shown by a logarithmic coordinate system, and it can be seen that the detection effect is correspondingly better when the distance between the two VA is larger, and when the false alarm rate reaches 0.1 and the distance between the two VA is small, VA positions obtained by different channels may be overlapped, and whether deception signals are contained or not cannot be distinguished.
Fig. 7 shows the relationship between the calculated error of VA and the detection probability, and we fix the distance from the spoofing source VA to the receiver VA to 40m, and as can be seen from fig. 7, the more accurate the position calculation of VA is, the better the detection effect is, and the effect of the detection algorithm is correspondingly reduced when the VA position error increases. The model has higher detection effect in normal error range, which also illustrates the effectiveness of the multipath auxiliary detection algorithm based on the virtual anchor point for fraud detection in complex multipath environment.
The above examples and drawings are not intended to limit the form or form of the present invention, and any suitable variations or modifications thereof by those skilled in the art should be construed as not departing from the scope of the present invention.
Claims (5)
1. A virtual anchor point-based GNSS spoofing detection system, characterized by:
the system comprises a receiver, a virtual anchor point calculation module and a deception detection judgment module;
The receiver is provided with a multichannel receiver resolving output module with a plurality of tracking channels, and the multichannel receiver resolving output module distributes a tracking channel for each signal which can be received under a PRN satellite; each tracking channel receives a coherent integration result and a baseband observed quantity obtained in the process of tracking a satellite, and converts the coherent integration result and the baseband observed quantity into satellite position data of the tracked satellite and pseudo-range data of the tracked satellite to a receiver, so as to obtain a data set of each tracking channel;
the virtual anchor point calculation module is respectively used for combining the data sets of each tracking channel Solving an equation set by using the values at each moment to obtain a set containing virtual anchor point positions corresponding to each tracking channel;
The deception detection judgment module receives the solved position set of the virtual anchor points, and judges the jump table threshold value of the virtual anchor point position corresponding to each tracking channel respectively: if the virtual anchor point is abnormal, judging the signal corresponding to the tracking channel as a deception signal, and if the virtual anchor point is normal, storing the virtual anchor point position corresponding to the tracking channel to form a point set; then, the method carries out movement variance detection on the point sets of the same tracking channel and the distances between the point sets of different tracking channels And (3) performing binary hypothesis test, and judging that a deception signal exists if the fluctuation of the movement variance detection is larger than a threshold value or the distance between different point sets is larger than the threshold value.
2. The virtual anchor point-based GNSS fraud detection system of claim 1, wherein:
the baseband observables include code phase and carrier phase.
3. The virtual anchor point-based GNSS fraud detection system of claim 1, wherein:
The multi-channel receiver resolving output module converts the coherent integration result and the baseband observed quantity into the first one Within tracking channel/>Three-dimensional coordinate position of individual moments/>Pseudo range/>Clock-difference/>, obtained locally with the receiverAnd sending the virtual anchor points to the virtual anchor point calculation module.
4. A virtual anchor point based GNSS fraud detection system as defined in claim 3, wherein:
The virtual anchor point calculation module firstly establishes a virtual anchor point of the receiver relative to the reflecting surface for each PRN satellite, and converts satellite signals of each PRN satellite relative to the multipath of the reflecting surface into a linear path from the satellite to the virtual anchor point;
For every tracking channel All at every moment/>Wherein/>Is/>Three-dimensional coordinate position/>, of VA obtained in each tracking channel; In obtaining the linear distance from VA to satelliteAnd satellite position/>Then, solving the VA position for the same satellite/>Location of time, th/>The data in the individual trace channels are:
；
Wherein the method comprises the steps of Is the speed of light;
Calculating the position of a virtual anchor VA by using the data of different moments in a tracking channel, thereby obtaining a virtual anchor VA with the following characteristics A set of points for the/>There is/>, within each trace channelThe coordinate points solved by the satellite about the multipath signals of the same reflecting surface are as follows:
。
5. The virtual anchor point-based GNSS fraud detection system of claim 4, wherein the fraud detection decision module processes:
First step, real-time based on each tracking intra-channel solution set Whether or not exceeding a threshold value threshold/>Is detected for the first time, when/>When judging that there is a deception signal, wherein/>Taking the positioning error of the receiver;
second step, utilizing sliding window to pair The detection is performed on the points in (a), the window length is 10, if the moving variance/>, of the distance of the points stored in the windowExceeding a set threshold/>Judging that a deception signal exists;
Third step, when the signal state is normal, it will calculate The method comprises the steps of storing, for each PRN satellite, constructing a hypothesis testing model for the distance between virtual anchor points output by any two tracking channels:
；
Wherein, Represents the/>Statistics of the geometric distance of the virtual anchor point location between any two trace channels at each instant,And/>Respectively represent the/>Distances in the individual time-of-day spoofing scene and in the spoofing scene; /(I)Represents the/>Gaussian white noise at each instant. /(I)And/>Representing the assumption of no fraud and fraud in the satellite signal, respectively; constructed test statistic/>，/>；
Constructing a binary hypothesis test problem and setting a null hypothesisFor the signal to really have no deception signal, the hypothesis/>If a spoofing signal exists for a signal anomaly, the decision problem is expressed as follows:
；
；
Wherein the method comprises the steps of For test statistics,/>To take absolute value,/>For detecting a threshold value; probability of detection in case of fraudThe method comprises the following steps:
；
If no deception signal exists, the distance between VA output by two tracking channels obeys the mean value to be 0 and the variance to be 0 Normal distribution/>The false alarm rate is:
；
And (3) obtaining a test result between every two tracking channels, and solving a plurality of tracking channels of the output module for the multichannel receiver, wherein when any one result is abnormal, the result represents that a deception signal exists.
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