CN109765574B - Single-base-station GNSS forwarding type deception source positioning method and device - Google Patents
Single-base-station GNSS forwarding type deception source positioning method and device Download PDFInfo
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Abstract
The embodiment of the invention provides a single base station GNSS forwarding type deception source positioning method and a device, wherein the method comprises the following steps: acquiring deception signal information to obtain first satellite transmission time information according to the deception signal; processing the first satellite transmitting time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information; and processing the space-time double-difference observation vector information by a maximum likelihood estimation method to obtain final deception source position information. Respectively carrying out time difference and space difference on the emission time of different satellites through a space-time double-difference observation model so as to obtain a space-time double-difference observation vector, and then carrying out maximum likelihood estimation to position a deception source; the embodiment of the invention can complete positioning through a single base station, the positioning precision is not influenced by the position of the base station, the position information of the base station is not required to be known, and the method can be easily realized by a common receiver.
Description
Technical Field
The embodiment of the invention relates to the technical field of satellite navigation positioning, in particular to a single-base-station GNSS forwarding type deception source positioning method and device.
Background
With the proliferation of GNSS facilities, GNSS plays an increasingly important role in human society, such as fields of communication, agriculture, finance, transportation, military, and electric power. However, the safety issues of GNSS are also becoming more severe.
Because the GNSS signal power is weak, it is very vulnerable to interference of external electromagnetic waves, including jamming interference and spoofing interference. The interference is suppressed, and the receiver cannot work normally by transmitting electromagnetic wave signals near high-power GNSS frequency points. However, the suppressed interference is easily discovered by the receiver; and the threat is more fraud interference, and the receiver is induced to output wrong position and time information under the condition of no knowledge by transmitting fraud signals. To cope with spoofing interference, it is desirable that we be able to detect and identify spoofing signals while locating the spoofing source. The deception source location is found through deception source location technology, and deception threats can be solved from the source.
The prior art mainly focuses on deception detection and identification, and researches on deception source positioning technology are less. Current spoofed source location techniques, such as Time Difference Of Arrival (TDOA) techniques, typically require multiple clock-synchronized base stations and require that the base station locations be known; the technology based on Received Signal Strength (RSS) requires an accurate channel fading model, which generally has a large error and is greatly influenced by the channel environment. Also, in these techniques, spoofed source location estimation accuracy is limited by the relative geometry of the base stations and spoofed sources. Therefore, how to effectively locate the spoofing source has become an urgent problem to be solved in the industry.
Disclosure of Invention
The embodiment of the invention provides a single base station GNSS forwarding type deception source positioning method and device, which are used for solving the technical problems in the background technology or at least partially solving the technical problems in the background technology.
In a first aspect, an embodiment of the present invention provides a single base station GNSS forward spoofing source positioning method, including:
acquiring deception signal information to obtain first satellite transmission time information according to the deception signal;
processing the first satellite transmitting time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information;
and processing the space-time double-difference observation vector information by a maximum likelihood estimation method to obtain final deception source position information.
In a second aspect, an embodiment of the present invention provides a single base station GNSS forwarding spoofing source positioning apparatus, including:
the acquisition module is used for acquiring deception signal information so as to obtain first satellite transmission time information according to the deception signal;
the processing module is used for processing the first satellite transmitting time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information;
and the positioning module is used for processing the space-time double-difference observation vector information through a maximum likelihood estimation method to obtain final deception source position information.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor, when executing the program, implements the steps of the single base station GNSS forward spoofing source locating method of the first aspect.
In a fourth aspect, embodiments of the present invention provide a non-transitory computer readable storage medium having a computer program stored thereon. The computer program when executed by a processor performs the steps of the single base station GNSS forward spoofing source locating method as described in the first aspect.
The embodiment of the invention provides a single-base-station GNSS forwarding type deception source positioning method and device. Obtaining first satellite transmission time information by processing a deception signal, respectively carrying out time difference and space difference on the first satellite transmission time information through a space-time double-difference observation model so as to obtain a space-time double-difference observation vector, and carrying out maximum likelihood estimation on deception source position information according to the space-time double-difference observation vector information; the embodiment of the invention can complete positioning through a single base station, the positioning precision is not influenced by the position of the base station, the position of the base station is not required to be known, and the method can be easily realized by a common receiver.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a flowchart illustrating a single base station GNSS forward spoofed source locating method according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating the variation of the maximum likelihood estimation error with the observation duration according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating another variation of maximum likelihood estimation error with observation duration according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating the variation of estimation error with observation duration according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating another variation of estimation error with observation duration according to an embodiment of the present invention;
FIG. 6 is a block diagram illustrating a single base station GNSS forward spoofing source locating device in accordance with an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of a single base station GNSS forward spoofing source positioning method according to an embodiment of the present invention, as shown in fig. 1, including:
and step 130, processing the space-time double-difference observation vector information by a maximum likelihood estimation method to obtain final deception source position information.
Specifically, in step 110, the spoofed signal information described in this embodiment of the present invention should include at least two satellite signals, and the forwarding delay information of different satellite signals is not changed, or the forwarding delay information change amounts of different satellite signals are the same.
The satellite clock error parameter information can be obtained by extracting and processing the deception signal information. The satellite signal emission time is corrected through the satellite clock error parameter information, so that corrected first satellite emission time information T is obtainedm(n)。
Tr(n)+ΔTr(n)-Tm(n)＝τm(n)+Dm+D0(n); formula one
Wherein, Tr(n)+ΔTr(n) is local time information, Tm(n) time information of the first satellite emission, τm(n) propagation time information of the signal from the satellite to the spoofing source; dmFor forwarding delay information, D0(n) propagation delay information of the signal from the spoofing source to the receiver;
and the forwarding delay information D in the formula ImDoes not change with time, so that the data can be eliminated by a time difference method, namely:
wherein, Tr(n)+ΔTr(n) is local time information, Tm(n) time information of the first satellite emission, τm(n) is signal propagation time information, (T)r(N)+ΔTr(N)-Tm(N)-D0(N)) is the signal propagation time at time N, τm(N) signal propagation time information at time N; dmFor forwarding delay information, D0And (N) is propagation delay information, wherein N is 1.
Due to local time, local clock error and propagation delay D0(n) is independent of satellite number and thus can be emptyRemoving the difference by a method to obtain
Wherein, M1, N1; (τ)M(n)-τM(N)) is the time differential distance of the M number satellite.
Therefore, Q ═ M-1 (N-1) double-difference observation equations can be obtained, and the space-time double-difference observation vector is recorded as y ∈ RQ×1I.e. by
Wherein y ism＝(ym(1)，ym(2)，...，ym(N-1))T∈R(N-1)×1(ii) a And the measurement noise q of the satellite emission timem(n) obey independent Gaussian distributions, i.e.
Mean vector
μm＝(μm(1)，μm(2)，...，μm(N-1))T∈R(N-1)×1Wherein
μm(n)＝τm(n)-τm(N)-(τM(n)-τM(N)); formula four
The matrix C belongs to RQ×QIs the covariance matrix of the space-time double-difference observation vector:
wherein, IN-1An identity matrix of order N-1, EN-1Representing a full 1-square matrix of order N-1, C being a square matrix of order (M-1) (N-1); and R is a real number set.
At the moment, the space-time double-difference observation vector obeys joint Gaussian distribution
In the observation of vector noise of
Then, a space-time double-difference observation model can be obtained:
y is mu + w; formula six
Step 130 is specifically to estimate the spoofed source location by space-time double-difference observation vector information and according to a Maximum Likelihood Estimation (MLE) method, where the Likelihood probability is:
then the MLE estimator of the spoofed source location information is:
let the objective function to be optimized be:
f(ps)＝(y-μ(ps))TC-1(y-μ(ps) ); equation eight
Let the gradient of the objective function with respect to the spoofed source location information vector be zero, resulting in:
namely, it is
(μ(ps)-y)TC-1J(ps)＝0T(ii) a Formula ten
The MLE estimate of the spoofed source location information vector can be obtained by solving the vector equation. But μ (p) in the equations) With respect to psIs non-linear and therefore cannot be directly determined, and needs to be set at an initial value p0Performing Taylor series expansion to obtain:
μ(ps)≈μ(p0)+J(p0)(ps-p0) (ii) a Formula eleven
Namely, it is
Then the iteration variation of the spoofed source location information at this time is:
in the iteration process, the spoofed source location information is:
ps＝p0+Δps(ii) a Fourteen formula
Wherein C is a square matrix of (M-1) (N-1) order; mu is a mean vector; y is a space-time double-difference observation vector; p is a radical of0To spoof source initial location information.
If the iteration variable quantity of the source position information is deceived | | | delta psIf | is greater than or equal to the preset threshold information, the step 130 is repeated until | Δ psAnd if the | | is smaller than the preset threshold information, the algorithm is converged, and the final deception source position information is obtained.
Extracting corrected first satellite transmission time information through a deception signal, respectively carrying out time difference and space difference on the first satellite transmission time information through a space-time double-difference observation model so as to obtain a space-time double-difference observation vector, and carrying out maximum likelihood estimation on deception source position information according to the space-time double-difference observation vector information; the embodiment of the invention can complete positioning through a single base station, the positioning precision is not influenced by the position of the base station, the position of the base station is not required to be known, and the method can be easily realized by a common receiver.
On the basis of the foregoing embodiment, the step of processing the space-time double-difference observation vector information by using a maximum likelihood estimation method to obtain final spoofed source location information specifically includes:
acquiring initial position information of a deception source and the space-time double-difference observation vector information;
obtaining observation vector change information according to the space-time double-difference observation vector information and the mean value vector information thereof;
obtaining the deception source position variable quantity information according to the deception source initial position information or the deception source position information after the last iteration update, the observation vector variable information and a maximum likelihood estimation method, and performing iteration update on the deception source position information according to the deception source position variable quantity;
and if the amount of change information of the deception source position is smaller than the preset threshold information, stopping iteratively updating the deception source position information to obtain the final deception source position information.
Specifically, the initial position information of the spoofing source in the embodiment of the present invention may be preset as needed. Because the spoofed source location information is continuously updated in the iterative process of the maximum likelihood estimation algorithm until convergence, the spoofed source location information does not directly influence the determination of the final spoofed source location information under the condition of algorithm convergence.
The spoofed source location variation information described in the embodiment of the present invention refers to spoofed source location variation information generated in an iterative process of a maximum likelihood estimation algorithm. In the iteration process, the initial position information of the deception source is used for the first iteration, and the deception source position information after the last iteration is updated is used later; and when the amount of change information of the deception source position is greater than or equal to the preset threshold, the iteration process still cannot be ended until the amount of change information of the deception source position is less than the preset threshold, the iteration is stopped, and the deception source position information when the iteration is stopped is used as the final deception source position information.
Obtaining the vector information mu (p) of the observed mean value according to the formula IVs) To observe the vector information y and the observation mean vector information mu (p) according to the space-time double differences) Obtaining observation vector change information delta y;
at the moment, obtaining the deception source position variable quantity information according to a formula thirteen, if the deception source position variable quantity information is larger than or equal to a preset threshold, continuing iteration until the deception source position variable quantity information is smaller than the preset threshold, and obtaining the final deception source position information; the preset threshold described herein may be preset as desired.
In the embodiment of the invention, in the process of estimating the deception source position information by a maximum likelihood estimation method, the final deception source position information is obtained by performing Taylor series expansion on the deception source initial position information and an iterative algorithm.
On the basis of the foregoing embodiment, the step of processing the first satellite transmission time information through the space-time double-difference observation model to obtain space-time double-difference observation vector information specifically includes:
processing the first satellite transmission time information to obtain:
Tr(n)+ΔTr(n)-Tm(n)＝τm(n)+Dm+D0(n); formula one
Wherein, Tr(n)+ΔTr(n) is local time information, Tm(n) time information of the first satellite emission, τm(n) propagation time information of the signal from the satellite to the spoofing source; dmFor forwarding delay information, D0(n) propagation delay information of the signal from the spoofing source to the receiver;
carrying out time difference processing on the formula I through a time difference method to obtain time difference result information, and processing the time difference result information through space difference to obtain space-time double difference result information;
and performing inverse number calculation on the space-time double-difference result information of the transmitting time to obtain space-time double-difference observation vector information.
Specifically, signal propagation time is obtained according to local time information and first satellite transmission time; and meanwhile, the signal propagation time is obtained according to the signal propagation time information, the forwarding time delay information and the propagation time delay information, so that a formula I is obtained. The first satellite transmission time herein refers to the satellite transmission time after correction.
When the deception source is static and the time delay information D is forwardedmIf not, the following formula can be obtained:
τm(n)＝Tr(n)+ΔTr(n)-Tm(n)-Dm-D0(n); equation fifteen
If time difference is performed, D in formula fifteen obtained according to formula one can be usedmAnd eliminating to obtain time difference result information, namely formula two:
since the method does not require reception of a real signal, there is no output of a real position and a local time synchronized with the satellite, so here the local time Tr(n) and clock difference parameter information Δ T thereofr(n) is unknown, and the local time, clock difference parameter information and propagation delay information D0(n) is independent of satellite number, and therefore can be eliminated by spatial differentiation, i.e., the time-differentiated distance τ of m satellites in the spoofed signal messagem(n)-τmAnd (N) respectively subtracting the time difference distance of the M number satellite to finally obtain a formula III.
When the spoofing source is stationary and the forwarding delay information variation Δ d (n) is the same, equation fifteen becomes:
τm(n)＝Tr(n)+ΔTr(n)-Tm(n)-Dm-ΔD(n)-D0(n); formula sixteen
Then, carrying out time difference and space difference according to a formula sixteenth to obtain a result the same as that of a formula III; where by doing spatial differentiation, we can cancel Δ d (n).
Therefore, the space-time double-difference observation model is feasible under the condition that the forwarding delay information is not changed or the forwarding delay information is the same in variation.
According to the formula III, Q ═ M-1 (N-1) double-difference observation equations are finally obtained, and the space-time double-difference observation vectors are recorded as y ∈ RQ×1I.e. by
Wherein y ism＝(ym(1),ym(2),...,ym(N-1))T∈R(N-1)×1。
According to the embodiment of the invention, the space-time double-difference observation model is used for processing the first satellite emission time, so that the space-time double-difference observation vector information can be obtained under the condition that the forwarding time delay applied by the deception source is unchanged or the variation is the same, and the subsequent steps can be favorably carried out.
On the basis of the above embodiment, before the step of obtaining the spoofed signal information, the method further includes:
acquiring signal information, wherein the signal information comprises deception signal information and real signal information;
and distinguishing the deception signal information and the real signal information by a preset detection method so as to identify the deception signal information.
Specifically, the preset detection method described in the embodiment of the present invention may include signal power detection, doppler detection, carrier consistency detection, signal arrival direction detection, and the like; the signal information is radio frequency information, the radio frequency information is processed by a down converter to obtain intermediate frequency information, and a digital intermediate frequency signal is obtained by a sampling device, wherein the digital intermediate frequency signal comprises deception signal information and real signal information. Because the invention does not need to track the real signal information, when the power of the deception signal is higher than the real signal, the single-peak capture can be carried out on the deception signal information, thereby obtaining the deception signal information.
The embodiment of the invention effectively identifies the deception signal information through signal power detection, and is beneficial to the implementation of the subsequent steps.
On the basis of the foregoing embodiment, the step of obtaining the first satellite transmission time information according to the spoofed signal specifically includes:
extracting and processing the deception signal information to obtain satellite clock error parameter information;
and correcting the second satellite transmission time information according to the satellite clock error parameter information to obtain the first satellite transmission time information.
Specifically, the second satellite transmission signal information described in the embodiment of the present invention refers to satellite transmission time information that is not corrected by clock offset; the size of the local clock difference parameter information described in the embodiments of the present invention may be different at different times.
The first satellite transmitting time information described in the embodiment of the invention is beneficial to the processing of a subsequent space-time double-difference observation model.
On the basis of the above embodiment, the step of iteratively updating the spoofed source location information according to the spoofed source location variation information specifically includes: adding the initial position information of the deception source and the variation information of the deception source position to iteratively update the information of the deception source position
And when the preset condition is met, iteratively converging to obtain the final deception source position information.
According to the space-time double-difference observation vector information, the position information of the final deception source is finally determined by utilizing a maximum likelihood estimation method.
Based on the above example, four sets of GPS survey data were recorded at different times of day 29/10/2018, each set having a duration of 30 minutes and data points spaced apart by 10.1 ms. The method comprises the following specific steps:
table 1 data set description
In table 1, there are a total of four sets of data sets in which the azimuth and elevation of the satellite are calculated from the perspective of the true location of the spoofed source. The first three datasets in the table all have observations of spoofed signals for 4 satellites. Observations for 6 satellites are in the fourth data set. And if the number of the satellites used for estimation is M, selecting observation data of the deception signals corresponding to the first M satellites in the data set to estimate the deception source position.
Fig. 2 is a diagram illustrating a variation of maximum likelihood estimation error with observation duration according to an embodiment of the present invention, as shown in fig. 2, which utilizes the first three data sets in table 1 to achieve positioning of a spoofing source based on the forwarded signals of 4 satellites, where the observation interval is 1.01 second. To make multiple estimates to evaluate the performance of the algorithm, we extracted sets of data at 1.01 second intervals from 30 minutes of data at 10.1 millisecond intervals. It can be seen that the estimation error under the three sets of test sets gradually decreases as the observation duration increases. Wherein the reduction is obvious from 1.01 min to 2.02 min, and the reduction reaches 600 m. Along with the increase of the data duration, the estimation error decreases gradually, reaches 200 meters at 3.03 minutes, and decreases to 90 meters at 5.05 minutes of observation duration. The estimation error is about 20 meters when the observation time is between 8.08 and 10.1 minutes. Therefore, the algorithm provided by the invention can effectively realize the estimation of the position of the deception source. Meanwhile, since the estimation algorithm precision is independent of the receiver position, the same estimation precision can still be obtained when the receiver is far away from or close to the deception source.
In order to evaluate the shortest observation time required by the estimation algorithm positioning, the estimation error under the condition of short observation time is tested in another experiment.
Fig. 3 is another variation diagram of maximum likelihood estimation error with observation duration according to an embodiment of the present invention, as shown in fig. 3, when the observation interval is 1.01 seconds, the estimation error gradually decreases with the increase of data duration, and the decrease from 5.05 seconds to 10.1 seconds is significant. When the observation time is 5 seconds, the estimation algorithm can still locate, but the estimation error is between 16 kilometers and 35 kilometers. When the observation time reaches 10 seconds, the estimation error is between 5 kilometers and 10 kilometers. When the observation time reaches 20 seconds, the estimation error is between 2 kilometers and 6 kilometers, and when the observation time reaches 40 seconds, the estimation error reaches about 1.5 kilometers. It can be seen that the estimation error is larger at shorter observation time. However, the position of the spoofed source output by the estimation algorithm provided by the invention is in the GPS coordinate system, that is, the positioning result is not the relative position of the receiver, but an absolute position. When the receiver is far away from the deception source, for example, hundreds of kilometers, if the deception signal can be received, the direction of the deception source can be roughly judged by observing the time length in 10 seconds. When the receiver is in the vicinity of the spoof source, a longer observation period is required if a more accurate relative position is desired. The algorithm proposed herein has no special requirements on the motion attitude of the receiver since it does not require the receiver to remain stationary, and therefore can be flexibly arranged. Because the estimation precision of the algorithm is not influenced by the position of the receiver, the position of the receiver has no special requirement, and the deception source positioning can be realized as long as the deception signal can be received.
FIG. 4 is a diagram illustrating the variation of estimation error with observation duration according to an embodiment of the present invention. As shown in fig. 4, which is the case where the spoofing source only forwards 2 or 3 signals, based on the first three data sets in table 1. Since the estimation error of the algorithm changes rapidly with time under the experimental environment, the change of the estimation error with time is drawn in a logarithmic coordinate system. In the figure, the notation "Data set 1-2" indicates the observation Data of the forwarded signals of the former two satellites selected from the Data set 1, and the other notations are similar. The upper three lines in the figure represent the estimation results for forwarding 2 signals, and the lower 3 lines represent the estimation results for forwarding 3 signals. The front part of the data points of some broken lines in the graph do not exist, because the estimation algorithm does not converge when the observation duration is short. As can be seen from the figure, the positioning performance of the spoofed source is drastically reduced when it forwards less than 4 satellite signals, but a smaller positioning error can be obtained by extending the observation time. In order to achieve an estimation accuracy of 4 km, the observation time for 2 forwarding signals needs to reach 25 minutes, and the observation time for 3 forwarding signals needs to reach 5 minutes. According to fig. 2 and 4, to achieve an estimation accuracy of 100 meters, the observation time for 4 transponders reaches 5 minutes, and the observation time for 3 transponders reaches 21 minutes.
FIG. 5 is another graph of estimation error versus observation duration, according to an embodiment of the present invention, as shown in FIG. 5, which shows the estimated performance for more than 4 satellites, and the experimental results are based on data set 4 in Table 1. The PRN numbers of the 6 satellites are 10,20,24,15,12 and 32, respectively, from which the first 4, 5, 6 transponders are selected for spoofing the estimation of the source location, respectively. As can be seen from the figure, when the observation time is short, increasing the number of satellites can significantly improve the estimation error. This is because the estimation accuracy can be significantly improved by increasing the number of satellites due to the short observation time and the large positioning error. When the observation time is longer, the estimation error is not improved obviously after the number of satellites is increased. This is because the estimation error is smaller with a longer observation time, so that the improvement of the estimation accuracy is less affected by the increase of the number of satellites.
Fig. 6 is a schematic structural diagram of a single-base-station GNSS forwarding spoofing source positioning apparatus according to an embodiment of the present invention, as shown in fig. 6, including: an acquisition module 610, a processing module 620 and a positioning module 630;
the obtaining module 610 is configured to obtain spoofed signal information, so as to obtain first satellite transmission time information according to the spoofed signal;
the processing module 620 is configured to process the first satellite transmission time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information;
the positioning module 630 is configured to process the space-time double-difference observation vector information by using a maximum likelihood estimation method to obtain final deception source location information.
The apparatus provided in the embodiment of the present invention is used for executing the above method embodiments, and for details of the process and the details, reference is made to the above embodiments, which are not described herein again.
According to the method, time difference and space difference are respectively carried out on the first satellite transmission time information through a space-time double-difference observation model so as to obtain a space-time double-difference observation vector, and then maximum likelihood estimation is carried out on deception source position information according to the space-time double-difference observation vector information; the embodiment of the invention can complete positioning through a single base station, the positioning precision is not influenced by the position of the base station, the position of the base station is not required to be known, and the method can be easily realized by a common receiver.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the invention. As shown in fig. 7, the electronic device may include: a processor (processor)701, a communication Interface (Communications Interface)702, a memory (memory)703 and a communication bus 704, wherein the processor 701, the communication Interface 702 and the memory 703 complete communication with each other through the communication bus 704. The processor 701 may call logic instructions in the memory 703 to perform the following method: acquiring deception signal information to obtain first satellite transmission time information according to the deception signal; processing the first satellite transmitting time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information; and processing the space-time double-difference observation vector information by a maximum likelihood estimation method to obtain final deception source position information.
In addition, the logic instructions in the memory 703 can be stored in a computer readable storage medium when they are implemented in the form of software functional units and sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
An embodiment of the invention discloses a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions. When the program instructions are executed by a computer, the computer can execute the method provided by the method embodiments, for example, the method comprises the following steps: acquiring deception signal information to obtain first satellite transmission time information according to the deception signal; processing the first satellite transmitting time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information; and processing the space-time double-difference observation vector information by a maximum likelihood estimation method to obtain final deception source position information.
Embodiments of the present invention provide a non-transitory computer-readable storage medium storing server instructions that cause a computer to perform the methods provided by the above embodiments, including, for example: acquiring deception signal information to obtain first satellite transmission time information according to the deception signal; processing the first satellite transmitting time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information; and processing the space-time double-difference observation vector information by a maximum likelihood estimation method to obtain final deception source position information.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A single base station GNSS forwarding type deception source positioning method is characterized by comprising the following steps:
acquiring deception signal information to obtain first satellite transmission time information according to the deception signal;
processing the first satellite transmitting time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information;
processing the space-time double-difference observation vector information by a maximum likelihood estimation method to obtain final deception source position information;
the step of processing the first satellite transmission time information through the space-time double-difference observation model to obtain space-time double-difference observation vector information specifically includes:
processing the first satellite transmission time information to obtain:
Tr(n)+ΔTr(n)-Tm(n)＝τm(n)+Dm+D0(n); formula one
Wherein, Tr(n)+ΔTr(n) is local time information, Tm(n) time information of the first satellite emission, τm(n) propagation time information of the signal from the satellite to the spoofing source, DmFor forwarding delay information, D0(n) propagation delay information of the signal from the spoofing source to the receiver;
carrying out time difference processing on the formula I through a time difference method to obtain time difference result information, and processing the time difference result information through space difference to obtain space-time double difference result information;
wherein, Tr(n)+ΔTr(n) is local time information, Tm(n) time information of the first satellite emission, τm(n) is signal propagation time information, (T)r(N)+ΔTr(N)-Tm(N)-D0(N)) is the signal propagation time at time N, τm(N) signal propagation time information at time N; dmFor forwarding delay information, D0(N) is propagation delay information, N is 1.
Local time, local clock error and propagation delay D by space difference method0(n) elimination, yielding:
wherein, M1, N1; (τ)M(n)-τM(N)) is the time differential distance of the M number satellite;
obtaining Q ═ M-1 (N-1) double-difference observation equations, and recording the space-time double-difference observation vector as y ∈ RQ×1I.e. by
Wherein y ism＝(ym(1),ym(2),...,ym(N-1))T∈R(N-1)×1(ii) a And the measurement noise q of the satellite emission timem(n) obey independent Gaussian distributions, i.e.
Mean vector
Wherein
μm(n)＝τm(n)-τm(N)-(τM(n)-τM(N)); formula four
The matrix C belongs to RQ×QIs the covariance matrix of the space-time double-difference observation vector:
wherein, IN-1An identity matrix of order N-1, EN-1Representing a full 1-square matrix of order N-1, C being a square matrix of order (M-1) (N-1); r is a real number set;
at the moment, the space-time double-difference observation vector obeys joint Gaussian distribution
In the observation of vector noise of
Then, a space-time double-difference observation model can be obtained:
y is mu + w; formula six
And performing phase inversion calculation on the space-time double-difference result information of the emission time, and forming a vector by phase inversion calculation results of different satellites at different times to obtain space-time double-difference observation vector information.
2. The method according to claim 1, wherein the step of processing the space-time double-difference observation vector information by a maximum likelihood estimation method to obtain final spoofed source location information specifically includes:
acquiring initial position information of a deception source and the space-time double-difference observation vector information;
obtaining observation vector change information according to the space-time double-difference observation vector information and the mean value vector information thereof;
obtaining the deception source position variable quantity information according to the deception source initial position information, the observation vector variable information and a maximum likelihood estimation method, and performing iterative updating on the deception source position information according to the deception source position variable quantity information;
and if the amount of change information of the deception source position is smaller than the preset threshold information, stopping iteratively updating the deception source position information to obtain the final deception source position information.
3. The method of claim 1, wherein the step of obtaining spoof signal information is preceded by the method further comprising:
acquiring signal information, wherein the signal information comprises deception signal information and real signal information;
and distinguishing the deception signal information and the real signal information by a preset detection method so as to identify the deception signal information.
4. The method according to claim 1, wherein the step of obtaining the first satellite transmission time information based on the spoofed signal specifically comprises:
extracting and processing the deception signal information to obtain satellite clock error parameter information and second satellite transmission time information;
and correcting the second satellite transmission time information according to the clock difference parameter information to obtain the first satellite transmission time information.
5. The method according to claim 2, wherein the step of iteratively updating the spoofed source location information according to the spoofed source location variation information specifically includes:
adding the initial position information of the deception source and the variable quantity information of the deception source position to iteratively update the information of the deception source position;
and when the preset condition is met, iteratively converging to obtain the final deception source position information.
6. A single base station GNSS forwarded spoofing source locating device comprising:
the acquisition module is used for acquiring deception signal information so as to obtain first satellite transmission time information according to the deception signal;
the processing module is used for processing the first satellite transmitting time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information;
the positioning module is used for processing the space-time double-difference observation vector information through a maximum likelihood estimation method to obtain final deception source position information;
the method comprises the following steps of processing the first satellite transmission time information through a space-time double-difference observation model to obtain space-time double-difference observation vector information, and specifically comprises the following steps:
processing the first satellite transmission time information to obtain:
Tr(n)+ΔTr(n)-Tm(n)＝τm(n)+Dm+D0(n); formula one
Wherein, Tr(n)+ΔTr(n) is local time information, Tm(n) time information of the first satellite emission, τm(n) propagation time information of the signal from the satellite to the spoofing source, DmFor forwarding delay information, D0(n) propagation delay information of the signal from the spoofing source to the receiver;
carrying out time difference processing on the formula I through a time difference method to obtain time difference result information, and processing the time difference result information through space difference to obtain space-time double difference result information;
wherein, Tr(n)+ΔTr(n) is local time information, Tm(n) time information of the first satellite emission, τm(n) is signal propagation time information, (T)r(N)+ΔTr(N)-Tm(N)-D0(N)) is the signal propagation time at time N, τm(N) signal propagation time information at time N; dmFor forwarding delay information, D0(n) is propagationTime delay information, N1., N-1;
local time, local clock error and propagation delay D by space difference method0(n) elimination, yielding:
wherein, M1, N1; (τ)M(n)-τM(N)) is the time differential distance of the M number satellite;
obtaining Q ═ M-1 (N-1) double-difference observation equations, and recording the space-time double-difference observation vector as y ∈ RQ×1I.e. by
Wherein y ism＝(ym(1),ym(2),...,ym(N-1))T∈R(N-1)×1(ii) a And the measurement noise q of the satellite emission timem(n) obey independent Gaussian distributions, i.e.
Mean vector
μm＝(μm(1),μm(2),...,μm(N-1))T∈R(N-1)×1Wherein
μm(n)＝τm(n)-τm(N)-(τM(n)-τM(N)); formula four
The matrix C belongs to RQ×QIs the covariance matrix of the space-time double-difference observation vector:
wherein, IN-1An identity matrix of order N-1, EN-1Representing a full 1-square matrix of order N-1, C being a square matrix of order (M-1) (N-1);r is a real number set;
at the moment, the space-time double-difference observation vector obeys joint Gaussian distribution
In the observation of vector noise of
Then, a space-time double-difference observation model can be obtained:
y is mu + w; formula six
And performing phase inversion calculation on the space-time double-difference result information of the emission time, and forming a vector by phase inversion calculation results of different satellites at different times to obtain space-time double-difference observation vector information.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the single base station GNSS forwarded spoof source locating method of any of claims 1 through 5.
8. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, performs the steps of the single base station GNSS forwarded spoofing source locating method as recited in any of claims 1 to 5.
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| EP2746813A1 (en) * | 2012-12-21 | 2014-06-25 | Astrium GmbH | Detection of spoofing of GNSS navigation signals |
| CN104656104A (en) * | 2015-02-27 | 2015-05-27 | 清华大学 | Satellite navigation deceptive signal identification method and system based on maximum likelihood estimation |
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| EP2746813A1 (en) * | 2012-12-21 | 2014-06-25 | Astrium GmbH | Detection of spoofing of GNSS navigation signals |
| CN104656104A (en) * | 2015-02-27 | 2015-05-27 | 清华大学 | Satellite navigation deceptive signal identification method and system based on maximum likelihood estimation |
| CN106772456A (en) * | 2017-01-12 | 2017-05-31 | 清华大学 | A kind of relay type based on multi-user Cooperation cheats the localization method in source |
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