CN115061158A - Deception jamming detection method, device, terminal and medium based on altimeter - Google Patents
Deception jamming detection method, device, terminal and medium based on altimeter Download PDFInfo
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- 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 provides a deception jamming detection method, a deception jamming detection device, a terminal and a medium based on an altimeter, wherein the method comprises the following steps: acquiring detection parameters of a barometric altimeter and detection parameters of a GNSS (global navigation satellite system); based on an ARIMA model, respectively denoising the detection parameters of the barometric altimeter and the detection parameters of the GNSS to obtain a first altitude corresponding to the barometric altimeter and a second altitude corresponding to the GNSS; and comparing the first height with the second height to determine whether a deception signal exists. Compared with the prior art, the method has the advantages that detection parameters of the barometric altimeter and detection parameters of the GNSS are combined, deception signals and real signals are distinguished on altitude data, the generated deception signals and the forwarded deception interference are well detected, the detection stability is improved, and the real signals are effectively reserved.
Description
Technical Field
The invention relates to the field of deception signal detection, in particular to a deception jamming detection method, a deception jamming detection device, a deception jamming detection terminal and a deception jamming detection medium based on an altimeter.
Background
At present, a deception signal emitted by a deception jamming source is very similar to a real signal, a user receiver is easily deceived, a user obtains wrong time and position, and the deception jamming signal is the same as a spreading code of the real signal, so that the deception signal mixed in the real signal is difficult to screen by adopting a RAIM algorithm. In the prior art, methods for detecting GNSS spoofing interference include a C/NO detection method, a signal arrival time detection method, and the like. The C/NO detection method finds the presence of a spoof signal by detecting an abnormal change in C/NO. But when the spoofed signal is transmitted with noise, it is liable to cause erroneous judgment. The signal arrival time detection aims at the problem that the distance of the repeater spoofing interference to a receiver is longer than that of a real signal, and the repeater spoofing interference forms a time difference so as to judge whether a spoofing signal exists or not.
Disclosure of Invention
The invention provides a deception jamming detection method, a deception jamming detection device, a deception jamming detection terminal and a deception jamming detection medium based on an altimeter, wherein detection parameters of the altimeter are used as a basis, and the detection accuracy is improved through comparison and analysis based on the altitude difference between the altimeter and a GNSS.
In order to solve the above technical problem, an embodiment of the present invention provides a spoofing interference detection method based on an altimeter, including:
acquiring detection parameters of a barometric altimeter and detection parameters of a GNSS (global navigation satellite system);
based on an ARIMA model, respectively denoising the detection parameters of the barometric altimeter and the detection parameters of the GNSS to obtain a first altitude corresponding to the barometric altimeter and a second altitude corresponding to the GNSS;
and comparing the first height with the second height to determine whether a deception signal exists.
As a preferred scheme, the ARIMA model is specifically an ARMIA (p, d, q) model:
Φ(L)Δ d x t ＝δ+Θ(L)ε t ；
Δ＝1-L；
wherein, { x t Is the time sequence, L is the backshifting operator, { ε t White noise subject to a standard normal distribution, t 1,2, N being the time series length, p, d, q being the order of the ARIMA (p, d, q) model, Φ (L), Δ, and Θ (L) being intermediate variables.
As a preferred scheme, the comparing the first height and the second height to determine whether a spoofing signal exists specifically includes:
calculating Euclidean distances of a first height and a second height, comparing the Euclidean distances with a preset threshold value, and determining that a deception signal exists when the Euclidean distances are larger than or equal to the preset threshold value; and when the Euclidean distance is smaller than the preset threshold value, determining that no deception signal exists.
Preferably, before the acquiring the barometric altimeter detection parameters and the GNSS detection parameters, the method further includes:
acquiring measurement data of a barometric altimeter and measurement data of a GNSS (global navigation satellite system), and performing difference processing on the measurement data of the barometric altimeter and the measurement data of the GNSS to obtain detection parameters of the barometric altimeter and the detection parameters of the GNSS.
Correspondingly, the embodiment of the invention also provides a deception jamming detection device based on the altimeter, which comprises a parameter acquisition module, a noise reduction module and a comparison analysis module, wherein,
the parameter acquisition module is used for acquiring detection parameters of the barometric altimeter and GNSS detection parameters;
the noise reduction module is used for respectively reducing noise of the detection parameters of the barometric altimeter and the detection parameters of the GNSS based on an ARIMA model to obtain a first height corresponding to the barometric altimeter and a second height corresponding to the GNSS;
the comparison analysis module is used for comparing the first height and the second height to determine whether a deception signal exists.
As a preferred scheme, the ARIMA model is specifically an arimia (p, d, q) model:
Φ(L)Δ d x t ＝δ+Θ(L)ε t ；
Δ＝1-L；
wherein, { x t Is the time sequence, L is the backshifting operator, { ε t White noise subject to a standard normal distribution, t 1,2, N being the time series length, p, d, q being the order of the ARIMA (p, d, q) model, Φ (L), Δ, and Θ (L) being intermediate variables.
As a preferred scheme, the comparing and analyzing module compares the first height and the second height to determine whether a spoofing signal exists, specifically:
the comparison analysis module calculates Euclidean distances of a first height and a second height, compares the Euclidean distances with a preset threshold value, and determines that a deception signal exists when the Euclidean distances are larger than or equal to the preset threshold value; and when the Euclidean distance is smaller than the preset threshold value, determining that no deception signal exists.
As a preferable scheme, the spoofed interference detecting device further includes a preprocessing module, where the preprocessing module is configured to obtain the altimeter measurement data and the GNSS measurement data before obtaining the altimeter detection parameter and the GNSS detection parameter, and perform difference processing on the altimeter measurement data and the GNSS measurement data to obtain the altimeter detection parameter and the GNSS detection parameter.
Correspondingly, the embodiment of the present invention further provides a terminal, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the altimeter-based spoof-jamming detection method when executing the computer program.
The embodiment of the invention also provides a computer-readable storage medium, which comprises a stored computer program, wherein when the computer program runs, the device where the computer-readable storage medium is located is controlled to execute the deception jamming detection method based on the altimeter.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
the embodiment of the invention provides a deception jamming detection method, a deception jamming detection device, a deception jamming detection terminal and a deception jamming detection medium based on an altimeter, wherein the method comprises the following steps: acquiring detection parameters of a barometric altimeter and detection parameters of a GNSS (global navigation satellite system); based on an ARIMA model, respectively denoising the detection parameters of the barometric altimeter and the detection parameters of the GNSS to obtain a first altitude corresponding to the barometric altimeter and a second altitude corresponding to the GNSS; and comparing the first height with the second height to determine whether a deception signal exists. Compared with the prior art, the method has the advantages that detection parameters of the barometric altimeter and detection parameters of the GNSS are combined, deception signals and real signals are distinguished on altitude data, the generated deception signals and the forwarded deception interference are well detected, the detection stability is improved, and the real signals are effectively reserved.
Furthermore, when the GNSS receives the deception signal, the second height fluctuates greatly, and the validity of the detection method can be improved by adding threshold detection.
Furthermore, the measurement data of the baro-altimeter and the measurement data of the GNSS are processed into detection parameters of the baro-altimeter and detection parameters of the GNSS through differential processing, so that the applicability of the data to an ARMIA (p, d, q) model can be increased, and a better identification effect can be obtained.
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FIG. 1: the invention provides a flow schematic diagram of an embodiment of a deception jamming detection method based on an altimeter.
FIG. 2: the invention provides a schematic structural diagram of an embodiment of a deception jamming detection device based on an altimeter.
Detailed Description
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, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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.
The first embodiment is as follows:
referring to fig. 1, fig. 1 shows a spoofing interference detecting method based on an altimeter according to an embodiment of the present invention, which includes steps S1 to S3, wherein,
step S1, acquiring the detection parameters of the barometric altimeter and the detection parameters of the GNSS.
In this embodiment, the measurement data of the baro-altimeter and the measurement data of the GNSS are obtained first. And pre-processing the measurement data of the barometric altimeter and the measurement data of the GNSS, optionally:
and respectively carrying out difference processing on the measurement data of the barometric altimeter and the measurement data of the GNSS until the data are stable, thereby obtaining the detection parameters of the barometric altimeter and the detection parameters of the GNSS.
Step S2, based on the ARIMA model, performing noise reduction on the barometric altimeter detection parameter and the GNSS detection parameter respectively, to obtain a first altitude corresponding to the barometric altimeter and a second altitude corresponding to the GNSS.
In this embodiment, first, error analysis is performed on a carrier such as a mobile phone as a receiver to construct a carrier motion model. Establishing the carrier motion model in the vertical direction by adopting a target tracking method:
h k ＝h a +δ k ；
wherein h is k As the true height information of the carrier, n a Is white noise, τ a Correlation time, δ, for first order Markov k For height measurement error, h a Is the ideal movement height of the carrier,
the motion acceleration of the carrier can be regarded as a stable first-order Markov process with zero mean value,
is the derivative of the acceleration of motion of the carrier.
Secondly, an error model of the barometric altimeter is constructed. The vertical distance from the position of the carrier to the ground level is generally defined as the altitude, which corresponds to the atmospheric pressure in the case of a standardized distribution of atmospheric pressure and temperature. And the altitude measurement equation for a barometric altimeter can be expressed as:
H k ＝h a +n s +γ b +ζ q ；
wherein n is s White noise, mainly errors caused by changes in motion state and system quantization noise.
ζ q The first-order Markov noise is mainly random drift caused by the error of an air pressure measurement algorithm, and meets the following requirements:
wherein, tau b The correlation time for this first order Markov noise is generally determined by the speed of motion of the carrier and the range of motion, n q The error caused by the quantization effect of the system can be considered as white noise. The smaller the correlation time, the closer the first order gaussian-markov process approaches the white noise performance (changes frequently), and the larger the correlation time, the closer the first order gaussian-markov process approaches the random walk performance (changes slowly). The correlation time can be specifically set according to specific situations, for example, the correlation time can be set according to a time scale of estimating zero offset under a typical motion condition of the carrier.
In addition, the altitude error measured by the barometric altimeter also includes a random constant value gamma b Generally, it can be approximately considered as a constant value when the altitude is below 50 km. In this embodiment, the random constant value is 0.
Then a GNSS error model. The GPS/BDS employs the WGS-84/CGCS2000 geodetic frame (the protodetic geodetic frame) and the GPS satellite ephemeris is referenced to the WGS-84 frame, so the coordinates of the GPS single-point fix and the baseline vector resolved in the relative position fix belong to the WGS-84 geodetic frame. The practical measurement result usually belongs to a national coordinate system or a local coordinate system (i.e. a local reference coordinate system), so that coordinate conversion is necessary.
And the vertical distance of the carrier position relative to the reference ellipsoid is the ellipsoid height, i.e. the geodetic height H p And the height difference from the ground level surface is the height difference delta h.
And h is due to the fact that the normal of the ellipsoid is not consistent with the vertical line a B is not completely equal to H p . However, the difference between the two is very slight, so this example is similar to H p ＝h k And +. DELTA.h. Generally, the default user locationThe position of the carrier is obtained by calculation, and the coordinate position of the carrier is converted into altitude information under a user coordinate system. The height measurement equation of the GNSS can now be simplified as:
H w ＝h k +n s ；
wherein H w For approximate altitude of GNSS, n s The noise introduced for the measurement is considered white noise.
As can be seen from the above analysis, in an actual situation, noise exists in the directly obtained barometric altimeter data and GNSS data, which affects the final detection result, and therefore, an ARIMA model is used to perform noise reduction processing on the signal.
For any generalized stationary stochastic process, an ARMA (n, m) model process of a certain order can be used for description. Assume a stationary, normal, zero-mean time series { x } t 1, 2.. times.n, then the corresponding ARMA (N, m) model is:
wherein phi is 1 ，φ 2 ，…，φ p As model autoregressive parameter, theta 1 ，θ 2 ，…，θ 1 As a model moving average parameter, { ε t Is white noise and follows a standard normal distribution. p, q are ARMA (p, q) model orders, and N is the time series length.
But in practice, the time series x considered t The stationary, normal and zero mean 3 conditions cannot be satisfied simultaneously. Thus for { x t D-order differentiation is performed. Then the original sequence is converted into an ARIMA (p, d, q) model, and the expression is as follows:
Φ(L)Δ d x t ＝δ+Θ(L)ε t ；
Δ＝1-L；
wherein, { x t Is a time sequence, { ε t White noise subject to a standard normal distribution, t 1,2, N being the time series length, p, d, q being the order of the ARIMA (p, d, q) model, Φ (L), Δ, and Θ (L) being intermediate variables, L being a back-shift operator, i.e., Lx t ＝x t-1 。
Random noise in signals of a GNSS satellite navigation system and a barometric altimeter can be effectively inhibited through the improved ARIMA model algorithm. Specifically, an ARMA model is established for the detection parameters of the barometric altimeter and the detection parameters of the GNSS, the modeling process performs order determination on the model through criteria such as AIC, preferably ARIMA (1,1,1) is an applicable model of a first-order difference altitude signal between a GNSS satellite navigation system and the barometric altimeter, and then a first altitude corresponding to the barometric altimeter and a second altitude corresponding to the GNSS are obtained.
And step S3, comparing the first height and the second height to determine whether a deception signal exists.
In this embodiment, the euclidean distance between the first height and the second height is calculated, the euclidean distance is compared with a preset threshold value, and when the euclidean distance is greater than or equal to the preset threshold value, it is determined that a spoof signal exists; and when the Euclidean distance is smaller than the preset threshold value, determining that no deception signal exists.
As is known in the art, X is { X ═ for a point X i Y and point Y ═ Y i The euclidean distance algorithm is as follows:
And substituting the first height and the second height into X and Y respectively to obtain the Euclidean distance between the detection height of the barometric altimeter and the detection height of the GNSS.
When the Euclidean distance between the detection altitude of the barometric altimeter and the detection altitude of the GNSS (namely the Euclidean distance between the first altitude and the second altitude) is larger than or equal to a threshold value, determining that a deception signal exists; and when the Euclidean distance is smaller than the preset threshold value, determining that no deception signal exists.
As an example of this embodiment, the following experiment may be designed to verify whether a satellite signal received by a receiver has a spoofed signal:
in the experiment, real satellite signals are broadcast in the first half of the time when the receiver receives the signals, deception satellite signals are added in the second half of the time, and the height data change is observed. In the first half of the experiment, it was basically confirmed that the height data fluctuated within a small range. When a deception signal is added, the satellite altitude data of the GNSS received by the receiver obviously jumps, and the altimeter data has no large fluctuation before and after the deception signal is added.
In the normal positioning stage, the actual altitude measured by the real satellite and the altitude measured by the barometric altimeter generally do not differ by more than 1 meter, and after the deceptive signal is added, the satellite altitude data fluctuates greatly, for example, tens of meters, and the barometric altitude data still has no obvious change. Based on this, we can set the threshold to be 1.5 meters, 2 meters, 3 meters, etc. Furthermore, when the Euclidean distance between the altitude measured by the real satellite signal and the altitude measured by the barometric altimeter is smaller than a threshold value, the deception signal is not considered to exist. And when the Euclidean distance between the altitude measured by the real satellite signal and the altitude measured by the barometric altimeter is larger than a preset threshold value, determining that a deception signal exists.
Correspondingly, referring to fig. 2, the embodiment further provides an altimeter-based spoofing interference detecting apparatus, which includes a parameter obtaining module 101, a noise reduction module 102 and a comparison analysis module 103, wherein,
the parameter acquiring module 101 is configured to acquire a detection parameter of the barometric altimeter and a detection parameter of the GNSS;
the denoising module 102 is configured to denoise the barometric altimeter detection parameter and the GNSS detection parameter respectively based on an ARIMA model, and obtain a first altitude corresponding to the barometric altimeter and a second altitude corresponding to the GNSS;
the comparison analysis module 103 is configured to compare the first height and the second height, and determine whether a spoofing signal exists.
Preferably, the ARIMA model is in particular an ARMIA (p, d, q) model:
Φ(L)Δ d x t ＝δ+Θ(L)ε t ；
Δ＝1-L；
wherein, { x t Is the time sequence, L is the backshifting operator, { ε t White noise subject to a standard normal distribution, t 1,2, N being the time series length, p, d, q being the order of the ARIMA (p, d, q) model, Φ (L), Δ, and Θ (L) being intermediate variables.
Illustratively, the comparison analysis module 103 compares the first height and the second height to determine whether a spoofing signal exists, specifically:
the comparison analysis module 103 calculates euclidean distances between the first height and the second height, compares the euclidean distances with a preset threshold value, and determines that a spoof signal exists when the euclidean distances are greater than or equal to the preset threshold value; and when the Euclidean distance is smaller than the preset threshold value, determining that no deception signal exists.
In this embodiment, the spoofed interference detecting device further includes a preprocessing module, where the preprocessing module is configured to obtain the altimeter measurement data and the GNSS measurement data before obtaining the altimeter detection parameter and the GNSS detection parameter, and perform difference processing on the altimeter measurement data and the GNSS measurement data to obtain the altimeter detection parameter and the GNSS detection parameter.
Correspondingly, the embodiment of the invention also provides a terminal, which comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the deception jamming detection method based on the altimeter when executing the computer program.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is the control center of the terminal and connects the various parts of the overall terminal using various interfaces and lines.
The memory may be used to store the computer program, and the processor may implement various functions of the terminal by executing or executing the computer program stored in the memory and calling data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Correspondingly, the embodiment of the invention also provides a computer-readable storage medium, which comprises a stored computer program, wherein when the computer program runs, a device where the computer-readable storage medium is located is controlled to execute the deception jamming detection method based on the altimeter.
Wherein, the module integrated by the deception jamming detection device based on the altimeter can be stored in a computer readable storage medium if the module is realized in the form of a software functional unit and sold or used as a separate product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
the embodiment of the invention provides a deception jamming detection method, a deception jamming detection device, a deception jamming detection terminal and a deception jamming detection medium based on an altimeter, wherein the method comprises the following steps: acquiring detection parameters of a barometric altimeter and detection parameters of a GNSS (global navigation satellite system); based on an ARIMA model, respectively denoising the detection parameters of the barometric altimeter and the detection parameters of the GNSS to obtain a first altitude corresponding to the barometric altimeter and a second altitude corresponding to the GNSS; and comparing the first height with the second height to determine whether a deception signal exists. Compared with the prior art, the method has the advantages that detection parameters of the barometric altimeter and detection parameters of the GNSS are combined, deception signals and real signals are distinguished on altitude data, the generated deception signals and the forwarded deception interference are well detected, the detection stability is improved, and the real signals are effectively reserved.
Furthermore, when the GNSS receives the deception signal, the second height fluctuates greatly, and the validity of the detection method can be improved by adding threshold detection.
Furthermore, the measurement data of the baro-altimeter and the measurement data of the GNSS are processed into detection parameters of the baro-altimeter and detection parameters of the GNSS through differential processing, so that the applicability of the data to an ARMIA (p, d, q) model can be increased, and a better identification effect can be obtained.
The above-mentioned embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, and it should be understood that the above-mentioned embodiments are only examples of the present invention and are not intended to limit the scope of the present invention. It should be understood that any modifications, equivalents, improvements and the like, which come within the spirit and principle of the invention, may occur to those skilled in the art and are intended to be included within the scope of the invention.
Claims (10)
1. An altimeter-based spoof-jamming detection method, comprising:
acquiring detection parameters of a barometric altimeter and detection parameters of a GNSS (global navigation satellite system);
based on an ARIMA model, respectively denoising the detection parameters of the barometric altimeter and the detection parameters of the GNSS to obtain a first altitude corresponding to the barometric altimeter and a second altitude corresponding to the GNSS;
and comparing the first height with the second height to determine whether a deception signal exists.
2. An altimeter-based deception jamming detection method according to claim 1, characterized in that said ARIMA model is specifically an ARIMA (p, d, q) model:
Φ(L)Δ d x t ＝δ+Θ(L)ε t ；
Δ＝1-L；
wherein, { x t Is the time series, L is the backshifting operator, { ε t White noise subject to a standard normal distribution, t 1,2, N being the time series length, p, d, q being the order of the ARIMA (p, d, q) model, Φ (L), Δ, and Θ (L) being intermediate variables.
3. The method as claimed in claim 1, wherein the comparing process is performed on the first altitude and the second altitude to determine whether a spoof signal exists, specifically:
calculating Euclidean distances of a first height and a second height, comparing the Euclidean distances with a preset threshold value, and determining that a deception signal exists when the Euclidean distances are larger than or equal to the preset threshold value; and when the Euclidean distance is smaller than the preset threshold value, determining that no deception signal exists.
4. The altimeter-based spoof-jamming detection method of any one of claims 1-3, further comprising, prior to said obtaining barometric altimeter sensed parameters and GNSS sensed parameters:
acquiring measurement data of a barometric altimeter and measurement data of a GNSS (global navigation satellite system), and performing difference processing on the measurement data of the barometric altimeter and the measurement data of the GNSS to obtain detection parameters of the barometric altimeter and the detection parameters of the GNSS.
5. A deception jamming detection device based on an altimeter is characterized by comprising a parameter acquisition module, a noise reduction module and a comparison analysis module, wherein,
the parameter acquisition module is used for acquiring detection parameters of the barometric altimeter and GNSS detection parameters;
the noise reduction module is used for respectively reducing noise of the detection parameters of the barometric altimeter and the detection parameters of the GNSS based on an ARIMA model to obtain a first height corresponding to the barometric altimeter and a second height corresponding to the GNSS;
the comparison analysis module is used for comparing the first height and the second height to determine whether a deception signal exists.
6. An altimeter-based spoof interference detecting device as recited in claim 5, wherein said ARIMA model is specifically ARMIA (p, d, q) model:
Φ(L)Δ d x t ＝δ+Θ(L)ε t ；
Δ＝1-L；
wherein, { x t Is the time sequence, L is the backshifting operator, { ε t White noise subject to a standard normal distribution, t 1,2, N being the time series length, p, d, q being the order of the ARIMA (p, d, q) model, Φ (L), Δ, and Θ (L) being intermediate variables.
7. The apparatus of claim 5, wherein the comparison analysis module compares the first altitude with the second altitude to determine whether a spoof signal exists, specifically:
the comparison analysis module calculates Euclidean distances of a first height and a second height, compares the Euclidean distances with a preset threshold value, and determines that a deception signal exists when the Euclidean distances are larger than or equal to the preset threshold value; and when the Euclidean distance is smaller than the preset threshold value, determining that no deception signal exists.
8. The altimeter-based spoof-interference detecting device of any one of claims 5-7, further comprising a preprocessing module, wherein said preprocessing module is configured to obtain the altimeter measurement data and the GNSS measurement data before said obtaining the altimeter detection parameters and the GNSS detection parameters, and to perform a difference processing on the altimeter measurement data and the GNSS measurement data to obtain the altimeter detection parameters and the GNSS detection parameters.
9. A terminal comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor when executing the computer program implementing the altimeter-based spoofed jamming detection method of any one of claims 1-4.
10. A computer-readable storage medium, comprising a stored computer program, wherein the computer program when executed controls an apparatus in which the computer-readable storage medium is located to perform the altimeter-based spoof interference detection method of any one of claims 1 to 4.
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