A method and device for detecting spoofing signals based on pseudo-range rate of Beidou satellite navigation system

Abstract

The disclosed embodiment is a method and device for detecting spoofing signals based on the pseudorange rate of the Beidou satellite navigation system. The method includes: obtaining the measured pseudorange rate according to the carrier phase value actually observed by the receiver, and obtaining the calibrated pseudorange rate according to the speed information provided by the inertial navigation system; differentiating the measured pseudorange rate from the calibrated pseudorange rate to obtain a statistical detection amount; establishing a test of no deceptive interference and the presence of deceptive interference according to the statistical detection amount, obtaining a probability distribution function of no deceptive interference and a probability distribution function of the presence of deceptive interference; obtaining a deceptive signal detection threshold through the probability distribution function of no deceptive interference, and obtaining an actual detection probability through the probability distribution function of the presence of deceptive interference; judging whether the information received by the receiver is a deceptive signal according to the deceptive signal detection threshold and the actual detection probability. The disclosed embodiment utilizes the characteristic that the velocity drift of the inertial navigation is not obvious in a short period of time to construct a test statistic and effectively detect deceptive signals.

Description

Technical Field

[0001] The disclosed embodiments relate to the technical field of satellite navigation spoofing detection, and more particularly to a spoofing signal detection method and device based on the pseudorange rate of a Beidou satellite navigation system. Background Art

[0002] Deceptive jamming forwards or autonomously generates deceptive signals that are highly similar to real signals, inducing the BeiDou Navigation Satellite System (BDS) to achieve incorrect positioning, which brings serious harm to production and life. Therefore, adopting effective deception detection technology based on the principle of deceptive jamming is an important means to improve navigation safety.

[0003] At present, common deception detection technologies are divided into two categories. The first category mainly detects the observed values ​​of deception signals and looks for the difference between them and the real signals. It includes detection technology based on signal power, detection technology based on multiple antennas, and detection technology based on consistency test of observations. The second category of technology detects deception based on the abnormal changes in the output results of the receiver after the real signal interacts with the deception signal. It mainly includes methods based on signal quality detection and tracking loop-related output anomaly detection. The disadvantage is that after encountering a zero-fall attack, the real signal and the deception signal will not be able to interact with each other, resulting in the failure of the detection method. The above methods mainly rely on the satellite navigation's own signals for deception detection. With the increasing development of deception technology, certain defects have been exposed. The Inertial Navigation System (INS) is not affected by the deception interference environment, can provide reliable information for navigation, and can be used to assist the detection of Beidou deception interference signals.

[0004] Therefore, it is necessary to improve one or more problems existing in the above-mentioned related technical solutions.

[0005] It should be noted that this section is intended to provide background or context for the technical solutions of the present disclosure stated in the claims. The description herein is not admitted to be prior art by virtue of being included in this section. Summary of the invention

[0006] The purpose of the embodiments of the present disclosure is to provide a method for detecting spoofing signals based on the pseudorange rate of the Beidou satellite navigation system, thereby overcoming one or more problems caused by the limitations and defects of the relevant technology at least to a certain extent.

[0007] According to a first aspect of an embodiment of the present disclosure, a method for detecting spoofing signals based on a Beidou satellite navigation system pseudorange rate is provided, the method comprising:

[0008] The measured pseudorange rate is obtained according to the carrier phase value actually observed by the receiver, and the calibrated pseudorange rate is obtained according to the speed information provided by the inertial navigation system;

[0009] Differentiating the measured pseudorange rate from the calibrated pseudorange rate to obtain a statistical detection amount;

[0010] Establishing a test of no deceptive interference and existence of deceptive interference according to the statistical detection amount, and obtaining a probability distribution function of no deceptive interference and a probability distribution function of existence of deceptive interference;

[0011] The deception signal detection threshold is obtained by using the probability distribution function of no deception interference, and the actual detection probability is obtained by using the probability distribution function of existence of deception interference;

[0012] It is determined whether the information received by the receiver is a spoof signal according to the spoof signal detection threshold and the actual detection probability.

[0013] In one embodiment of the present disclosure, judging whether the information received by the receiver is a spoofing signal according to the spoofing signal detection threshold and the actual detection probability includes:

[0014] The preset minimum detection probability is compared with the actual detection probability. If the actual detection probability satisfies or is less than or equal to the preset minimum detection probability, the statistical detection amount is compared with the deception signal detection threshold. When the statistical detection amount is greater than the deception signal detection threshold, a deception interference signal exists.

[0015] In one embodiment of the present disclosure, when the actual detection probability is greater than the preset minimum detection probability, it means that the data amount cannot meet the requirements of deception detection, and it is necessary to extend the data collection time and obtain observation data of multiple epochs for smoothing until the actual detection probability is less than or equal to the preset minimum detection probability, and then deception detection is performed.

[0016] In one embodiment of the present disclosure, the speed information provided by the inertial navigation system includes:

[0017] The inertial navigation system utilizes the velocity increment and angular velocity increment outputted by the accelerometer and the gyroscope respectively.

[0018] In one embodiment of the present disclosure, when the receiver receives a real signal, the statistical detection quantity obeys a normal distribution with a mean of zero.

[0019] In one embodiment of the present disclosure, after the receiver receives the spoofing signal, the artificially set forwarding delay will affect the accuracy of the pseudo-range rate, resulting in a non-zero deviation in the statistical detection amount.

[0020] In one embodiment of the present disclosure, after obtaining the probability distribution function of no deceptive interference and the probability distribution function of deceptive interference, the method further includes:

[0021] The probability distribution function of no deceptive interference and the probability distribution function of existence of deceptive interference are analyzed by fault detection theory to obtain a probability distribution curve of no deceptive interference and a probability distribution curve of existence of deceptive interference.

[0022] In one embodiment of the present disclosure, obtaining the spoofing signal detection threshold by using the non-spoofing interference probability distribution function includes:

[0023] The deception signal detection threshold is calculated based on a preset false alarm rate and the non-deception interference probability distribution curve.

[0024] In one embodiment of the present disclosure, obtaining the actual detection probability by using the existence of deceptive interference probability distribution function includes:

[0025] The actual detection probability when the deviation value exists is calculated according to the deception interference probability distribution curve.

[0026] According to a second aspect of an embodiment of the present disclosure, a spoofing signal detection device based on a Beidou satellite navigation system pseudorange rate is provided, the device comprising:

[0027] The pseudo-range rate calculation module is used to obtain the measured pseudo-range rate according to the carrier phase value actually observed by the receiver, and to obtain the calibrated pseudo-range rate according to the speed information provided by the inertial navigation system;

[0028] A statistical detection amount calculation module, used for differentiating the measured pseudorange rate from the calibrated pseudorange rate to obtain a statistical detection amount;

[0029] A test module, used to establish a test of no deceptive interference and existence of deceptive interference according to the statistical detection amount, and obtain a probability distribution function of no deceptive interference and a probability distribution function of existence of deceptive interference;

[0030] A processing module, configured to obtain a spoofing signal detection threshold through the probability distribution function of no spoofing interference, and obtain an actual detection probability through the probability distribution function of existence of spoofing interference;

[0031] The judging module is used to judge whether the information received by the receiver is a spoofing signal according to the spoofing signal detection threshold and the actual detection probability.

[0032] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0033] In the embodiments of the present disclosure, the above-mentioned deception signal detection method and device based on the pseudorange rate of the Beidou satellite navigation system are used to construct a test statistic and effectively detect deception signals by utilizing the characteristic that the speed drift of the inertial navigation system is not obvious in a short period of time. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0035] Figure 1 A step diagram of a spoofing signal detection method based on Beidou satellite navigation system pseudorange rate disclosed in the present invention is shown;

[0036] Figure 2 A schematic diagram of a forwarding spoofing principle in an exemplary embodiment of the present disclosure is shown;

[0037] Figure 3 A BDS spoofing detection probability analysis diagram in an exemplary embodiment of the present disclosure is shown;

[0038] Figure 4 A motion trajectory diagram of a drone in an exemplary embodiment of the present disclosure is shown;

[0039] Figure 5 A pseudo-range rate test error distribution curve diagram in an exemplary embodiment of the present disclosure is shown;

[0040] Figure 6 A probability distribution curve diagram of eastward inspection amount in an exemplary embodiment of the present disclosure is shown;

[0041] FIG. 7( a ) shows a diagram of eastward detection results of a pseudorange rate model under a deception state in an exemplary embodiment of the present disclosure;

[0042] FIG. 7( b ) shows a diagram of north detection results of a pseudorange rate model under a deception state in an exemplary embodiment of the present disclosure;

[0043] Figure 8 A pseudorange verification error distribution curve diagram in an exemplary embodiment of the present disclosure is shown;

[0044] FIG9( a ) shows a probability distribution curve diagram of the eastward inspection amount within the first 200 seconds in an exemplary embodiment of the present disclosure;

[0045] FIG9( b ) shows a probability distribution curve diagram of the eastward inspection quantity within the first 1750 seconds in an exemplary embodiment of the present disclosure;

[0046] FIG. 10( a ) shows a pseudorange verification error curve of an east detection result of a pseudorange model in a deception state in an exemplary embodiment of the present disclosure;

[0047] FIG. 10( b ) shows a pseudorange verification error curve of a north detection result of a pseudorange model in a deception state in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0048] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0049] In addition, the accompanying drawings are only schematic illustrations of the embodiments of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated descriptions will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities.

[0050] This example implementation provides a method for detecting spoofing signals based on the pseudo-range rate of the Beidou satellite navigation system, which can be applied to a device. Figure 1 As shown in , the deception signal detection method based on the Beidou satellite navigation system pseudorange rate may include the following steps: step S101 to step S105.

[0051] Step S101: obtaining a measured pseudorange rate according to a carrier phase value actually observed by a receiver, and obtaining a calibrated pseudorange rate according to speed information provided by an inertial navigation system;

[0052] Step S102: Differentiate the measured pseudorange rate from the calibrated pseudorange rate to obtain a statistical detection amount;

[0053] Step S103: establishing a test of no deceptive interference and existence of deceptive interference according to the statistical detection amount, and obtaining a probability distribution function of no deceptive interference and a probability distribution function of existence of deceptive interference;

[0054] Step S104: obtaining a spoofing signal detection threshold by using the probability distribution function of no spoofing interference, and obtaining an actual detection probability by using the probability distribution function of existence of spoofing interference;

[0055] Step S105: judging whether the information received by the receiver is a spoof signal according to the spoof signal detection threshold and the actual detection probability.

[0056] Through the above-mentioned deception signal detection method based on the pseudo-range rate of the Beidou satellite navigation system, the test statistic is constructed by utilizing the characteristic that the speed drift of the inertial navigation system is not obvious in a short period of time, and the deception signal is effectively detected.

[0057] Next, we will refer to Figures 1 to 3 Each step of the above-mentioned spoofing signal detection method based on the pseudorange rate of the Beidou satellite navigation system in this example implementation is described in more detail.

[0058] Step S101: obtaining a measured pseudorange rate according to a carrier phase value actually observed by a receiver, and obtaining a calibrated pseudorange rate according to speed information provided by an inertial navigation system.

[0059] Specifically, the Beidou satellite real signal pseudorange observation equation is:

[0060] ρ (j) =r (j) +δt r -δt (j) +I (j) +T (j) +ε (1)

[0061] In the formula, δt r represents the position error caused by the receiver clock error, δt (j) represents the position error caused by the clock error of satellite j, I (j) and T (j) denote the ionospheric delay and tropospheric delay respectively, ε is the observation noise, r (j) represents the geometric distance from satellite j to the receiver, which can be expressed in the Earth-centered Earth-fixed coordinate system as:

[0062]

[0063] Where (x (j) ,y (j) ,z (j) ) represents the actual observed satellite coordinates, and (x, y, z) represents the ground receiver coordinates.

[0064] Using the four-star positioning principle, when there are 4 or more satellite signals at the same time, the satellite position coordinates (x (j) ,y (j) ,z (j) ), substitute it into equation (1) and equation (2), use the least square method to solve, and get the receiver position coordinates (x, y, z) to achieve the positioning requirement.

[0065] When there is forwarding deception interference, the forwarding deception interference source intercepts the real satellite signal, and then forwards it after signal delay, power amplification and other processing, to trick the receiver into making an incorrect positioning, thereby achieving the purpose of deception interference. Figure 2 As shown in Figure 2, due to the existence of deceptive signal sources, the Beidou satellite pseudorange observation equation becomes:

[0066]

[0067] In the formula, represents the pseudo-range observation equation at the deception position N, that is, the sum of the distance from the satellite to the deception interference source and the equivalent distance of the real signal after the repeater delay processing, Δρ (j) represents the distance from the transmitting antenna of the forwarding deception interference source to the receiver, and its observation equation is:

[0068]

[0069] In the formula, represents the geometric distance from the satellite to the spoofed position N, Δr d Indicates the distance from the spoofing interference source to the satellite receiver.

[0070] Combining equations (3) and (4), we can get the pseudo-range observation equation after being deceived:

[0071]

[0072] By taking the time derivative of equation (1), we can obtain:

[0073]

[0074] In the formula, represents the pseudorange rate, δf r Indicates the receiver clock frequency drift, δf (j) is the satellite j clock frequency drift, and represent the changing rates of ionospheric delay and tropospheric delay respectively, It represents the rate of change of the geometric distance between the satellite and the receiver, which can be obtained by the difference between the satellite rate and the receiver rate:

[0075]

[0076] In the formula, v (j) is the operating speed of satellite j, v is the receiver speed, 1 (j) is the unit observation vector from the satellite to the receiver.

[0077] Considering that the measurement accuracy of the carrier phase observation is much higher than that of the pseudorange observation, the pseudorange change rate Use the carrier phase observation value φ at adjacent time(n) It is expressed as:

[0078]

[0079] In the actual observation process, the ionospheric delay and tropospheric delay are not very sensitive to time changes, so their delay change rates can be ignored. Combining equations (6) and (7), we can get:

[0080]

[0081] In the formula,

[0082] δf (j) =a f1 +2a f2 (tt oc ) (10)

[0083] In the formula, a f1 、a f2 is the binomial coefficient of satellite clock error, t oc It is the standard time, and the specific data can be obtained from the navigation message.

[0084] Similarly, when there is deceptive interference,

[0085]

[0086] In the formula, represents the rate of change of the geometric distance from the satellite to the transponder, It represents the rate of change of the geometric distance from the transponder to the receiver. Its relationship with the speed can be expressed as:

[0087]

[0088] Substituting into formula (11), we can get:

[0089]

[0090] By analyzing equations (9) and (13), it can be found that after the delay processing of the repeater, an additional pseudorange rate will be generated, resulting in positioning jumps in the observed values.

[0091] INS is not affected by satellite deception interference and can provide reliable information for navigation. The accelerometer and gyroscope are used to output velocity increment and angle increment respectively. By integrating the time, the velocity of the receiver at time k is obtained as:

[0092]

[0093] In the formula, represents the speed of the receiver at time k-1 in the n coordinate system; represents the velocity increment generated at time k; It represents the velocity increment at time k due to harmful acceleration caused by factors such as the earth's rotation and uneven gravity distribution.

[0094]

[0095] In the formula is the posture matrix, is the specific force parameter in system b.

[0096] The value of changes slowly over time, expressed as:

[0097]

[0098] In the formula, is the angular velocity of the Earth's rotation, represents the angular velocity of the n-axis rotation, g n is the acceleration due to gravity, T is the integration interval, t k-1 / 2 The data at each moment can be calculated using the extrapolation method.

[0099] When the satellite is deceptively interfered, the receiver velocity is calculated using the inertial navigation solution and substituted into equation (9) to obtain the pseudo-range rate after INS calibration: for:

[0100]

[0101] Where G is the transformation matrix from the Earth-centered Earth-fixed coordinate system to the “Northeast Sky” coordinate system.

[0102] Step S102: Differentiate the measured pseudorange rate from the calibrated pseudorange rate to obtain a statistical detection value.

[0103] Specifically, by taking a difference with the pseudo-range rate actually measured by the satellite, a statistical test quantity is constructed:

[0104]

[0105] Step S103: establishing a test of no deceptive interference and presence of deceptive interference according to the statistical detection amount, and obtaining a probability distribution function of no deceptive interference and a probability distribution function of presence of deceptive interference.

[0106] By taking advantage of the fact that the velocity drift of inertial navigation is not obvious in a short period of time, the consistency detection of statistical test quantity can be realized. It should obey a normal distribution with a mean of 0. When the satellite is interfered by deception, the artificially set forwarding delay will affect the accuracy of the pseudo-range rate, resulting in There is a non-zero bias.

[0107] according to Two hypothesis tests are constructed with different numerical values. Assuming H0 (no deception interference) and H1 (deception interference exists), then:

[0108]

[0109] In the formula, x(k) can be expressed as Components in any direction in ; A represents a non-zero deviation; θ(k) obeys a Gaussian distribution with a mean of 0, expressed as:

[0110]

[0111] In the formula, represents the variance of θ.

[0112] Step S104: obtaining a spoofing signal detection threshold through the probability distribution function of no spoofing interference, and obtaining an actual detection probability through the probability distribution function of existence of spoofing interference.

[0113] Then the condition for H1 to hold (the existence of deception interference) is:

[0114]

[0115] Where γ is the decision threshold, is the maximum likelihood estimate of A, and are the maximum likelihood estimates of the variance of x under the assumptions H0 and H1, respectively, expressed as

[0116]

[0117] Since the mean of θ(k) is 0, let Therefore, formula (21) can be expressed as:

[0118]

[0119] When H0 holds, T~t(k-1), and λ(x) is a monotonically increasing function of |T|, so

[0120] P{λ(x)≥γ||H0 holds}=P{|T|≥γ1||H0 holds}=α (24)

[0121] Get critical value

[0122]

[0123] Therefore, the decision threshold of the spoof signal consistency check can be expressed as:

[0124]

[0125] The corresponding false alarm rate P FA and the minimum detection probability is P D (Maximum missed detection probability P MD =1-P D )for:

[0126]

[0127] Where P0 and P1 are the probability distribution functions when H0 and H1 are true, respectively.

[0128] It is analyzed through the theory of fault detection, such as Figure 3 shown.

[0129] Step S105: judging whether the information received by the receiver is a spoof signal according to the spoof signal detection threshold and the actual detection probability.

[0130] When P D ≥P D ',and When the deception detection threshold γ1 is exceeded, there is a deception interference signal; if P D <P D ′, it means that the data volume cannot meet the requirements of deception detection, and it is necessary to extend the data collection time and obtain observation data of multiple epochs for smoothing until P is met. D ≥P D ′ and then perform deception detection.

[0131] The disclosed embodiment also provides a spoofing signal detection device based on the pseudorange rate of the Beidou satellite navigation system, which uses any of the above-mentioned spoofing signal detection methods based on the pseudorange rate of the Beidou satellite navigation system to perform signal detection.

[0132] This embodiment is further described below in conjunction with a specific simulation example.

[0133] 1. Simulation condition setting

[0134] In order to verify the effectiveness of the Beidou velocity / pseudorange rate consistency detection method assisted by inertial navigation, a deception interference environment was built using navigation signal source, deception interference source and integrated navigation receiver. The consistency statistical test quantity was constructed by using the solved Beidou pseudorange rate and inertial navigation velocity information to realize the detection of deception interference signals.

[0135] The simulation sets the UAV motion time to 1750s, and simulates the motion state of the UAV at different times. The initial motion state of the UAV is set as shown in Table 1.

[0136] Table 1 Initial state of carrier

[0137]

[0138] According to the flight attitude parameters preset in the trajectory simulation code, the motion trajectory is simulated, such as Figure 4 shown.

[0139] Connect the navigation signal source, deception simulation source, integrated navigation receiver and computer to build a deception jamming platform. Import the UAV motion data into the signal source, and then set up deception jamming artificially through the deception simulation source to collect BDS signals and INS signals in real and deception situations, respectively, and obtain observation data.

[0140] Table 2 Initial state of carrier

[0141]

[0142] In order to verify the detection performance of the proposed method for different deception jamming signals, different types of deception jamming schemes are set using deception simulation sources, and the deception jamming mode settings are shown in Table 3. To ensure that the deception signal can effectively interfere with the signal source, the deception jamming source is set at 108.1° east longitude, 33.9° north latitude, 400m altitude, and the signal output power is -20dB.

[0143] Table 3 Deception scheme settings

[0144]

[0145] 2. Experimental results analysis

[0146] Without adding deceptive interference signals, the collected satellite signal carrier phase observations are solved according to formula (8) to obtain the pseudo-range rate in the real situation: Then, according to formula (17), the satellite velocity provided in the satellite ephemeris information and the velocity information calculated by the inertial navigation solution are used to obtain the satellite pseudorange rate after INS calibration:

[0147] By comparing the carrier's three-dimensional pseudo-range rate information, it can be found that when there is no deception interference signal, the pseudo-range rate obtained by satellite signal solution is basically consistent with the pseudo-range rate after INS calibration. On this basis, according to formula (18), the consistency test quantity is constructed .like Figure 5 As shown in the figure, except for the divergence of the celestial error, the eastward error and the northward error fluctuate around 0 during the simulation time.

[0148] like Figure 6As shown in the figure, taking the eastward test quantity as an example, within 1750s, its probability density distribution curve meets the requirements of normal distribution. Considering that the speed error obtained by INS solution will also accumulate over time, the test quantity shows a divergent trend in the time domain, and the divergent trend of the altitude channel test quantity is more obvious. Therefore, in this experiment, only the eastward and northward test quantities of the first 200s are processed to obtain the probability density function under the real signal, and the false alarm rate P is set. FA =0.01, the minimum detection probability is P D =0.9. According to the probability density distribution curve, the detection threshold of the deceptive interference signal is obtained: the eastward test value is 0.2071HZ, and the northward test value is 0.1366HZ.

[0149] According to the deception scheme provided in the table, deception interference is performed, and the deception interference strategies in schemes 2, 3, and 4 are applied to the receiver in sequence by setting the deception simulation source. The deception interference signal is detected using the test quantity constructed by the pseudo-range rate, and the detection results are shown in the figure.

[0150] As shown in Figure 7(a), within 25 to 50 seconds, a hovering deception scheme was applied to the eastward verification quantity, resulting in a satellite pseudorange rate of , inspection quantity A sudden change occurs, far exceeding the detection threshold; when the carrier moves to 1500s, it is deceived by the eastward position under Scheme 4, causing the test quantity to exceed the detection threshold again. It can be seen from the figure that the carrier is stationary in the north direction from 25 to 50s, so it is impossible to detect the stationary deception in Scheme 2 through the northward test quantity. At 650 to 750s, as shown in Figure 7(b), the northward pseudorange rate test quantity exceeds the detection threshold, corresponding to the northward speed deception in Scheme 3. In the period without deception interference, the eastward and northward test quantities can be kept within the detection threshold.

[0151] 3. Detection result analysis based on pseudo-range model

[0152] First, according to formula (1), the satellite position in the ephemeris data and the trajectory position information obtained by INS solution are combined to obtain the pseudo-range reference value calibrated by INS; then, the pseudo-range consistency check value is obtained by differentiating it with the pseudo-range actually measured by the satellite, as follows: Figure 8 shown.

[0153] By comparison Figure 5 and Figure 8It can be found that compared with the pseudorange model with obvious divergence, the test quantity constructed using the pseudorange rate has a higher sensitivity to deceptive interference signals. Taking the eastward pseudorange test quantity as an example, the probability density distribution curve is constructed, as shown in Figure 9(a) and Figure 9(b). In the first 200 seconds, the pseudorange test quantity can meet the requirements of normal distribution, but as time goes by, the position drift of INS makes the probability density of the pseudorange test quantity present an irregular distribution, which cannot meet the theoretical analysis results.

[0154] Similarly, set the false alarm rate P FA =0.01, the minimum detection probability is P D =0.9. The probability density function in the first 200s is used to obtain the detection threshold of the pseudorange test quantity: the eastward test quantity is 58.5951m, and the northward test quantity is 58.1481m. Then, the deception interference strategies of modes 2 and 3 in Table 3 are applied to the moving carrier respectively, and the moving carrier is deceived to deviate 100m in the eastward position at 700-750s. The test quantity constructed by the pseudorange test quantity is used to detect the deception interference signal, and the detection results are shown in Figures 10(a) and 10(b).

[0155] As for the pseudo-range model detection results, within 25 to 50 seconds, the carrier was deceived by the hovering and stationary setting of mode 2, causing the test value to shift about 1,000 meters to the east, exceeding the detection threshold; when the movement time was 700 seconds, the deception interference source tricked the carrier into deviating 100 meters to the east, causing the test value to exceed the threshold value. However, as time goes by, due to the continuous accumulation of inertial navigation position errors, the test value is higher than the detection threshold even when it is not deceptive interference, and it is impossible to effectively detect subsequent deceptive interference. At the same time, the pseudo-range model cannot effectively detect slow speed deviations, resulting in missed alarms.

[0156] From the above analysis, it can be found that the INS position error diverges seriously over time, resulting in the pseudo-range model only being able to maintain high accuracy in a short period of time and being unable to effectively detect slow-moving speed deception. The detection model constructed using the pseudo-range rate has high sensitivity to both position deception signals and speed deception signals, and is suitable for longer-term deception interference detection.

[0157] Aiming at the deception and interference problem faced by Beidou satellite navigation, the present invention proposes to use the speed information of INS to assist BDS in pseudo-range rate consistency test. The method uses the characteristic that the speed drift of INS is not obvious in a short period of time to construct a test statistic, and effectively detects the deception signal based on the fault diagnosis method. The experimental results show that the method has a good detection effect on both position deception with large deviation and speed deception with slow deviation. Compared with the pseudo-range model with serious divergence, it can ensure the accuracy of the detection results for a long time, and is suitable for deception interference detection in large-scale and long-term interference scenarios.

[0158] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification.

[0159] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

Claims

1. A method for detecting spoofing signals based on the pseudo-range rate of the Beidou satellite navigation system, characterized in that: include: The measured pseudorange rate is obtained according to the carrier phase value actually observed by the receiver, and the calibrated pseudorange rate is obtained according to the speed information provided by the inertial navigation system; Differentiating the measured pseudorange rate from the calibrated pseudorange rate to obtain a statistical detection amount; Establishing a test of no deceptive interference and existence of deceptive interference according to the statistical detection amount, and obtaining a probability distribution function of no deceptive interference and a probability distribution function of existence of deceptive interference; The deception signal detection threshold is obtained by using the probability distribution function of no deception interference, and the actual detection probability is obtained by using the probability distribution function of existence of deception interference; determining whether the information received by the receiver is a spoof signal according to the spoof signal detection threshold and the actual detection probability; Wherein, the preset minimum detection probability is compared with the actual detection probability. If the actual detection probability satisfies or is less than or equal to the preset minimum detection probability, the statistical detection amount is compared with the spoofing signal detection threshold. When the statistical detection amount is greater than the spoofing signal detection threshold, there is a spoofing interference signal. When the actual detection probability is greater than the preset minimum detection probability, it means that the data amount cannot meet the requirements of deception detection, and it is necessary to extend the data collection time and obtain observation data of multiple epochs for smoothing until the actual detection probability is less than or equal to the preset minimum detection probability before deception detection is performed.

2. The method for detecting spoofing signals based on the pseudo-range rate of the Beidou satellite navigation system according to claim 1, characterized in that: The speed information provided by the inertial navigation system includes: The inertial navigation system utilizes the velocity increment and angular velocity increment outputted by the accelerometer and the gyroscope respectively.

3. The method for detecting spoofing signals based on the pseudo-range rate of the Beidou satellite navigation system according to claim 1, characterized in that: When the receiver receives a real signal, the statistical detection quantity obeys a normal distribution with a mean of zero.

4. The method for detecting spoofing signals based on the pseudo-range rate of the Beidou satellite navigation system according to claim 1, characterized in that: After the receiver receives the spoof signal, the artificially set forwarding delay will affect the accuracy of the pseudo-range rate, resulting in a non-zero deviation in the statistical detection amount.

5. The method for detecting spoofing signals based on the pseudo-range rate of the Beidou satellite navigation system according to claim 1, characterized in that: After obtaining the probability distribution function of no deceptive interference and the probability distribution function of deceptive interference, the method further includes: The probability distribution function of no deceptive interference and the probability distribution function of existence of deceptive interference are analyzed by a fault diagnosis method to obtain a probability distribution curve of no deceptive interference and a probability distribution curve of existence of deceptive interference.

6. The method for detecting spoofing signals based on the pseudo-range rate of the Beidou satellite navigation system according to claim 5, characterized in that: Obtaining the deception signal detection threshold through the non-deception interference probability distribution function includes: The deception signal detection threshold is calculated based on a preset false alarm rate and the non-deception interference probability distribution curve.

7. The method for detecting spoofing signals based on the pseudo-range rate of the Beidou satellite navigation system according to claim 6, characterized in that: The actual detection probability obtained by using the existence of deception interference probability distribution function includes: The actual detection probability when the deviation value exists is calculated according to the deception interference probability distribution curve.

8. A spoofing signal detection device based on Beidou satellite navigation system pseudo-range rate, characterized in that: The device includes: The pseudo-range rate calculation module is used to obtain the measured pseudo-range rate according to the carrier phase value actually observed by the receiver, and to obtain the calibrated pseudo-range rate according to the speed information provided by the inertial navigation system; A statistical detection amount calculation module, used for differentiating the measured pseudorange rate from the calibrated pseudorange rate to obtain a statistical detection amount; A test module, used to establish a test of no deceptive interference and existence of deceptive interference according to the statistical detection amount, and obtain a probability distribution function of no deceptive interference and a probability distribution function of existence of deceptive interference; A processing module, configured to obtain a spoofing signal detection threshold through the probability distribution function of no spoofing interference, and obtain an actual detection probability through the probability distribution function of existence of spoofing interference; A judging module, configured to judge whether the information received by the receiver is a spoofing signal according to the spoofing signal detection threshold and the actual detection probability; Wherein, the preset minimum detection probability is compared with the actual detection probability. If the actual detection probability satisfies or is less than or equal to the preset minimum detection probability, the statistical detection amount is compared with the spoofing signal detection threshold. When the statistical detection amount is greater than the spoofing signal detection threshold, there is a spoofing interference signal. When the actual detection probability is greater than the preset minimum detection probability, it means that the data amount cannot meet the requirements of deception detection, and it is necessary to extend the data collection time and obtain observation data of multiple epochs for smoothing until the actual detection probability is less than or equal to the preset minimum detection probability before deception detection is performed.

Images