A method, device and electronic device for detecting navigation deception interference

Abstract

The present invention discloses a navigation deception interference detection method, device and electronic device. The method includes, in the deception interference detection stage, using a satellite navigation receiver to obtain a received signal, performing a cross-correlation operation on the received signal and a replicated pseudo-random code generated locally by the receiver, obtaining the output results of the in-phase branch correlator of the early code, the instant code and the late code and the output results of the orthogonal branch correlator of the early code, the instant code and the late code; performing a sum-difference operation to construct an SQM detection amount; performing sliding processing on the received signal with a preset length window, calculating the mean measurement value and the variance measurement value of the SQM detection amount in the window; comparing the SQM detection amount, the mean measurement value and the variance measurement value with the corresponding threshold value respectively, and calculating the respective detection probabilities, and determining the detection result of the navigation deception interference based on the comparison result and the detection probability. The scheme of the present invention can improve the detection performance and enhance the robustness of the detection algorithm.

Description

Technical Field

[0001] The present invention relates to the field of satellite navigation signal processing technology, and in particular to a navigation deception interference detection method, device and electronic equipment. Background Art

[0002] GNSS is currently in a new era of rapid development and cross-border integration with other fields. Its applications and services have been widely infiltrated into multiple social fields such as communications, engineering, transportation, and public safety. Positioning services in daily life, such as in-vehicle navigation, express tracking, autonomous driving, and mobile phone positioning, all rely on GNSS, and its popularity can be described as ubiquitous. However, this also brings some potential threats. GNSS signals experience absorption, scattering, and reflection when passing through environments such as the atmosphere, clouds, rain, and buildings, resulting in path loss of signal energy. In addition, the propagation loss in free space increases with distance, making the signal extremely weak when it reaches the ground. In addition, the structure of civil signals is public, making them vulnerable to interference and deception.

[0003] With the widespread application of GNSS in various industries, its security and reliability have become the focus of everyone's attention. Therefore, it is crucial to develop and apply effective anti-spoofing interference technology, and detecting spoofing interference is the key link in suppressing or eliminating spoofing interference. Only by accurately detecting spoofing interference can the impact of spoofing interference be further alleviated or eliminated. Signal Quality Monitoring (SQM) detection technology has higher flexibility, applicability and robustness, and is one of the most widely and deeply studied directions of spoofing interference detection at this stage.

[0004] At present, the traditional SQM algorithm only uses the ratio of the in-phase I branch signal to construct the detection quantity, and the I branch signal is in phase with the carrier phase, so the drift of the carrier phase will directly affect the detection quantity. The carrier phase difference between the real satellite navigation signal and the deceptive interference signal will cause the energy of the orthogonal Q branch signal to be abnormal, and will also greatly reduce the detection performance of the I branch algorithm. Summary of the invention

[0005] In order to solve the technical problem of poor detection performance of the traditional SQM algorithm, the embodiments of the present invention provide a navigation deception interference detection method, device and electronic device.

[0006] The technical solution of the embodiment of the present invention is achieved as follows:

[0007] The embodiment of the present invention provides a navigation deception interference detection method, which includes: in the deception interference detection stage, using a satellite navigation receiver to obtain a received signal, performing a cross-correlation operation on the received signal and a replicated pseudo-random code generated locally by the receiver, and obtaining an output result of an in-phase branch correlator of an early code, an output result of an in-phase branch correlator of an immediate code, an output result of an in-phase branch correlator of a late code, an output result of an orthogonal branch correlator of an early code, an output result of an orthogonal branch correlator of an immediate code, and an output result of an orthogonal branch correlator of a late code; and outputting the output result of the in-phase branch correlator of the early code, the output result of the in-phase branch correlator of the immediate code, and the output result of the orthogonal branch correlator of the late code. The output result of the correlator, the output result of the orthogonal branch correlator of the early code, the output result of the orthogonal branch correlator of the immediate code and the output result of the orthogonal branch correlator of the late code are subjected to sum and difference operations to construct an SQM detection amount; the received signal is subjected to sliding processing with a preset length window to calculate the mean measurement value and the variance measurement value of the SQM detection amount in the window; the SQM detection amount, the mean measurement value and the variance measurement value are respectively compared with corresponding threshold values, and the detection probability of the SQM detection amount, the mean measurement value and the variance measurement value is calculated, and the detection result of navigation deception interference is determined based on the comparison result and the detection probability.

[0008] The embodiment of the present invention also provides a navigation deception interference detection device, which includes: a cross-correlation operation module, which is used to use a satellite navigation receiver to obtain a received signal in the deception interference detection stage, and perform a cross-correlation operation on the received signal and a replicated pseudo-random code generated locally by the receiver to obtain an in-phase branch correlator output result of an early code, an in-phase branch correlator output result of an immediate code, an in-phase branch correlator output result of a late code, an orthogonal branch correlator output result of an early code, an orthogonal branch correlator output result of an immediate code, and an orthogonal branch correlator output result of a late code; a first construction module, which is used to output the in-phase branch correlator output result of the early code, the in-phase branch correlator output result of the immediate code, the orthogonal branch correlator output result of the late code, and the orthogonal branch correlator output result of the late code. The output result of the in-phase branch correlator of the late code, the output result of the orthogonal branch correlator of the early code, the output result of the orthogonal branch correlator of the prompt code and the output result of the orthogonal branch correlator of the late code are subjected to sum and difference operations to construct an SQM detection amount; a second construction model is used to perform sliding processing on the received signal with a preset length window, and calculate the mean measurement value and the variance measurement value of the SQM detection amount in the window; a detection module is used to compare the SQM detection amount, the mean measurement value and the variance measurement value with the corresponding threshold values, and calculate the detection probability of the SQM detection amount, the mean measurement value and the variance measurement value respectively, and determine the detection result of navigation deception interference based on the comparison result and the detection probability.

[0009] An embodiment of the present invention further provides an electronic device, comprising: a processor and a memory for storing a computer program that can be run on the processor; wherein the processor executes the steps of any of the above methods when running the computer program.

[0010] The navigation deception interference detection method, device and electronic device provided by the embodiment of the present invention, in the deception interference detection stage, use a satellite navigation receiver to obtain a received signal, perform a cross-correlation operation on the received signal and a replicated pseudo-random code generated locally by the receiver, and obtain an output result of the in-phase branch correlator of the early code, an output result of the in-phase branch correlator of the instant code, an output result of the in-phase branch correlator of the late code, an output result of the orthogonal branch correlator of the early code, an output result of the orthogonal branch correlator of the instant code and an output result of the orthogonal branch correlator of the late code; the output result of the in-phase branch correlator of the early code, the output result of the in-phase branch correlator of the instant code, the output result of the in-phase branch correlator of the late code The output result of the orthogonal branch correlator of the early code, the output result of the orthogonal branch correlator of the instant code and the output result of the orthogonal branch correlator of the late code are summed and differed to construct the SQM detection amount; the received signal is subjected to sliding processing with a preset length window, and the mean measurement value and variance measurement value of the SQM detection amount in the window are calculated; the SQM detection amount, the mean measurement value and the variance measurement value are compared with the corresponding threshold value respectively, and the detection probability of the SQM detection amount, the mean measurement value and the variance measurement value are calculated, and the detection result of the navigation deception interference is determined based on the comparison result and the detection probability. The scheme provided by the present invention introduces the Q branch signal, and uses the I branch and Q branch signal products of the early code, late code and instant code correlators to construct the detection amount by summing and differencing, thereby reducing the influence of the carrier phase difference on the algorithm; at the same time, the scheme uses the sliding window average and variance processing to suppress the noise, better reflect the fluctuation of the detection amount, so as to improve the detection performance and enhance the robustness of the detection algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A flowchart of a navigation deception interference detection method according to an embodiment of the present invention;

[0012] Figure 2 This is a schematic diagram of the system architecture of an embodiment of the present invention;

[0013] Figure 3 This is a schematic diagram of the implementation flow of SQM satellite navigation deception interference detection according to an embodiment of the present invention;

[0014] Figure 4 This is a schematic diagram of the change in the Mpsd detection amount of the 8-channel captured star under the ds2 data set of the embodiment of the present invention; wherein, Figure 4 (a) is a schematic diagram of the change in the Mpsd detection value of channel 1 under the ds2 data set. Figure 4 (b) is a schematic diagram of the change in the Mpsd detection value of channel 2 under the ds2 data set. Figure 4 (c) is a schematic diagram of the change in the Mpsd detection value of channel 3 under the ds2 data set. Figure 4 (d) is a schematic diagram of the change in the Mpsd detection value of channel 4 under the ds2 data set. Figure 4 (e) is a schematic diagram of the change in the Mpsd detection value of channel 5 under the ds2 data set. Figure 4 (f) is a schematic diagram of the change in the Mpsd detection value of channel 6 under the ds2 data set. Figure 4 (g) is a schematic diagram of the change in the Mpsd detection value of channel 7 under the ds2 data set. Figure 4 (h) is a schematic diagram of the change in the Mpsd detection value of channel 8 under the ds2 data set;

[0015] Figure 5 This is a schematic diagram of the comparison of various detection quantities of PRN23 under the ds2 data set in an embodiment of the present invention; wherein, Figure 5 (a) is a schematic diagram of the change of Ratio detection quantity under the ds2 data set. Figure 5 (b) is a schematic diagram of the change in Mpsd detection quantity under the ds2 dataset. Figure 5 (c) is a schematic diagram of the change in Mpsd-mean detection quantity under the ds2 data set. Figure 5 (d) is a schematic diagram of the change in Mpsd-var detection quantity under the ds2 dataset;

[0016] Figure 6 This is a schematic diagram of the comparison of detection probabilities of various detection quantities of PRN23 under the ds2 data set in an embodiment of the present invention;

[0017] Figure 7 Schematic diagram of ROC curve comparison of various detection values ​​of PRN23 in the ds2 data set according to an embodiment of the present invention;

[0018] Figure 8 This is a schematic diagram of the change of the Mpsd detection value of the 8-channel captured star under the ds3 data set over time in an embodiment of the present invention; wherein, Figure 8 (a) is a schematic diagram of the change in the Mpsd detection value of channel 1 under the ds3 data set. Figure 8 (b) is a schematic diagram of the change in the Mpsd detection value of channel 2 under the ds3 data set. Figure 8 (c) is a schematic diagram of the change in the Mpsd detection value of channel 3 under the ds3 data set. Figure 8 (d) is a schematic diagram of the change in the Mpsd detection value of channel 4 under the ds3 data set. Figure 8 (e) is a schematic diagram of the change in the Mpsd detection value of channel 5 under the ds3 data set. Figure 8(f) is a schematic diagram of the change in the Mpsd detection value of channel 6 under the ds3 data set. Figure 8 (g) is a schematic diagram of the change in the Mpsd detection value of channel 7 under the ds3 data set. Figure 8 (h) is a schematic diagram of the change in the Mpsd detection value of channel 8 under the ds3 data set;

[0019] Fig. 9 This is a schematic diagram of the comparison of various detection quantities of PRN23 under the ds3 data set in an embodiment of the present invention; wherein, Fig. 9 (a) is a schematic diagram of the change of Ratio detection quantity under the ds3 data set. Fig. 9 (b) is a schematic diagram of the change in Mpsd detection quantity under the ds3 dataset. Fig. 9 (c) is a schematic diagram of the change in Mpsd-mean detection quantity under the ds3 data set. Fig. 9 (d) is a schematic diagram of the change in Mpsd-var detection quantity under the ds3 dataset;

[0020] Fig.10 This is a schematic diagram of the comparison of detection probabilities of various detection quantities of PRN23 under the ds3 data set in an embodiment of the present invention;

[0021] Fig.11 Schematic diagram of ROC curve comparison of various detection values ​​of PRN23 in the ds3 data set according to an embodiment of the present invention;

[0022] Fig.12 1 is a diagram showing the internal structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] Before introducing the method of this embodiment, the following definitions are introduced.

[0024] GNSS: Global Navigation Satellite System (GNSS) is a space-based radio navigation and positioning system that transmits signals through satellites to ultimately achieve user positioning, speed measurement and timing functions.

[0025] SQM: Signal Quality Monitoring (SQM) is a deception detection technology that determines whether there is deception interference by detecting whether the signal correlation peak is abnormal during the tracking phase of the receiver.

[0026] ROC curve: The detection capability of spoofing attacks under any assumed false alarm probability, also known as the receiver operating characteristic curve.

[0027] The present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

[0028] The embodiment of the present invention provides a navigation deception interference detection method, such as Figure 1 As shown, the method includes:

[0029] Step 101: In the deception interference detection stage, a satellite navigation receiver is used to obtain a received signal, and the received signal is cross-correlated with a replicated pseudo-random code generated locally by the receiver to obtain an output result of an in-phase branch correlator of an early code, an output result of an in-phase branch correlator of an immediate code, an output result of an in-phase branch correlator of a late code, an output result of an orthogonal branch correlator of an early code, an output result of an orthogonal branch correlator of an immediate code, and an output result of an orthogonal branch correlator of a late code;

[0030] Step 102: performing sum and difference operations on the output results of the in-phase branch correlator of the early code, the output results of the in-phase branch correlator of the instant code, the output results of the in-phase branch correlator of the late code, the output results of the orthogonal branch correlator of the early code, the output results of the orthogonal branch correlator of the instant code and the output results of the orthogonal branch correlator of the late code to construct an SQM detection amount;

[0031] Step 103: Sliding the received signal with a preset length window to calculate the mean measurement value and variance measurement value of the SQM detection quantity in the window;

[0032] Step 104: Compare the SQM detection value, the mean measurement value and the variance measurement value with the corresponding threshold values ​​respectively, and calculate the detection probability of the SQM detection value, the mean measurement value and the variance measurement value respectively, and determine the detection result of the navigation deception interference based on the comparison result and the detection probability.

[0033] The method of this embodiment uses the I branch (i.e., the output result of the in-phase branch correlator) and Q branch (the output result of the orthogonal branch correlator) signals of the early code, late code and prompt code to construct a detection quantity, and compares it with the detection threshold (i.e., the threshold value) to determine whether there is a deceptive interference signal; on this basis, the mean and variance of the detection quantity (i.e., the mean measurement value and the variance measurement value) are obtained through sliding window processing, and the deceptive interference signal is detected through abnormal fluctuations in the mean and variance, thereby improving the detection probability.

[0034] Specifically, see Figure 2 and Figure 3 , Figure 2 This is a schematic diagram of the system architecture of an embodiment of the present invention; Figure 3 This is a schematic diagram of the implementation process of SQM satellite navigation deception interference detection in an embodiment of the present invention. The specific process of this embodiment is as follows:

[0035] Step 1: In the absence of a spoofing signal, the received signal is down-converted. The real satellite navigation complex signal after down-conversion at time t can be expressed as:

[0036] Calculation formula (1)

[0037] in, is the real satellite navigation signal power, D(t) is the data bit stream with a value of ±1, C(t) is the pseudo-random code with a value of ±1, is the carrier phase, j is the imaginary unit, is a natural exponential function.

[0038] The replica pseudo-random code generated locally by the receiver is correlated with the down-converted signal, and the real signal (i.e. the down-converted signal) is cross-correlated with the local signal (i.e. the replica pseudo-random code). The I branch output and Q branch output of the instant code are obtained as follows:

[0039] Calculation formula (2)

[0040] Calculation formula (3)

[0041] in, The output result of the in-phase branch correlator representing the instant code; The output result of the orthogonal branch correlator representing the instant code; Indicates the phase difference between the instant code and the locally copied pseudo-random code, is the signal power, is the carrier phase, and represents noise; R( ) is the pseudo code normalized autocorrelation function of the BPSK signal.

[0042] Similarly, the relevant output of early code and late code is expressed as:

[0043] Calculation formula (4)

[0044] Calculation formula (5)

[0045] Calculation formula (6)

[0046] Calculation formula (7)

[0047] in, The output result of the in-phase branch correlator representing the early code; The orthogonal branch correlator output result representing the early code; Indicates the phase difference between the early code and the local replicated pseudo-random code; represents the output result of the in-phase branch correlator of the late code; Q L represents the output result of the orthogonal branch correlator of the late code; Represents the phase difference between the late code and the local replicated pseudo-random code; is the signal power, is the carrier phase, , , , represents noise; R() represents the pseudo code normalized autocorrelation function of the phase shift keying signal.

[0048] Step 2: In the absence of deceptive interference signals, the SQM detection quantity Mpsd(n) is constructed by performing sum and difference operations using the IQ branch correlation outputs of the early code, immediate code, and late code. The calculation formula is as follows:

[0049] Calculation formula (8)

[0050] in, , and They are the early code, immediate code and late code correlator outputs of the in-phase channel in the nth coherent integration, and the code spacing is 0.5 code chips. , and are the early and late correlator outputs of the orthogonal channels within the nth coherent integration, respectively.

[0051] Step 3: In the absence of deceptive interference signals, calculate the threshold value of the SQM detection quantity Mpsd(n) according to the preset false alarm rate. The threshold value is calculated as follows: The Mpsd value approximately follows a normal distribution. Theoretically, the high and low thresholds can be solved respectively according to the preset false alarm rate:

[0052] Calculation formula (9)

[0053] Calculation formula (10)

[0054] Its detection probability can also be solved according to the theoretical distribution:

[0055] Calculation formula (11)

[0056] However, due to the time-varying characteristics of the deception process, this application uses a statistical method to determine the detection threshold and detection probability, and the expressions are:

[0057] Calculation formula (12)

[0058] Calculation formula (13)

[0059] Wherein, M and N represent the total number of Mpsd samples without deceptive interference and the total number of Mpsd samples with deceptive interference, respectively, and num(X) represents the number that meets the conditions.

[0060] Step 4: In the absence of deceptive interference signals, perform sliding processing with a fixed-length window to calculate the mean Mpsd-mean (i.e., mean measurement value) and variance Mpsd-var (i.e., variance measurement value) of the SQM detection value Mpsd in the window. Sliding average processing of the obtained Mpsd value can reduce the impact of noise on the algorithm performance, and the window variance can better reflect the fluctuation of Mpsd. Select a suitable sliding window size w, calculate the mean Mpsd-mean and variance Mpsd-var of each window, slide the window forward by a fixed sliding interval, the size of the sliding interval is equal to the length of the window, and repeat the process to form a new data subset. The nth sliding mean and variance results calculated by the sliding window are as follows:

[0061] Calculation formula (14)

[0062] Calculation formula (15)

[0063] Among them, Mpsd(i) represents the i-th sample value in the data, k is the sliding interval, N is the total number of sliding windows; w represents the sliding window length.

[0064] Step 5: In the absence of deceptive interference signals, calculate the threshold values ​​of Mpsd-mean and Mpsd-var according to the preset false alarm rate. The same statistical method as step 3 is used to calculate the Mpsd-mean data set, and the expression is:

[0065] Calculation formula (16)

[0066] in, and express The lower detection threshold and upper detection threshold of Represents the total number of Mpsd-mean samples when there is no deceptive interference.

[0067] The Mpsd-mean detection probability formula is expressed as:

[0068] Calculation formula (17)

[0069] Among them, N-mean represents the total number of Mpsd-mean samples when there is deception interference.

[0070] Similarly, the threshold value and detection probability calculation formula of Mpsd-var is:

[0071] Calculation formula (18)

[0072] Calculation formula (19)

[0073] in, represents the detection threshold corresponding to the variance measurement value, represents the total number of Mpsd-var samples without deception interference, Represents the total number of Mpsd-var samples when deception interference exists.

[0074] Step 6: In the deception jamming detection phase, the Mpsd, Mpsd-mean, and Mpsd-var measurements are calculated in the same manner as in Steps 2 and 4;

[0075] Step 7: In the deception interference detection stage, the calculated Mpsd, Mpsd-mean and Mpsd-var measurement values ​​are compared with the threshold values ​​corresponding to steps 3 and 5 respectively. If they exceed the threshold values, deception interference is considered to exist.

[0076] Step 8: In the deception interference detection stage, finally, the detection probabilities of the three methods, Mpsd, Mpsd-mean and Mpsd-var, are counted.

[0077] This embodiment can overcome the limitations of the traditional SQM spoofing detection method based only on the I branch, introduce the Q branch signal for fusion detection, and use sliding mean processing and sliding variance processing to improve the overall performance of the detection algorithm.

[0078] In addition, this embodiment is based on the TEXBAT data set and uses the method of this embodiment to conduct a comparative experiment. The TEXBAT data set is shown in Table 1 below.

[0079] Table 1

[0080]

[0081] In the table above, "Code Phase Proportion" means that the carrier phase of the spoofed signal is proportional to the code phase change, "Frequency Lock" means that the initial phase offset between the spoofed signal and the real signal remains unchanged throughout the spoofing scenario, and "Carrier Phase Alignment" means that the carrier phase of the spoofed signal is accurately aligned with the carrier phase of the real signal. "Match" means that the spoofed signal is power matched, but the exact value is unknown.

[0082] This example first conducts a performance comparison experiment on the ds2 dataset in the TEXBAT dataset.

[0083] Specifically, see Figure 4 , Figure 4 It is a schematic diagram of the change of the Mpsd detection quantity of the 8-channel captured star under the ds2 data set of an embodiment of the present invention.

[0084] from Figure 4 It can be seen that after the spoofing signal is added to the ds2 dataset at 100s, the amplitude of the Mpsd detection increases significantly around 110s.

[0085] Taking satellite No. 23 as an example, the Ratio, Mpsd, Mpsd-mean and Mpsd-var detection quantities and their detection probabilities and ROC curve comparison diagrams in the ds2 dataset are shown in Figure 5 , Figure 6 and Figure 7 .

[0086] In addition, this embodiment also conducts a performance comparison experiment using the ds3 dataset in the TEXBAT dataset.

[0087] See also Figure 8 , Figure 8 It is a schematic diagram of the change of the Mpsd detection amount of the 8-channel captured star under the ds3 data set in an embodiment of the present invention over time.

[0088] After 100s, the spoofing signal is added to the ds3 dataset. The MPSD detection amount of each channel increases around 119s and changes dramatically between 120s and 250s.

[0089] Taking satellite No. 23 as an example, the Ratio, Mpsd, Mpsd-mean and Mpsd-var detection quantities and their detection probabilities and ROC curve comparison diagrams under the ds3 dataset are shown in Fig. 9 , Fig.10 and Fig.11 .

[0090] It can be concluded from the above simulation results that the detection probability of the method in this embodiment can reach 87.6% in only 120 seconds under the data set ds2, and can maintain a high detection probability of about 90% thereafter, while the detection probability of the traditional Ratio algorithm at 120 seconds is only 30.1%; and under the data set ds3, the overall detection probability of the Mpsd algorithm is also better than the Ratio algorithm; after adopting the window average and window variance algorithms, under the data sets ds2 and ds3, the timeliness and detection probability are greatly improved, and the detection probability of Mpsd-var can reach 100% in 120 seconds and is maintained.

[0091] Compared with the prior art, the method of this embodiment has the following differences:

[0092] 1) Use the I branch and Q branch signals of early code, late code and instant code to construct the detection quantity;

[0093] 2) Using the sum and difference operation of the I branch and Q branch signals will not amplify the slight error of the instant code;

[0094] 3) Utilize the abnormal fluctuations of window mean and variance to detect deceptive interference signals and significantly improve the detection performance.

[0095] The navigation deception interference detection method provided by the embodiment of the present invention, in the deception interference detection stage, uses a satellite navigation receiver to obtain a received signal, performs a cross-correlation operation on the received signal and a replicated pseudo-random code generated locally by the receiver, and obtains an output result of an in-phase branch correlator of an early code, an output result of an in-phase branch correlator of an immediate code, an output result of an in-phase branch correlator of a late code, an output result of an orthogonal branch correlator of an early code, an output result of an orthogonal branch correlator of an immediate code, and an output result of an orthogonal branch correlator of a late code; the output result of the in-phase branch correlator of the early code, the output result of the in-phase branch correlator of the immediate code, and the output result of the orthogonal branch correlator of the late code are output; the output result of the in-phase branch correlator of the early code, the output result of the in-phase branch correlator of the immediate code, and the output result of the in-phase branch correlator of the late code are output; The output result, the output result of the orthogonal branch correlator of the early code, the output result of the orthogonal branch correlator of the instant code and the output result of the orthogonal branch correlator of the late code are summed and differed to construct the SQM detection amount; the received signal is subjected to sliding processing with a preset length window, and the mean measurement value and variance measurement value of the SQM detection amount in the window are calculated; the SQM detection amount, the mean measurement value and the variance measurement value are compared with the corresponding threshold values ​​respectively, and the detection probability of the SQM detection amount, the mean measurement value and the variance measurement value are calculated, and the detection result of the navigation deception interference is determined based on the comparison result and the detection probability. The scheme provided by the present invention introduces the Q branch signal, and uses the I branch and Q branch signal products of the early code, late code and instant code correlators to perform sum and difference operations to construct the detection amount, thereby reducing the influence of the carrier phase difference on the algorithm; at the same time, the scheme uses the sliding window average and variance processing to suppress noise, better reflect the fluctuation of the detection amount, so as to improve the detection performance and enhance the robustness of the detection algorithm.

[0096] In order to implement the method of the embodiment of the present invention, the embodiment of the present invention also provides a navigation deception interference detection device, which includes: a cross-correlation operation module, which is used to use a satellite navigation receiver to obtain a received signal in the deception interference detection stage, and perform a cross-correlation operation on the received signal and a replica pseudo-random code generated locally by the receiver to obtain an in-phase branch correlator output result of the early code, an in-phase branch correlator output result of the instant code, an in-phase branch correlator output result of the late code, an orthogonal branch correlator output result of the early code, an orthogonal branch correlator output result of the instant code, and an orthogonal branch correlator output result of the late code; a first construction module, which is used to output the in-phase branch correlator output result of the early code, the in-phase branch correlator output result of the instant code, and the orthogonal branch correlator output result of the late code. The output result, the output result of the in-phase branch correlator of the late code, the output result of the orthogonal branch correlator of the early code, the output result of the orthogonal branch correlator of the prompt code and the output result of the orthogonal branch correlator of the late code are subjected to sum and difference operations to construct an SQM detection amount; a second construction model is used to perform sliding processing on the received signal with a preset length window, and calculate the mean measurement value and the variance measurement value of the SQM detection amount in the window; a detection module is used to compare the SQM detection amount, the mean measurement value and the variance measurement value with the corresponding threshold values, respectively, and calculate the detection probability of the SQM detection amount, the mean measurement value and the variance measurement value, and determine the detection result of navigation deception interference based on the comparison result and the detection probability.

[0097] The above-mentioned device provided in this embodiment belongs to the same concept as the above-mentioned method embodiment. The specific implementation process thereof is detailed in the method embodiment and will not be repeated here.

[0098] In order to implement the method of the embodiment of the present invention, the embodiment of the present invention also provides a computer program product, which includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps of the above method.

[0099] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiment of the present invention, the embodiment of the present invention further provides an electronic device (computer device). Specifically, in one embodiment, the computer device may be a terminal, and its internal structure diagram may be as follows: Fig.12As shown. The computer device includes a processor A01, a network interface A02, a display screen A04, an input device A05 and a memory (not shown in the figure) connected through a system bus. Among them, the processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A06. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor A01, the method of any one of the above embodiments is implemented. The display screen A04 of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device A05 of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0100] Those skilled in the art will understand that Fig.12 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0101] The device provided by the embodiment of the present invention includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the method of any one of the above embodiments is implemented.

[0102] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0103] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0104] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0105] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0106] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0107] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0108] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0109] It can be understood that the memory of the embodiment of the present invention can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and direct RAMbus random access memory (DRRAM, Direct Rambus Random Access Memory).The memories described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memories.

[0110] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0111] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A navigation deception interference detection method, characterized in that: The method comprises: In the deception interference detection stage, a satellite navigation receiver is used to obtain a received signal, and a cross-correlation operation is performed on the received signal and a replica pseudo-random code generated locally by the receiver to obtain an in-phase branch correlator output result of an early code, an in-phase branch correlator output result of an immediate code, an in-phase branch correlator output result of a late code, an orthogonal branch correlator output result of an early code, an orthogonal branch correlator output result of an immediate code, and an orthogonal branch correlator output result of a late code; Perform sum and difference operations on the output results of the in-phase branch correlator of the early code, the output results of the in-phase branch correlator of the immediate code, the output results of the in-phase branch correlator of the late code, the output results of the orthogonal branch correlator of the early code, the output results of the orthogonal branch correlator of the immediate code and the output results of the orthogonal branch correlator of the late code to construct an SQM detection amount; Perform sliding processing on the received signal with a preset length window, and calculate the mean measurement value and variance measurement value of the SQM detection quantity in the window; Comparing the SQM detection amount, the mean measurement value, and the variance measurement value with corresponding threshold values, respectively, and calculating the detection probability of the SQM detection amount, the mean measurement value, and the variance measurement value, respectively, and determining the detection result of the navigation deception interference based on the comparison result and the detection probability; Before performing a cross-correlation operation on the received signal and the replicated pseudo-random code generated locally by the receiver, the method further includes: down-converting the received signal, and the signal expression after down-conversion is: ； in, is the signal power, D(t) is the data bit stream with a value of ±1, C(t) is the pseudo-random code with a value of ±1, is the carrier phase, j is the imaginary unit, is a natural exponential function; The method for obtaining the threshold value and detection probability corresponding to the mean measurement value includes: in the absence of a deceptive interference signal, sliding processing the received signal with a preset length window, calculating the mean measurement value of the SQM detection amount in the window; obtaining a preset false alarm rate; according to the preset false alarm rate, calculating the threshold value and detection probability corresponding to the mean measurement value; the threshold value corresponding to the mean measurement value can be calculated by the preset false alarm rate, and the calculation formula is: ； The detection probability corresponding to the mean measurement value is: ； in, represents the preset false alarm rate corresponding to the mean measurement value, represents the detection probability corresponding to the mean measurement value; Mpsd-mean(n) represents the mean measurement value; num(X) represents the number of conditions that meet the conditions; and express The lower detection threshold and upper detection threshold of Indicates the total number of Mpsd-mean samples when there is no deception interference; Indicates the total number of Mpsd-mean samples when deception interference exists; The method for obtaining the threshold value and detection probability corresponding to the variance measurement value includes: in the absence of a deceptive interference signal, sliding processing the received signal with a preset length window, calculating the variance measurement value of the SQM detection amount in the window; obtaining a preset false alarm rate; according to the preset false alarm rate, calculating the threshold value and detection probability corresponding to the variance measurement value; the threshold value corresponding to the variance measurement value can be calculated by the preset false alarm rate, and the calculation formula is: ； The detection probability corresponding to the variance measurement value is: ； in, represents the preset false alarm rate corresponding to the variance measurement value, represents the detection probability corresponding to the variance measurement value, represents the variance measurement value; num(X) represents the number of conditions that meet the conditions; represents the detection threshold corresponding to the variance measurement value, represents the total number of Mpsd-var samples without deception interference, Represents the total number of Mpsd-var samples when deception interference exists.

2. The navigation deception interference detection method according to claim 1, characterized in that: The output result of the in-phase branch correlator of the early code is: ； The output result of the in-phase branch correlator of the instant code is: ； The output result of the in-phase branch correlator of the late code is: ； The output result of the orthogonal branch correlator of the early code is: ； The orthogonal branch correlator output result of the instant code is: ； The orthogonal branch correlator output result of the late code is: ； in, The output result of the in-phase branch correlator representing the early code; The orthogonal branch correlator output result representing the early code; Indicates the phase difference between the early code and the local replicated pseudo-random code; The output result of the in-phase branch correlator representing the instant code; The output result of the orthogonal branch correlator representing the instant code; Indicates the phase difference between the instant code and the locally copied pseudo-random code; represents the output result of the in-phase branch correlator of the late code; Q L represents the output result of the orthogonal branch correlator of the late code; Represents the phase difference between the late code and the local replicated pseudo-random code; is the signal power, is the carrier phase, , , , , , represents noise; R() represents the pseudo code normalized autocorrelation function of the phase shift keying signal.

3. The navigation deception interference detection method according to claim 1, characterized in that: The constructed SQM detection volume is: ； Where, Mpsd(n) represents the SQM detection quantity, , and They are the early code, late code and prompt code correlator outputs of the in-phase channel in the nth coherent integration, and the code spacing is 0.5 code chips. , and They are the early code, late code and prompt code correlator outputs of the orthogonal channels in the nth coherent integration.

4. The navigation deception interference detection method according to claim 1, characterized in that: The mean measurements are: ； Where Mpsd-mean represents the mean measurement value; Mpsd(i) represents the i-th sample value in the data, n=1,2,...,N; k is the sliding interval, N is the total number of sliding windows; w represents the length of the sliding window; The variance measure is: ； Where Mpsd-var(n) represents the variance measurement; Mpsd(i) represents the i-th sample value in the data; n=1,2,...,N; k is the sliding interval, N is the total number of sliding windows; w represents the length of the sliding window.

5. The navigation deception interference detection method according to claim 1, characterized in that: The method for obtaining the threshold value and detection probability corresponding to the SQM detection quantity includes: Construct SQM detection volume without deceptive interference signals; Obtaining a preset false alarm rate; calculating a threshold value and a detection probability corresponding to the SQM detection amount according to the preset false alarm rate; The threshold value corresponding to the SQM detection quantity can be calculated by the preset false alarm rate, and the calculation formula is: ； The detection probability corresponding to the SQM detection amount is: ； in, Indicates the preset false alarm rate, represents the detection probability corresponding to the SQM detection amount; M and N represent the total number of Mpsd samples without deception interference and the total number of Mpsd samples with deception interference, respectively; num(X) represents the number that meets the conditions; Mpsd(n) represents the SQM detection amount; Indicates the high threshold corresponding to the preset false alarm rate; Indicates the lower threshold corresponding to the preset false alarm rate.

6. A navigation deception interference detection device, characterized in that: The navigation deception interference detection device comprises: A cross-correlation operation module is used to obtain a received signal using a satellite navigation receiver during a deception interference detection phase, and to perform a cross-correlation operation on the received signal and a replica pseudo-random code generated locally by the receiver to obtain an output result of an in-phase branch correlator of an early code, an output result of an in-phase branch correlator of an immediate code, an output result of an in-phase branch correlator of a late code, an output result of an orthogonal branch correlator of an early code, an output result of an orthogonal branch correlator of an immediate code, and an output result of an orthogonal branch correlator of a late code; The first construction module is used to perform sum and difference operations on the output results of the in-phase branch correlator of the early code, the output results of the in-phase branch correlator of the instant code, the output results of the in-phase branch correlator of the late code, the output results of the orthogonal branch correlator of the early code, the output results of the orthogonal branch correlator of the instant code and the output results of the orthogonal branch correlator of the late code to construct an SQM detection amount; The second model is constructed to perform sliding processing on the received signal with a preset length window, and calculate the mean measurement value and the variance measurement value of the SQM detection amount in the window; a detection module, configured to compare the SQM detection amount, the mean measurement value, and the variance measurement value with corresponding threshold values, respectively, and calculate the detection probability of the SQM detection amount, the mean measurement value, and the variance measurement value, respectively, and determine the detection result of navigation deception interference based on the comparison result and the detection probability; The cross-correlation operation module is also specifically used to down-convert the received signal before performing a cross-correlation operation on the received signal and the replicated pseudo-random code generated locally by the receiver. The down-converted signal expression is: ； in, is the signal power, D(t) is the data bit stream with a value of ±1, C(t) is the pseudo-random code with a value of ±1, is the carrier phase, j is the imaginary unit, is a natural exponential function; The method for obtaining the threshold value and detection probability corresponding to the mean measurement value includes: in the absence of a deceptive interference signal, sliding processing the received signal with a preset length window, calculating the mean measurement value of the SQM detection amount in the window; obtaining a preset false alarm rate; according to the preset false alarm rate, calculating the threshold value and detection probability corresponding to the mean measurement value; the threshold value corresponding to the mean measurement value can be calculated by the preset false alarm rate, and the calculation formula is: ； The detection probability corresponding to the mean measurement value is: ； in, represents the preset false alarm rate corresponding to the mean measurement value, represents the detection probability corresponding to the mean measurement value; Mpsd-mean(n) represents the mean measurement value; num(X) represents the number of conditions that meet the conditions; and express The lower detection threshold and upper detection threshold of Indicates the total number of Mpsd-mean samples when there is no deception interference; Indicates the total number of Mpsd-mean samples when deception interference exists; The method for obtaining the threshold value and detection probability corresponding to the variance measurement value includes: in the absence of a deceptive interference signal, sliding processing the received signal with a preset length window, calculating the variance measurement value of the SQM detection amount in the window; obtaining a preset false alarm rate; according to the preset false alarm rate, calculating the threshold value and detection probability corresponding to the variance measurement value; the threshold value corresponding to the variance measurement value can be calculated by the preset false alarm rate, and the calculation formula is: ； The detection probability corresponding to the variance measurement value is: ； in, represents the preset false alarm rate corresponding to the variance measurement value, represents the detection probability corresponding to the variance measurement value, represents the variance measurement value; num(X) represents the number of conditions that meet the conditions; represents the detection threshold corresponding to the variance measurement value, represents the total number of Mpsd-var samples without deception interference, Represents the total number of Mpsd-var samples when deception interference exists.

7. An electronic device, characterized in that: include: A processor and a memory for storing a computer program that can be run on the processor; wherein, when the processor is used to run the computer program, the steps of the method according to any one of claims 1 to 5 are executed.

Images