GNSS signal angle of arrival estimation and consistency detection method and apparatus

Abstract

The application relates to a GNSS signal angle of arrival estimation and consistency detection method and device, which realizes independent monitoring of multi-source spoofing signals by synchronously collecting homologous navigation signals and rotating azimuth angle sampling values through double antennas, and solves a cosine mathematical model by combining single-difference carrier phase measurement values and azimuth angle sampling values with the aid of carrier phase observation values received by double radio frequency channels, thereby greatly improving AOA estimation accuracy, meeting high-precision spoofing interference monitoring and directional requirements, calculating a theoretical angle of arrival based on receiver position information and ephemeris data, identifying suspicious spoofing signals with deviation exceeding the limit through consistency detection, providing key support for multi-source spoofing interference orientation and positioning, effectively solving the problem that the effect of traditional methods in dealing with spatially distributed multi-source spoofing interference is poor, and realizing low complexity, and being suitable for safety-sensitive GNSS application scenarios of key infrastructures such as airports and ports.

Description

Technical Field

[0001] This application relates to the field of satellite navigation deception and interference signal monitoring technology, and in particular to a method and apparatus for GNSS signal angle of arrival estimation and consistency detection. Background Technology

[0002] Satellite navigation spoofing interference poses a serious security risk to GNSS applications. Because civilian satellite navigation signal systems are publicly available, real satellite signals can easily be artificially simulated to generate similar false signals. By broadcasting false signals simulating real satellites to victim receivers, the receivers output incorrect position, velocity, and time (PVT) results. The implementation of spoofing signals typically leads to serious malfunctions in PVT-related infrastructure and security-sensitive GNSS applications, especially in locations such as airports, ports, and railways. In recent years, with the widespread adoption of low-cost software-defined radio equipment and high-fidelity simulators, the technical barrier to implementing spoofing attacks has significantly decreased, leading to a gradual increase in successful satellite navigation spoofing interference, resulting in a sharp rise in GNSS security risks. These developments urgently necessitate more precise spoofing interference monitoring and direction finding systems. Since current spoofing signals struggle to maintain consistency with the Angle of Arrival (AOA) of all satellite signals in the actual constellation, GNSS signal AOA estimation and consistency detection are core technologies and key devices for improving the performance of spoofing interference monitoring and direction finding systems.

[0003] Traditional methods for detecting GNSS spoofing signals include receiver-internal signal processing (monitoring carrier-to-noise ratio, carrier phase, clock variations, etc.) and methods utilizing the relative geometric constraints between two or more antennas. However, existing solutions rely on assumptions such as the satellite signal being normal at the initial receiver startup or all spoofed satellite signals being transmitted from a single antenna. Therefore, they are ineffective against spatially distributed multi-source spoofing interference. Summary of the Invention

[0004] Therefore, it is necessary to provide a method and apparatus for GNSS signal angle of arrival estimation and consistency detection that can efficiently detect multi-source spoofing and accurately orient the signal, in order to address the above-mentioned technical problems.

[0005] A method for GNSS signal angle of arrival estimation and consistency detection, the method comprising:

[0006] The satellite navigation signal is acquired by a rotating dual-antenna receiver that synchronously collects two sets of identical navigation signals emitted by the same satellite, as well as a rotating azimuth angle sample value that is synchronized with the acquisition timing of the two sets of identical navigation signals.

[0007] The two sets of co-source navigation signals are processed to obtain ephemeris data and two sets of carrier phase observations corresponding to the rotating dual-antenna receiver;

[0008] The difference between the two sets of carrier phase observations is calculated to obtain the single-difference carrier phase measurement. Combined with the azimuth angle sampling value, a cosine mathematical model is constructed to show the variation of the single-difference carrier phase measurement with the azimuth angle sampling value. Based on the cosine mathematical model, integer ambiguity and cycle slip detection are estimated and verified.

[0009] Based on the integer ambiguity, the elevation and azimuth angles of a single satellite signal are inferred through spatial geometric relationships to obtain the signal angle of arrival estimation result;

[0010] Based on the position information of the rotating dual-antenna receiver and the ephemeris data, the theoretical angle of arrival of the satellite signal is obtained, and consistency detection is performed on the estimated angle of arrival of the signal and the theoretical angle of arrival of the satellite signal.

[0011] In one embodiment, estimating and verifying integer ambiguity and detecting cycle slips based on the cosine mathematical model includes:

[0012] The cosine mathematical model is linearized by introducing transformation parameters. A system of linear equations is constructed and solved using multi-epoch rotating azimuth angle sampling values ​​and single-difference carrier phase measurement values ​​to obtain the floating-point solution of integer ambiguity.

[0013] Calculate the maximum amplitude of the single-difference carrier phase residual, compare the maximum amplitude with a preset threshold, and determine that a cycle slip exists when the maximum amplitude exceeds the preset threshold;

[0014] Two sets of single-difference carrier phase measurements with an azimuth angle difference of 180° were selected. The two sets of measurements were added together and divided by 2. The result was rounded to the nearest integer to complete the fixation of integer ambiguity.

[0015] In one embodiment, the cosine-type mathematical model after introducing transformation parameters is expressed as:

[0016]

[0017] In the above formula, The sampling index represents the rotation azimuth angle. Indicates the carrier wavelength of the navigation signal. Indicates the time-varying azimuth of the baseline. Indicates the radius of rotation. , Indicates the introduced transformation parameters, Indicates the integer ambiguity of redundant parameters. This indicates single-difference carrier phase single-difference observation noise.

[0018] In one embodiment, a consistency check is performed on the estimated angle of arrival of the signal and the theoretical angle of arrival of the satellite signal, including:

[0019] A Mahalanobis distance statistic is constructed. After converting the estimated angle of arrival of the signal and the theoretical angle of arrival into parameters in a unified coordinate system, the deviation value is calculated by substituting them into the Mahalanobis distance statistic.

[0020] When the deviation value exceeds the preset detection threshold, the currently acquired satellite navigation signal is determined to be a suspicious deception signal. The detection threshold is determined by the false alarm probability and satisfies the right-tail probability distribution characteristics.

[0021] This application also provides a GNSS signal angle of arrival estimation and consistency detection device, the device comprising: a rotating dual-antenna assembly, a rotating drive module with an optoelectronic code disk, a dual-RF channel GNSS receiving module, a rotating joint, and a signal processing unit;

[0022] The rotating dual-antenna assembly consists of two GNSS antennas connected by a rigid structure to form a fixed-length baseline. It is horizontally arranged and symmetrical about the rotation center axis, and is used to synchronously acquire navigation signals from the same source emitted by the same satellite.

[0023] The rotation drive module containing the photoelectric encoder disk is mechanically coupled to the rotating dual antenna assembly, which is used to drive the rotating dual antenna assembly to rotate at a constant speed and to collect the rotation azimuth angle sampling value in real time.

[0024] The dual-RF channel GNSS receiver module has an internal common clock design. The two RF input terminals are connected one-to-one with the two GNSS antennas of the rotating dual antenna assembly through the rotating joint. It is used to receive and synchronously process the same source navigation signal, and output ephemeris data, two sets of carrier phase observation values ​​and second pulse synchronization signal.

[0025] The signal processing unit is used to execute the above-mentioned GNSS signal angle of arrival estimation and consistency detection method based on the rotation azimuth angle sampling value, ephemeris data and two sets of carrier phase observation values, to obtain a detection result including the angle of arrival estimation result and the suspicious signal mark, and to send the detection result to the user terminal through the rotation joint.

[0026] In one embodiment, the photoelectric encoder receives the second pulse synchronization signal output by the dual-RF channel GNSS receiving module, thereby synchronizing the acquisition timing of the rotation azimuth angle sampling value and the carrier phase observation value.

[0027] In one embodiment, the rotating dual-antenna assembly has a rotation radius of 0.32 meters and a rotation angular velocity of 72° / s;

[0028] The carrier phase observation update rate of the dual-RF channel GNSS receiver module is 5Hz, and the standard deviation of the carrier phase measurement noise is better than 1 / 40 cycle.

[0029] In one embodiment, the rotating dual-antenna assembly receives the L1 C / A navigation signal from GPS.

[0030] In one embodiment, the rotary joint is a rotary slip ring.

[0031] The aforementioned GNSS signal angle of arrival estimation and consistency detection method and device, through the design of synchronously acquiring the same satellite's homogeneous navigation signal with rotating dual antennas and synchronously obtaining the rotating azimuth angle sampling value, breaks through the traditional method's assumption of a normal initial receiver signal and a single-source transmission of spoofing signals. It can achieve independent monitoring of multi-source spoofing signals without relying on the legitimacy judgment of the initial signal. Utilizing the technical characteristics of a dual-RF channel common-clock receiving module to process signals and output carrier phase observation values, it constructs a cosine-based mathematical model by combining single-difference carrier phase measurements and azimuth angle sampling values. Then, by solving the cosine-based mathematical model, it significantly improves the accuracy and consistency of GNSS signal acquisition. It improves the estimation accuracy of the angle of arrival (AOA) of a single satellite, meeting the needs for higher precision spoofing interference monitoring and orientation. At the same time, it also uses the core logic of calculating the theoretical angle of arrival based on receiver position information and ephemeris data, and accurately identifies suspicious spoofing signals when the deviation between the estimated AOA and the theoretical AOA exceeds the limit through consistency detection. This provides key support for the orientation and positioning of multi-source spoofing interference, effectively solving the technical problem that traditional methods are not effective in dealing with spatially distributed multi-source spoofing interference. Moreover, the overall implementation has low complexity and is suitable for security-sensitive GNSS application scenarios such as airports and ports. Attached Figure Description

[0032] Figure 1 This is a flowchart illustrating a GNSS signal angle of arrival estimation and consistency detection method in one embodiment;

[0033] Figure 2 This is a schematic diagram illustrating an embodiment where the angle of arrival of the spoofed signal received by the rotating dual antennas is inconsistent with that of the actual satellite signal.

[0034] Figure 3 This is a schematic diagram of the geometric model of a rotating dual antenna and a GNSS satellite signal in one embodiment;

[0035] Figure 4 This is a comparison chart of the GNSS angle of arrival estimation result based on rotating dual antennas and the actual satellite angle in one embodiment;

[0036] Figure 5 This is a diagram showing the GNSS angle-of-arrival consistency detection results based on a rotating dual-antenna system in one embodiment. Figure 5(a) Schematic diagram showing the test statistic for unbiased azimuth. Figure 5 (b) A schematic diagram showing the test statistic for the existence of a deviation in the azimuth angle;

[0037] Figure 6 This is a schematic diagram of the structure of a GNSS signal angle of arrival estimation and consistency detection device in one embodiment;

[0038] Figure 7 This is a block diagram of a GNSS signal angle of arrival estimation and consistency detection device in one embodiment;

[0039] Figure 8 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0041] In this application, as Figure 1 As shown, a method for GNSS signal angle of arrival estimation and consistency detection is provided, which specifically includes the following steps:

[0042] Step S100: Acquire satellite navigation signals. The satellite navigation signals are acquired by a rotating dual-antenna receiver, which synchronously collects two sets of source navigation signals emitted by the same satellite, as well as the rotation azimuth angle sampling value that is synchronized with the acquisition timing of the two sets of source navigation signals.

[0043] Step S110: Process the two sets of navigation signals from the same source to obtain ephemeris data and two sets of carrier phase observations from the corresponding rotating dual-antenna receiver.

[0044] Step S120: Calculate the difference between the two sets of carrier phase observations to obtain the single-difference carrier phase measurement value. Combine the azimuth angle sampling value to construct a cosine mathematical model of the single-difference carrier phase measurement value as a function of the azimuth angle sampling value. Estimate and verify the integer ambiguity and detect cycle slip based on the cosine mathematical model.

[0045] Step S130: Based on the integer ambiguity, the elevation angle and azimuth angle of the single satellite signal are inferred through spatial geometric relationships to obtain the signal arrival angle estimation result.

[0046] Step S140: Based on the position information of the rotating dual-antenna receiver and the ephemeris data, the theoretical angle of arrival of the satellite signal is obtained, and a consistency check is performed on the signal angle of arrival estimation result and the theoretical angle of arrival of the satellite signal.

[0047] This application addresses the serious security risks posed by spoofing interference to GNSS applications. These attacks deceive receivers by transmitting forged signals that mimic legitimate signals, causing them to return incorrect position, velocity, and time calculations. Spoofing can lead to severe failures in critical infrastructure and security-sensitive applications, particularly in key locations such as airports, ports, and railways. For genuine GNSS signals, the angle of arrival (AOA) can be predicted using satellite positions derived from ephemeris data and the receiver's approximate position. However, even in advanced multi-antenna spoofing attacks, the physical limitations of the spoofing device deployment environment inevitably result in discrepancies between the predicted AOA and the actual satellite signal direction. This means that the satellite signal angle of arrival (AOA) can serve as a crucial basis for detecting and locating spoofed signals. Therefore, this method combines such algorithms with a low-cost rotation angle measurement sensor.

[0048] The core processes of steps S100 and S110 are as follows: Two sets of homogeneous navigation signals emitted by the same satellite are synchronously acquired using a rotating dual-antenna receiver, along with rotational azimuth angle sampling values ​​that are strictly synchronized with the acquisition sequence of these two sets of homogeneous navigation signals; simultaneously, the two sets of homogeneous navigation signals are processed synchronously to obtain ephemeris data and two sets of carrier phase observations corresponding to the rotating dual-antenna receiver. The relevant hardware configuration has been detailed in the device section below and will not be repeated here.

[0049] In step S120, since GNSS spoofing sources typically distort the true AOA of satellite signals, such as... Figure 2 As shown, this affects the time difference of arrival (TDOA) between the two antenna signals. Figure 3 As shown, when antennas A and B of a dual-antenna clock receiver operate simultaneously, the spoofing source simulates a satellite signal and transmits it to both antennas simultaneously. The carrier phase measurement of the spoofing signal received by antenna A is shown. It can be modeled as:

[0050] (1)

[0051] In formula (1), The sampling index represents the rotation azimuth angle. Indicates the carrier wavelength of the GNSS signal. This represents the geometric distance from the satellite to the virtual location. This represents the distance from the deception source to antenna A. Indicates receiver clock bias. This represents the integer ambiguity of the receiver at antenna A.

[0052] Similarly, the carrier phase measurement of the spoofing signal received by antenna B It can be represented as:

[0053] (2)

[0054] In formula (2), Indicates the ionospheric error of the satellite. Indicates the tropospheric error of the satellite. Indicates satellite clock bias, This represents the carrier phase measurement noise of antenna B.

[0055] Therefore, the single-difference carrier phase (SDCP) measurement between antenna A and antenna B reflects the arrival time difference of the spoofing signal, and is expressed as:

[0056] (3)

[0057] in

[0058]

[0059] like Figure 3 As shown, the dual-antenna rotating receiver rotates clockwise around the origin of the East-North-Earth (ENU) coordinate system. The plane of rotation is horizontal, and antennas A and B are rigidly mounted on this plane, forming a fixed-length baseline. The rotational angular velocity is... The time-varying azimuth of the baseline is denoted as The deception at point P is caused by the angle of elevation. and azimuth Definition, according to Figure 2 The geometric configuration shown represents the path difference of the spoofing signal between the two antennas. It can be represented as:

[0060] (4)

[0061] In formula (4), This represents the distance from the source of the deception to a certain point. Indicates the radius of rotation. Let be the rotation angle at epoch n. The location of the deception source is usually much larger than the rotation radius of the dual-antenna system (generally, d ≥ 100 meters, while r ≤ 2 meters). Under these conditions, the distance difference can be approximated as:

[0062] (5)

[0063] Furthermore, by combining equations (5) and (3), we can obtain:

[0064] (6)

[0065] For the special case of uniform rotation, the single difference of Doppler measurements can also be used for AOA estimation, and the process is expressed as follows:

[0066] (7)

[0067] In formula (7), This represents the single difference between the Doppler measurements at epoch n. For a constant angular velocity, It is a single difference of Doppler noise. and These are unknown parameters to be estimated.

[0068] In this embodiment, for the observation model represented by formula (6), namely the cosine mathematical model of the change of single-difference carrier phase measurement value with the sampling value of dual-antenna baseline azimuth angle, this involves the AOA parameters under the condition of known multi-epoch rotation angle. and Nonlinear estimation is performed, and redundant parameter integer ambiguity is also handled. And the cycle slip problem that may occur in the carrier phase.

[0069] Specifically, the estimation and verification of integer ambiguity and detection of cycle slips based on a cosine-based mathematical model include: introducing transformation parameters to linearize the cosine-based mathematical model; constructing and solving a system of linear equations using multi-epoch rotating azimuth angle sampling values ​​and single-difference carrier phase measurement values ​​to obtain the floating-point solution of the integer ambiguity; calculating the maximum amplitude of the single-difference carrier phase residual; comparing the maximum amplitude with a preset threshold; determining the presence of a cycle slip when the maximum amplitude exceeds the preset threshold; selecting two sets of single-difference carrier phase measurement values ​​with an azimuth angle difference of 180°; adding the two sets of measurement values ​​and dividing by 2; rounding the result to the nearest integer to complete the fixation of the integer ambiguity.

[0070] In this embodiment, the following transformation parameters are introduced to linearize the nonlinear problem:

[0071] (8)

[0072] Then the SDCP observation model, i.e., the cosine mathematical model, in formula (6) can be rewritten as:

[0073] (9)

[0074] In formula (9), The sampling index represents the rotation azimuth angle. Indicates the carrier wavelength of the navigation signal. Indicates the time-varying azimuth of the baseline. Indicates the radius of rotation. , Indicates the introduced transformation parameters, Indicates the integer ambiguity of redundant parameters. This indicates single-difference carrier phase single-difference observation noise.

[0075] Furthermore, when solving formula (9), this is a classic linear estimation problem, and its solution can be expressed as:

[0076] (10)

[0077] In formula (10):

[0078] (11)

[0079] (12)

[0080] Furthermore, the floating-point solution of the ambiguity parameter is rounded to the nearest integer to obtain:

[0081] (13)

[0082] In formula (13), This indicates rounding to the nearest integer. The SDCP residual can be calculated using the preliminary AOA in formula (10) and the fixed solution in formula (13) as follows:

[0083] (14)

[0084] SDCP residuals are used to construct test statistics to verify data quality in the following ways:

[0085] (15)

[0086] In formula (15), , It is determined by the variance of the carrier phase observation noise. This is the detection threshold determined based on the false alarm probability. When a single or multiple cycle slips occur, it affects the integer ambiguity resolution, leading to an increase in the residual amplitude.

[0087] In this embodiment, cycle slip detection is performed using the maximum amplitude of the SDCP residual, specifically implemented in the following manner:

[0088] (16)

[0089] In formula (16), This is the cycle slip detection threshold. Since the carrier phase accuracy is consistently better than 1 / 40 of a cycle, to avoid the occurrence of the minimum half-cycle slip, a threshold is set... =0.25 weeks. If either condition of formula (15) or formula (16) is met, the data segment is marked as undetectable.

[0090] Furthermore, for the special case of uniform rotation, the antenna exchange method can be used to fix the integer ambiguity. By reasonably designing the rotation speed and carrier phase output update rate, single-difference results can be obtained at two positions with an azimuth angle difference of 180°. Then, the floating-point solution of the integer ambiguity can be quickly obtained through the following equation:

[0091] (17)

[0092] Specifically, in the process of estimating and verifying integer ambiguity, the initial value of AOA can also be obtained by solving formula (7).

[0093] In step S130, once the integer ambiguity is fixed, the estimation problem is separated into spatial and temporal components, transforming it into a purely real-valued optimization problem. After fixing the integer ambiguity, the rotational SDCP model in the above formula (9) can be simplified to:

[0094] (18)

[0095] In formula (18), SDCP noise measured in meters is typically considered additive white Gaussian noise. , The definition is as follows:

[0096] (19)

[0097] Using the least squares method to solve formula (19), the solution can be expressed as:

[0098] (20)

[0099] in

[0100]

[0101]

[0102] Then, we can start from the transformed parameters. and Recover AOA parameters (e.g.) Figure 4 The estimated angle of arrival of each satellite shown is represented as:

[0103] (twenty one)

[0104] (twenty two)

[0105] Due to the influence of noise, It may exceed 1, leading to There are no real solutions. To avoid this problem, when At that time, Set to 1. However, this adjustment will have an impact on low elevation angles. The estimation introduces bias.

[0106] In step S140, based on the position information and ephemeris data of the rotating dual-antenna receiver, the theoretical angle of arrival of the satellite signal is obtained, such as... Figure 4 The actual angle of arrival (AHA) results for each satellite are obtained. Consistency checks are performed on the estimated AHA and the theoretical AHA of the satellite signals. This includes: constructing a Mahalanobis distance statistic; converting the estimated AHA and theoretical AHA into parameters in a unified coordinate system; substituting these parameters into the Mahalanobis distance statistic to calculate the deviation; and determining the acquired satellite navigation signal as a suspicious spoofing signal if the deviation exceeds a preset detection threshold. The detection threshold is determined by the false alarm probability and satisfies the right-tail probability distribution characteristics.

[0107] In this embodiment, after completing a full rotation, the AOA of the signal can be estimated using formulas (21) and (22). The consistency between the spoofed signal and the real signal can be detected by comparing the estimated AOA with the satellite angle calculated from ephemeris data. For spoofed signals, the estimated angle represents the true direction of arrival of the spoofing source; while for real GNSS signals, the estimated angle matches the satellite angle derived from ephemeris. A 100 km error will result in a prediction error of approximately 0.29° in the angle of arrival. Therefore, the consistency of the angle of arrival detection has strong robustness to the positioning results. The angle of arrival discrimination criterion can be expressed as:

[0108] (twenty three)

[0109] In formula (23), This represents the parameters of the AOA obtained from ephemeris data after coordinate transformation, and its calculation method is the same as that of formula (8). The AOA consistency detector determines the following conditions: :

[0110] (twenty four)

[0111] In formula (24), It is determined by the false alarm probability The determined detection threshold is expressed as:

[0112] (25)

[0113] In formula (25), It is for the threshold The right-tail probability. For example... Figure 5 As shown, under the null hypothesis Down, Approximately follows the parameter: of If the signal is distributed correctly, it is classified into a normal subset; otherwise... Accordingly, it approximately conforms to non-central The signal is distributed and will be marked as a suspicious signal.

[0114] In the aforementioned GNSS signal angle of arrival estimation and consistency detection method, the rotating dual-antenna receiver synchronously acquires the same satellite's same-source navigation signal and the time-synchronized rotation azimuth angle sampling value. This eliminates the need for pre-setting the initial signal's legality; instead, it processes each satellite signal independently based on real-time acquired data on the phase difference and rotation angle correlation between the two signals. This method is naturally adapted to multi-source deception scenarios with spatial distribution, overcoming the traditional method's assumption of single-source deception. By calculating the single-difference carrier phase measurement value and constructing a cosine-type mathematical model, the nonlinear angle of arrival estimation problem is transformed into a solvable linear equation. Combined with integer ambiguity resolution and cycle slip detection, it effectively offsets the effects of measurement noise and signal interference, significantly improving the accuracy of single-satellite AOA estimation. This meets the core requirements for higher-precision deception interference monitoring and orientation. Furthermore, consistency detection is performed by calculating the theoretical angle of arrival based on the receiver position and ephemeris data. Utilizing the inherent differences in AOA between real satellites and deception signals, it accurately identifies suspicious deception signals using objective deviation judgment logic, without relying on internal receiver signal feature monitoring, thus avoiding the susceptibility to interference inherent in traditional methods.

[0115] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0116] like Figure 6As shown in the figure, this application also provides a GNSS signal angle of arrival estimation and consistency detection device. This device includes: a rotating dual-antenna assembly, a rotating drive module with an optoelectronic code disk, a dual-RF channel GNSS receiving module, a rotating joint, and a signal processing unit. The rotating dual-antenna assembly consists of two GNSS antennas connected by a rigid structure to form a fixed-length baseline. It is horizontally positioned and symmetrical about the rotation center axis, used to synchronously acquire navigation signals from the same source transmitted by the same satellite. The rotating drive module with the optoelectronic code disk is mechanically coupled to the rotating dual-antenna assembly, used to drive the rotating dual-antenna assembly to rotate at a uniform speed and acquire the rotation azimuth angle sampling value in real time. The dual-RF channel GNSS receiving module has an internal common-clock design. Its two RF input terminals are connected one-to-one with the two GNSS antennas of the rotating dual-antenna assembly through the rotating joint, used to receive and synchronously process the navigation signals from the same source, outputting ephemeris data, two sets of carrier phase observations, and a second pulse synchronization signal. The signal processing unit is used to perform the above-mentioned GNSS signal angle of arrival estimation and consistency detection method based on the rotation azimuth angle sampling value, ephemeris data and two sets of carrier phase observation values, to obtain the detection result including the angle of arrival estimation result and the suspicious signal mark, and to send the detection result to the user terminal through the rotation joint.

[0117] In this embodiment, the photoelectric encoder receives the second pulse synchronization signal output by the dual-radio frequency channel GNSS receiving module, thereby synchronizing the acquisition timing of the rotating azimuth angle sampling value and the carrier phase observation value.

[0118] In this embodiment, the rotation radius of the rotating dual-antenna assembly is 0.32 meters, and the baseline length is adapted to the spatial geometric constraints of this radius to ensure the accuracy of the path difference approximation under far-field conditions (spoofing source distance ≥ 100 meters). The rotation angular velocity of the rotating dual-antenna assembly is 72° / s, so it completes one rotation in 5 seconds, balancing the number of sampling points and elevation angle stability (the elevation angle can be considered constant within a short period).

[0119] In this embodiment, a rotating dual-antenna assembly receives the GPS L1 C / A navigation signal. The related module for processing the signal uses a dual-RF channel GNSS orientation board with a carrier phase observation update rate of 5Hz. The GNSS receiving module calculates SDCP measurements based on this signal, adapting the algorithm to meet the high accuracy requirements of the carrier phase (measurement noise standard deviation better than 1 / 40 cycle).

[0120] In this embodiment, the rotary joint uses a rotary slip ring.

[0121] Regarding the specific execution of steps S120 to S140 in the aforementioned GNSS signal angle of arrival estimation and consistency detection method within the signal processing unit, for specific limitations, please refer to the limitations of this method described above, which will not be repeated here. Each unit and module in the above transpose can be implemented entirely or partially through software, hardware, or a combination thereof. For example, functions such as integer ambiguity resolution and AOA estimation can be implemented by running algorithm programs on an embedded processor, while rotating joints (slip rings) are hardware components.

[0122] The aforementioned GNSS signal angle of arrival estimation and consistency detection device, relying on the rotating dual-antenna assembly, leverages its structural advantages of rigid connection, fixed-length baseline, and symmetrical horizontal layout along the central axis. This allows for stable and synchronous acquisition of navigation signals from the same satellite, avoiding signal acquisition deviations during rotation and providing high-quality raw data for subsequent phase difference calculations. The rotation drive module, containing the photoelectric encoder, drives the dual antennas to rotate at a uniform speed. The synchronously acquired rotational azimuth angle sampling values ​​are strictly aligned with the second pulse synchronization signal of the dual-RF channel GNSS receiving module, ensuring timing consistency between signal acquisition and angle sampling, laying a precise timing foundation for the construction of the cosine mathematical model. The internal common-clock design of the dual-RF channel GNSS receiving module effectively cancels out inter-channel clock errors, resulting in a measurement noise standard deviation of better than 1 / 40 cycle for the two sets of output carrier phase observations, significantly improving the accuracy of single-difference carrier phase calculations. The rotating joint (slip ring) constructs a tangle-free transmission link, ensuring stable and attenuated signal and data transmission while supporting long-term continuous operation of the device.

[0123] The signal processing unit, by executing the detection method proposed in this paper, accurately completes integer ambiguity resolution, cycle slip detection, angle of arrival estimation, and consistency verification. It overcomes the limitations of traditional methods that rely on assumptions of normal initial signals and single-source spoofing, independently identifying spatially distributed multi-source spoofing signals. Its output angle of arrival estimation results deviates little from the true angle. Combined with theoretical angle of arrival derived from ephemeris and Mahalanobis distance statistics, it can accurately mark suspicious signals with excessive deviations, providing crucial data support for the orientation and localization of multi-source spoofing interference. The overall device has low implementation complexity and strong operational robustness, making it suitable for security-sensitive GNSS applications such as airports, ports, and railways. It effectively addresses the shortcomings of traditional monitoring equipment, such as poor performance and insufficient estimation accuracy in dealing with multi-source spoofing interference, providing reliable anti-spoofing security for GNSS systems.

[0124] In one embodiment, such as Figure 7 As shown, a GNSS signal angle of arrival estimation and consistency detection device is provided, including: a satellite navigation signal acquisition module 200, a signal processing module 210, an integer ambiguity determination module 220, a signal angle of arrival estimation module 230, and a consistency detection module 240, wherein:

[0125] The satellite navigation signal acquisition module 200 is used to acquire satellite navigation signals, which are obtained by a rotating dual-antenna receiver that synchronously acquires two sets of homogeneous navigation signals emitted by the same satellite, as well as rotating azimuth angle sampling values ​​that are synchronized with the acquisition timing of the two sets of homogeneous navigation signals.

[0126] The signal processing module 210 is used to process the two sets of navigation signals from the same source to obtain ephemeris data and two sets of carrier phase observations corresponding to the rotating dual-antenna receiver.

[0127] The integer ambiguity determination module 220 is used to calculate the difference between the two sets of carrier phase observations to obtain the single-difference carrier phase measurement value. Combined with the azimuth angle sampling value, a cosine mathematical model is constructed to show the change of the single-difference carrier phase measurement value with the azimuth angle sampling value. Based on the cosine mathematical model, the integer ambiguity is estimated and verified and the cycle slip is detected.

[0128] The signal angle of arrival estimation module 230 is used to infer the elevation angle and azimuth angle of a single satellite signal based on the integer ambiguity and spatial geometric relationships to obtain the signal angle of arrival estimation result.

[0129] The consistency detection module 240 is used to obtain the theoretical angle of arrival of the satellite signal based on the position information of the rotating dual-antenna receiver and the ephemeris data, and to perform consistency detection on the estimated angle of arrival of the signal and the theoretical angle of arrival of the satellite signal.

[0130] Specific limitations regarding the GNSS signal angle of arrival estimation and consistency detection device can be found in the limitations of the GNSS signal angle of arrival estimation and consistency detection method described above, and will not be repeated here. Each module in the aforementioned GNSS signal angle of arrival estimation and consistency detection device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independent of the processor in a computer device, or stored in software in the memory of a computer device, so that the processor can call and execute the corresponding operations of each module.

[0131] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 8As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When executed by the processor, the computer program implements a GNSS signal angle of arrival estimation and consistency detection method. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0132] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0133] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0134] The satellite navigation signal is acquired by a rotating dual-antenna receiver that synchronously collects two sets of identical navigation signals emitted by the same satellite, as well as a rotating azimuth angle sample value that is synchronized with the acquisition timing of the two sets of identical navigation signals.

[0135] The two sets of co-source navigation signals are processed to obtain ephemeris data and two sets of carrier phase observations corresponding to the rotating dual-antenna receiver;

[0136] The difference between the two sets of carrier phase observations is calculated to obtain the single-difference carrier phase measurement. Combined with the azimuth angle sampling value, a cosine mathematical model is constructed to show the variation of the single-difference carrier phase measurement with the azimuth angle sampling value. Based on the cosine mathematical model, integer ambiguity and cycle slip detection are estimated and verified.

[0137] Based on the integer ambiguity, the elevation and azimuth angles of a single satellite signal are inferred through spatial geometric relationships to obtain the signal angle of arrival estimation result;

[0138] Based on the position information of the rotating dual-antenna receiver and the ephemeris data, the theoretical angle of arrival of the satellite signal is obtained, and consistency detection is performed on the estimated angle of arrival of the signal and the theoretical angle of arrival of the satellite signal.

[0139] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0140] The satellite navigation signal is acquired by a rotating dual-antenna receiver that synchronously collects two sets of identical navigation signals emitted by the same satellite, as well as a rotating azimuth angle sample value that is synchronized with the acquisition timing of the two sets of identical navigation signals.

[0141] The two sets of co-source navigation signals are processed to obtain ephemeris data and two sets of carrier phase observations corresponding to the rotating dual-antenna receiver;

[0142] The difference between the two sets of carrier phase observations is calculated to obtain the single-difference carrier phase measurement. Combined with the azimuth angle sampling value, a cosine mathematical model is constructed to show the variation of the single-difference carrier phase measurement with the azimuth angle sampling value. Based on the cosine mathematical model, integer ambiguity and cycle slip detection are estimated and verified.

[0143] Based on the integer ambiguity, the elevation and azimuth angles of a single satellite signal are inferred through spatial geometric relationships to obtain the signal angle of arrival estimation result;

[0144] Based on the position information of the rotating dual-antenna receiver and the ephemeris data, the theoretical angle of arrival of the satellite signal is obtained, and consistency detection is performed on the estimated angle of arrival of the signal and the theoretical angle of arrival of the satellite signal.

[0145] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0146] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0147] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for estimating the angle of arrival and detecting the consistency of GNSS signals, characterized in that, The method includes: The satellite navigation signal is acquired by a rotating dual-antenna receiver that synchronously collects two sets of identical navigation signals emitted by the same satellite, as well as a rotating azimuth angle sample value that is synchronized with the acquisition timing of the two sets of identical navigation signals. The two sets of co-source navigation signals are processed to obtain ephemeris data and two sets of carrier phase observations corresponding to the rotating dual-antenna receiver; The difference between the two sets of carrier phase observations is calculated to obtain a single-difference carrier phase measurement. Combined with the azimuth angle sampling value, a cosine-based mathematical model is constructed to show the variation of the single-difference carrier phase measurement with the azimuth angle sampling value. Integer ambiguity is estimated based on the cosine-based mathematical model. Integer ambiguity is verified based on the residual of the cosine-based mathematical model. Cycle slip is detected based on the maximum amplitude of the residual of the cosine-based mathematical model. The cosine-based mathematical model is expressed as: In the above formulae, denotes a sampling index of the rotation azimuth angle, denotes a navigation signal carrier wavelength, denotes a baseline time-varying azimuth angle, denotes a rotation radius, , denotes an introduced transformation parameter, denotes an integer ambiguity, denotes a single-difference carrier phase single-difference observation noise; Based on the integer ambiguity, the elevation and azimuth angles of a single satellite signal are inferred through spatial geometric relationships to obtain the signal angle of arrival estimation result; Based on the position information of the rotating dual-antenna receiver and the ephemeris data, the theoretical angle of arrival of the satellite signal is obtained, and consistency detection is performed on the estimated angle of arrival of the signal and the theoretical angle of arrival of the satellite signal.

2. The GNSS signal angle of arrival estimation and consistency detection method according to claim 1, characterized in that, The estimation and verification of integer ambiguity and detection of cycle slip based on the cosine mathematical model include: The cosine mathematical model is linearized by introducing transformation parameters. A system of linear equations is constructed and solved using multi-epoch rotating azimuth angle sampling values ​​and single-difference carrier phase measurement values ​​to obtain the floating-point solution of integer ambiguity. Calculate the maximum amplitude of the single-difference carrier phase residual, compare the maximum amplitude with a preset threshold, and determine that a cycle slip exists when the maximum amplitude exceeds the preset threshold; Two sets of single-difference carrier phase measurements with an azimuth angle difference of 180° were selected. The two sets of measurements were added together and divided by 2. The result was rounded to the nearest integer to complete the fixation of integer ambiguity.

3. The GNSS signal angle of arrival estimation and consistency detection method according to claim 1 or 2, characterized in that, The consistency check between the estimated angle of arrival (Angle of Arrival) and the theoretical angle of arrival of the satellite signal includes: A Mahalanobis distance statistic is constructed. After converting the estimated angle of arrival of the signal and the theoretical angle of arrival into parameters in a unified coordinate system, the deviation value is calculated by substituting them into the Mahalanobis distance statistic. When the deviation value exceeds the preset detection threshold, the currently acquired satellite navigation signal is determined to be a suspicious deception signal. The detection threshold is determined by the false alarm probability and satisfies the right-tail probability distribution characteristics.

4. A GNSS signal angle of arrival estimation and consistency detection apparatus, characterized by, The device includes: a rotating dual-antenna assembly, a rotating drive module with an optoelectronic code disk, a dual-radio frequency channel GNSS receiving module, a rotating joint, and a signal processing unit; The rotating dual-antenna assembly consists of two GNSS antennas connected by a rigid structure to form a fixed-length baseline. It is horizontally arranged and symmetrical about the rotation center axis, and is used to synchronously acquire navigation signals from the same source emitted by the same satellite. The rotation drive module containing the photoelectric encoder disk is mechanically coupled to the rotating dual antenna assembly, which is used to drive the rotating dual antenna assembly to rotate at a constant speed and to collect the rotation azimuth angle sampling value in real time. The dual-RF channel GNSS receiver module has an internal common clock design. The two RF input terminals are connected one-to-one with the two GNSS antennas of the rotating dual antenna assembly through the rotating joint. It is used to receive and synchronously process the same source navigation signal, and output ephemeris data, two sets of carrier phase observation values ​​and second pulse synchronization signal. The signal processing unit is configured to execute the GNSS signal angle of arrival estimation and consistency detection method according to any one of claims 1-3 based on the rotation azimuth angle sampling value, ephemeris data and two sets of carrier phase observation values, to obtain a detection result including the angle of arrival estimation result and the suspicious signal marker, and to send the detection result to the user terminal through the rotation joint.

5. The GNSS signal angle of arrival estimation and consistency detection apparatus according to claim 4, characterized in that, The photoelectric encoder receives the second pulse synchronization signal output by the dual-radio frequency channel GNSS receiving module, thereby synchronizing the acquisition timing of the rotation azimuth angle sampling value and the carrier phase observation value.

6. The GNSS signal angle of arrival estimation and consistency detection apparatus according to claim 4, characterized in that, The rotating dual-antenna assembly has a rotation radius of 0.32 meters and a rotation angular velocity of 72° / s. The carrier phase observation update rate of the dual-RF channel GNSS receiver module is 5Hz, and the standard deviation of the carrier phase measurement noise is better than 1 / 40 cycle.

7. The GNSS signal angle of arrival estimation and consistency detection apparatus according to claim 4, characterized in that, The rotating dual-antenna assembly receives the GPS L1 C / A navigation signal.

8. The GNSS signal angle of arrival estimation and consistency detection apparatus of claim 4, wherein, The rotary joint uses a rotary slip ring.

Images