Wireless node authentication method, apparatus, device, storage medium, and program product

Abstract

The application provides a wireless node authentication method, device, equipment, storage medium and program product, relates to the technical field of wireless communication security, and the method is characterized in that residual Doppler shift information in different spatial directions is acquired and a Doppler zero value curve is reconstructed by receiving a DNS discovery signal sent by a transmitting node, then physical layer fingerprint features are extracted and compared with reference fingerprint information to complete authentication, so that the integration of neighbor discovery and identity authentication is realized at the physical layer, traditional multi-round authentication handshake is not needed, and the authentication delay in a high-speed dynamic scene is reduced; meanwhile, the DNS curve is a high-dimensional physical layer fingerprint containing node spatial position, motion state and propagation path information and the like, and compared with single RSS, AoA, CFO or Doppler value, the DNS curve has stronger unforgeability, effectively improves the anti-fraud capability, and solves the defects that the authentication is unreliable and time-consuming in a high-speed mobile scene in the prior art.

Description

Technical Field

[0001] This application relates to the field of wireless communication security technology, and in particular to a wireless node authentication method, apparatus, device, storage medium, and program product. Background Technology

[0002] Mobile Ad Hoc Networks (MANETs) are temporary networks composed of multiple mobile nodes that do not rely on fixed infrastructure. Drone swarm networks are a typical application, where multiple drone nodes collaborate to perform tasks such as reconnaissance, communication relay, and formation flying. These networks are characterized by high node speeds, rapid topology changes, short link establishment times, and potential exposure to complex multipath, interference, and spoofing environments. Communication nodes typically need to perform two fundamental tasks: neighbor discovery and authentication. However, traditional solutions handle these tasks separately, first broadcasting to discover neighbors and then performing authentication via cryptographic protocols. This can lead to significant latency and signaling overhead in high-speed mobile scenarios.

[0003] Current wireless network authentication primarily relies on the following methods: ID-based or password-based authentication: Nodes complete authentication by sending their own ID or executing cryptographic protocols such as challenge-response or digital signatures. These methods rely on digital layer information or key infrastructure; IDs are easily copied and forged; cryptographic authentication requires multiple handshakes, resulting in significant latency in dynamic scenarios with short-lived links; and the link may have changed by the time authentication is complete.

[0004] Authentication based on physical layer features: This method utilizes physical layer features such as RSS (Received Signal Strength), CSI (Channel State Information), AoA (Angle of Arrival), and CFO (Carrier Frequency Offset) for identification. While this approach does not rely on upper-layer protocols, RSS is easily spoofed by adjusting power, CSI is unstable due to rapid changes during high-speed motion, AoA only provides directional information and is insufficient for unique authentication, and CFO is easily coupled with Doppler and temperature drift. Furthermore, the amount of information contained in a single feature is limited and easily counterfeited.

[0005] Doppler shift-based identification involves measuring the Doppler shift at the receiver and comparing it to the expected value. However, traditional methods use only a single Doppler value, resulting in low feature dimensionality and susceptibility to noise and frequency offset. Attackers can adjust the transmission frequency to forge Doppler values.

[0006] Multi-receiving node collaborative localization: Multiple receiving nodes jointly determine the sender's location using AoA / ToA (Time of Arrival) / TDoA (Time Difference of Arrival). This type of scheme requires high-precision time synchronization, is sensitive to multipath propagation, and its authentication capability decreases if an attacker approaches the location of a legitimate node, usually requiring an additional discovery process.

[0007] In summary, existing technologies generally suffer from drawbacks such as large latency due to the separation of discovery and authentication, simplistic authentication features that are easily counterfeited, poor adaptability to dynamic scenarios, lack of multi-dimensional joint decision-making capabilities, and insufficient reliability of single nodes. Summary of the Invention

[0008] This application provides a wireless node authentication method, apparatus, device, storage medium, and program product to address the shortcomings of unreliable and high-latency wireless node authentication in high-speed dynamic scenarios in the prior art, and to achieve integrated physical layer security authentication based on Doppler zero-value manipulation curves for discovery and authentication.

[0009] This application provides a wireless node authentication method for a receiving node, comprising the following steps: Receive the Doppler zero value manipulation DNS discovery signal sent by the transmitting node; Obtain the residual Doppler frequency shift information of the DNS discovery signal in different spatial directions; Based on the correspondence between the spatial direction and the residual Doppler frequency shift information, the Doppler zero-value curve is reconstructed; Physical layer fingerprint features are extracted based on the Doppler zero-value curve, and the physical layer fingerprint features are compared with the reference fingerprint information. An identity authentication decision is determined based on the comparison result.

[0010] According to a wireless node authentication method provided in this application, obtaining the residual Doppler frequency shift information of the DNS discovery signal in different spatial directions includes: Beamforming is performed on the DNS discovery signal using an array antenna to obtain received signal components in multiple beam directions; Carrier synchronization and frequency offset estimation are performed on the received signal components in each beam direction, and the residual Doppler frequency shift value corresponding to each beam direction is extracted.

[0011] According to a wireless node authentication method provided in this application, the step of reconstructing the Doppler null curve based on the correspondence between the spatial direction and the residual Doppler frequency shift information includes: A data point sequence is constructed with each spatial direction as the horizontal axis and the corresponding residual Doppler frequency shift value as the vertical axis. The data point sequence is interpolated or fitted to form a curve showing the continuous residual Doppler frequency shift as a function of spatial direction, which serves as the Doppler zero-value curve.

[0012] According to a wireless node authentication method provided in this application, the physical layer fingerprint feature includes at least one of the following: The direction of the zero point of the Doppler zero-value curve; The slope of the Doppler zero-value curve at the zero point; The curvature characteristics of the Doppler zero-value curve; The correlation coefficient between the Doppler zero-value curve and the baseline curve; The zero-value depth or zero-value width of the Doppler zero-value curve.

[0013] According to a wireless node authentication method provided in this application, the step of comparing the physical layer fingerprint feature with reference fingerprint information and determining an identity authentication decision based on the comparison result includes: Calculate the similarity between the physical layer fingerprint features and the reference fingerprint information; the similarity includes at least one of curve similarity, orientation similarity, and distance similarity; If the similarity is greater than or equal to a preset threshold, the transmitting node is determined to be a legitimate node. If the similarity is less than a preset threshold, the transmitting node is determined to be an illegal node.

[0014] According to a wireless node authentication method provided in this application, calculating the similarity between the physical layer fingerprint features and the reference fingerprint information includes: The direction of arrival of the transmitting node is determined based on the zero point direction of the Doppler zero-value curve; Based on the propagation delay of the DNS discovery signal, the propagation distance between the transmitting node and the receiving node is determined; The curve correlation between the Doppler zero-value curve and the baseline curve in the baseline fingerprint information is calculated as the curve similarity. Calculate the orientation error between the orientation of arrival and the reference orientation in the reference fingerprint information, and use it as the orientation similarity. The distance error between the propagation distance and the reference distance in the reference fingerprint information is calculated as the distance similarity.

[0015] According to the wireless node authentication method provided in this application, the method further includes: The physical layer fingerprint features and / or the identity authentication decision are reported to the collaborative authentication fusion node. The collaborative authentication fusion node is used to receive the physical layer fingerprint features and / or identity authentication decisions reported by multiple receiving nodes, including this receiving node, and to perform consistency verification on the information reported by the multiple receiving nodes. Receive the collaborative authentication decision returned by the collaborative authentication fusion node.

[0016] According to the wireless node authentication method provided in this application, the method further includes: Obtain the signal quality parameters of the DNS discovery signal and / or the curve quality parameters of the Doppler zero-value curve; the signal quality parameters include received power and / or signal-to-noise ratio, and the curve quality parameters include curve distortion degree, zero-point offset and / or correlation coefficient with the reference curve; Based on the signal quality parameters and / or the curve quality parameters, identify whether the DNS discovery signal is an abnormal signal; If an abnormal signal is detected, authentication will be rejected or an alarm will be triggered.

[0017] This application provides a wireless node authentication method applied to a transmitting node, comprising the following steps: Obtain the motion state information of the transmitting node; A DNS discovery signal is generated based on a preset scan angle sequence and the motion state information; the DNS discovery signal is a signal formed by applying Doppler frequency compensation related to the scan direction to the discovery signals in different scan directions. The DNS discovery signal is sent so that the receiving node can reconstruct the Doppler zero-value curve and perform identity authentication based on the DNS discovery signal.

[0018] According to a wireless node authentication method provided in this application, the step of generating a DNS discovery signal based on a preset scan angle sequence and the motion state information includes: Based on the speed magnitude and direction of the transmitting node in the motion state information, and each scanning direction in the preset scanning angle sequence, calculate the Doppler frequency compensation amount corresponding to each scanning direction; Based on the Doppler frequency compensation amount corresponding to each scanning direction, the baseband detection signal is frequency modulated to generate a Doppler pre-compensated transmission signal; The DNS discovery signal is formed by transmitting Doppler-precompensated discovery signals in each scanning direction.

[0019] This application also provides a wireless node authentication device for use in a receiving node, comprising the following modules: The receiving module is used to receive the Doppler zero-value manipulated DNS discovery signal sent by the transmitting node; The residual Doppler frequency shift information acquisition module is used to acquire the residual Doppler frequency shift information of the DNS discovery signal in different spatial directions; The Doppler zero-value curve reconstruction module is used to reconstruct the Doppler zero-value curve based on the correspondence between the spatial direction and the residual Doppler frequency shift information; The authentication module is used to extract physical layer fingerprint features based on the Doppler zero-value curve, compare the physical layer fingerprint features with the reference fingerprint information, and determine the identity authentication decision based on the comparison result.

[0020] This application also provides a wireless node authentication device for use in a transmitting node, comprising the following modules: The motion state information acquisition module is used to acquire the motion state information of the transmitting node; The DNS discovery signal generation module is used to generate a DNS discovery signal based on a preset scan angle sequence and the motion state information; the DNS discovery signal is a signal formed by applying Doppler frequency compensation related to the scan direction to the discovery signals in different scan directions. The sending module is used to send the DNS discovery signal so that the receiving node can reconstruct the Doppler zero curve and perform identity authentication based on the DNS discovery signal.

[0021] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the wireless node authentication methods described above.

[0022] This application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the wireless node authentication method as described above.

[0023] This application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the wireless node authentication methods described above.

[0024] The wireless node authentication method, apparatus, device, storage medium, and program product provided in this application obtain residual Doppler frequency shift information in different spatial directions and reconstruct the Doppler zero-value curve by receiving the DNS discovery signal sent by the transmitting node. Then, it extracts physical layer fingerprint features and compares them with the reference fingerprint information to complete the authentication. This achieves the integration of neighbor discovery and identity authentication at the physical layer, eliminating the need for traditional multi-round authentication handshakes and reducing authentication latency in high-speed dynamic scenarios. At the same time, the DNS curve, as a high-dimensional physical layer fingerprint containing information such as node spatial location, motion state, and propagation path, has stronger unforgeability than a single RSS, AoA, CFO, or Doppler value, effectively improving anti-spoofing ability and solving the defects of unreliable authentication and high latency in high-speed mobile scenarios of existing technologies. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is one of the flowcharts illustrating the wireless node authentication method provided in this application.

[0027] Figure 2 This is a schematic diagram of attack and anomaly scenario handling provided in this application.

[0028] Figure 3 This is a schematic diagram of multi-receiving node collaborative authentication provided in this application.

[0029] Figure 4 This is the second flowchart illustrating the wireless node authentication method provided in this application.

[0030] Figure 5 This is a diagram illustrating the DNS scanning principle provided in this application.

[0031] Figure 6 This is an architecture diagram of the mobile wireless node rapid discovery and collaborative authentication system based on the DNS Doppler zero-value curve provided in this application.

[0032] Figure 7 This is one of the structural schematic diagrams of the wireless node authentication device provided in this application.

[0033] Figure 8 This is the second structural schematic diagram of the wireless node authentication device provided in this application.

[0034] Figure 9 This is a schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0036] The following is combined Figures 1-9 This application describes the wireless node authentication method, apparatus, device, storage medium, and program product.

[0037] Figure 1 This is one of the flowcharts illustrating the wireless node authentication method provided in this application, such as... Figure 1 As shown, the method includes the following: Step 101: Receive the Doppler zero value manipulation DNS discovery signal sent by the transmitting node.

[0038] It should be noted that the execution subject of this application embodiment is a receiving node, wherein the receiving node refers to a communication device in a mobile wireless ad hoc network that has the ability to receive wireless signals and process physical layer authentication, including drones, ground control stations, vehicle terminals, roadside units, base stations or other fixed or mobile communication devices.

[0039] A transmitting node refers to a communication device in a mobile wireless ad hoc network that has the ability to transmit wireless signals and move autonomously. It may include drones, vehicle-mounted terminals, handheld terminals or other mobile communication devices.

[0040] In one embodiment, the receiving node can be a mobile node isomorphic to the transmitting node, such as other drones in a swarm; it can also be a heterogeneous ground infrastructure node, such as a ground control station or communication base station; or it can be a specially deployed cooperative authentication node. The receiving node receives Doppler NullSteering (DNS) discovery signals through its antenna array and performs physical layer authentication processing to complete the identity authentication decision of the transmitting node.

[0041] DNS discovery signals refer to the wireless signals that a transmitting node transmits sequentially in each scanning direction after applying Doppler frequency compensation related to the scanning direction to the discovery signals in different scanning directions, based on a preset scanning angle sequence and its own motion state information.

[0042] The receiving node captures the radio discovery signal emitted by the transmitting node in the radio space through its antenna array, which has undergone directionally correlated Doppler precompensation.

[0043] Step 102: Obtain the residual Doppler frequency shift information of the DNS discovery signal in different spatial directions.

[0044] Residual Doppler frequency shift information refers to the Doppler frequency shift value that the receiving node actually measures in a certain spatial direction, after Doppler pre-compensation by the transmitting node. This value reflects the deviation between the pre-compensation amount of the transmitting node in that direction and the actual Doppler frequency shift.

[0045] The receiving node uses array antennas and beamforming technology to perform spatial separation on the received DNS discovery signal, obtain signal components in different spatial directions, and measure the residual Doppler frequency shift value corresponding to each spatial direction through carrier synchronization and frequency offset estimation, thereby obtaining a data set of residual Doppler frequency shift as a function of spatial direction.

[0046] Step 103: Reconstruct the Doppler zero-value curve based on the correspondence between the spatial direction and the residual Doppler frequency shift information.

[0047] The Doppler zero-value curve is a curve constructed with the spatial direction as the horizontal axis and the residual Doppler frequency shift value measured in each spatial direction as the vertical axis. This curve reflects the distribution law of the continuous change of residual Doppler frequency shift with spatial direction. Its zero point (i.e., the spatial direction where the residual Doppler frequency shift is zero or close to zero) corresponds to the direction of arrival of the transmitting node. The overall shape, slope and curvature of the curve reflect the speed, motion state and propagation path information of the transmitting node.

[0048] The receiving node converts the data point sequence consisting of each spatial direction and its corresponding residual Doppler frequency shift value into a continuous function curve through interpolation or fitting, thereby obtaining the distribution law of the continuous change of residual Doppler frequency shift with spatial direction and generating a Doppler zero-value curve.

[0049] Step 104: Extract physical layer fingerprint features based on the Doppler zero-value curve, compare the physical layer fingerprint features with the reference fingerprint information, and determine the identity authentication decision based on the comparison result.

[0050] Physical layer fingerprint features refer to multi-dimensional feature information extracted from the Doppler zero-value curve, used to uniquely identify and recognize the identity of the transmitting node. The Doppler zero-value curve is jointly determined by information such as the spatial location, velocity magnitude, velocity direction of the transmitting node, the location of the receiving node, scanning protocol, and propagation path, and has strong physical unforgeability. The physical layer fingerprint features extracted from this curve inherit this unforgeability accordingly, and therefore can serve as a reliable basis for identity authentication. Attackers find it difficult to match all fingerprint dimensions simultaneously by forging digital IDs or adjusting a single physical quantity.

[0051] In one embodiment, the physical layer fingerprint features include at least one of the following: the zero-point direction of the Doppler zero-value curve, the slope of the Doppler zero-value curve at the zero point, the curvature feature of the Doppler zero-value curve, the correlation coefficient between the Doppler zero-value curve and the reference curve, and the zero-value depth or zero-value width of the Doppler zero-value curve.

[0052] The zero-point direction refers to the spatial direction corresponding to the intersection of the Doppler zero-value curve and the zero-value axis (i.e., the axis where the residual Doppler frequency shift is zero). Since the transmitting node has undergone Doppler pre-compensation for each scanning direction, the residual Doppler frequency shift approaches zero in a specific direction; this direction is the zero-value point direction of the curve. The zero-point direction corresponds to the true azimuth of the transmitting node. When the transmitting node moves at high speed along a certain direction, the Doppler frequency shift in that direction is maximum. After pre-compensation, the residual Doppler frequency shift approaches zero; therefore, the zero-point direction directly indicates the spatial azimuth of the transmitting node.

[0053] The zero-slope refers to the derivative of the Doppler zero-value curve at the zero point, reflecting the rate of change of the curve near the zero point. The absolute value of the zero-slope is positively correlated with the magnitude of the transmitting node's velocity; the greater the velocity, the greater the gradient of the Doppler frequency shift with direction, and the steeper the change of the curve at the zero point. Therefore, the zero-slope can serve as an effective fingerprint feature reflecting the magnitude of the transmitting node's velocity. When the velocity is low, the absolute value of the zero-slope is small, and the curve changes gently near the zero point; when the velocity is high, the absolute value of the zero-slope is large, and the curve changes steeply near the zero point.

[0054] Curvature features refer to the curvature values ​​of the Doppler zero-value curve at the zero point direction or other feature points, reflecting the degree of curvature of the curve at that point. Curvature features are related to the motion state of the transmitting node, changes in velocity direction, and scanning protocol, and can be used as auxiliary fingerprint features, combined with other features to improve the accuracy of authentication.

[0055] The correlation coefficient is a measure of similarity between the Doppler zero-value curve to be authenticated and the baseline curve of a legitimate node pre-stored in the benchmark fingerprint information. Specifically, the overall similarity between the two curves can be calculated using methods such as Pearson correlation coefficient, normalized cross-correlation peak value, or Euclidean distance. The correlation coefficient reflects the consistency of the overall shape of the curves. When the shape similarity between the curve to be authenticated and the baseline curve is high, the correlation coefficient is close to 1; when the shape difference is large, the correlation coefficient is far from 1. This feature is sensitive to changes in the overall shape of the curve and can effectively detect deceptive behavior by attackers attempting to imitate the shape of legitimate node curves.

[0056] Zero-value depth refers to the minimum absolute value of the residual Doppler frequency shift at the zero point of the Doppler zero-value curve. Ideally, it is zero, but in reality, it is a value close to zero. Zero-value depth reflects the accuracy of Doppler compensation and signal quality; the more accurate the compensation and the higher the signal quality, the closer the zero-value depth is to zero. Zero-value width refers to the length of the spatial directional interval where the absolute value of the residual Doppler frequency shift is below a certain preset threshold. It reflects the sharpness of the zero-value direction; the narrower the zero-value width, the higher the directional resolution and the higher the authentication accuracy.

[0057] Of the five physical layer fingerprint features mentioned above, zero-point direction, zero-point slope, and zero-value depth / width are local features directly extracted from the curve; curvature features are local features reflecting the geometric shape of the curve; and correlation coefficients are global features reflecting the similarity of the entire curve. In one embodiment, one of the above features can be used alone to achieve fast authentication; in another embodiment, multiple features can be combined to achieve a balance between computational complexity and authentication accuracy. By combining one or more of the above features, multi-dimensional and highly reliable authentication of the transmitting node's identity can be achieved.

[0058] The baseline fingerprint information refers to the physical layer fingerprint feature data of legitimate nodes pre-stored in the fingerprint database module, which is used as a comparison benchmark for identity authentication. Since the Doppler zero-value curve and its fingerprint features corresponding to the DNS discovery signal sent by a legitimate node under normal working conditions are unique and stable, the receiving node can pre-store them as baseline fingerprint information for comparison with the physical layer fingerprint features extracted by the node to be authenticated during authentication.

[0059] In one embodiment, the fingerprint database module is located locally on a single receiving node, which directly reads the reference fingerprint information from its local storage during authentication. In another embodiment, the fingerprint database module is located at a ground control station or the master node of the swarm, and multiple receiving nodes obtain the reference fingerprint information from the ground control station or the master node via a network. In yet another embodiment, the fingerprint database module is distributed across multiple receiving nodes, and the nodes achieve sharing and synchronization of the reference fingerprint information through collaborative interaction.

[0060] In one embodiment, the baseline fingerprint information can be obtained in advance as follows: a legitimate node sends a DNS discovery signal according to a preset scan angle sequence; a receiving node receives the signal and reconstructs the Doppler zero-value curve; extracts physical layer fingerprint features from the curve; and associates and stores these features with the identity identifier of the legitimate node to form the baseline fingerprint information of the legitimate node. This process can be performed when the legitimate node joins the network, or it can be updated periodically during network operation.

[0061] In one embodiment, the reference fingerprint information stored in the fingerprint database module may include: (1) Valid Node ID: The unique identifier of a valid node, used to index and retrieve the baseline fingerprint information of the corresponding node. This ID can be a network layer address, device serial number or other unique identifier.

[0062] (2) Reference DNS curve: After the legitimate node sends the DNS discovery signal during the pre-collection process, the receiving node reconstructs the Doppler zero curve data. This data can be a complete curve function, a discrete sampling point sequence, or curve fitting parameters, which are used to compare the overall correlation with the curve of the node to be authenticated.

[0063] (3) Reference zero point direction: The zero point direction of the Doppler zero value curve of the legitimate node corresponds to the true orientation of the legitimate node relative to the receiving node.

[0064] (4) Reference propagation distance: The propagation distance between the legitimate node and the receiving node can be determined based on the propagation delay of the DNS discovery signal. This distance information can be used for spatial consistency verification of multiple receiving nodes in collaborative authentication.

[0065] (5) Reference received power: The average received power or power distribution of the DNS discovery signal of the legitimate node at the receiving node. It can be used to assist in the decision. For example, when the received power of the signal to be authenticated deviates too much from the reference received power, it may be a spoofing attack or interference signal.

[0066] (6) Reference motion state: The motion state information of a legitimate node, including velocity magnitude, velocity direction, acceleration, and heading, can be used to verify whether the motion state of the node to be authenticated is consistent with the reference. If the velocity vector of the node to be authenticated deviates significantly from the reference motion state, spoofing may be present.

[0067] (7) Reference frequency offset statistical characteristics: The carrier frequency offset statistical characteristics of legal nodes, including average value, variance and drift pattern, can be used as auxiliary features of hardware fingerprint.

[0068] (8) Joint fingerprint under multiple receiving nodes: When multiple receiving nodes simultaneously receive the DNS discovery signal of the same legitimate node, the physical layer fingerprint features extracted by each receiving node and their spatial consistency relationship are used for multi-receiving node collaborative authentication to improve the reliability of the decision.

[0069] (9) Fingerprint update timestamp: The time of collection or most recent update of the baseline fingerprint information, used to determine the timeliness of the fingerprint information. When the preset validity period is exceeded, the fingerprint database module can trigger the fingerprint update process to re-collect the baseline fingerprint information of the legitimate nodes.

[0070] The fingerprint database module stores a rich variety of baseline fingerprint information, supporting multiple authentication modes such as single-node local authentication and multi-node collaborative authentication, which effectively improves the accuracy of authentication and the ability to resist deception.

[0071] The receiving node extracts multi-dimensional physical layer fingerprint features that can uniquely identify the identity of the transmitting node from the reconstructed Doppler zero-value curve, and performs similarity calculation and threshold comparison with the extracted physical layer fingerprint features and pre-stored legal node benchmark fingerprint information. The legality of the transmitting node's identity is determined based on the comparison results. For example, if the similarity is greater than or equal to a preset threshold, it is determined to be a legal node; otherwise, it is determined to be an illegal node.

[0072] The wireless node authentication method provided in this application receives the DNS discovery signal sent by the transmitting node, obtains residual Doppler frequency shift information in different spatial directions, reconstructs the Doppler zero-value curve, and then extracts physical layer fingerprint features and compares them with the reference fingerprint information to complete authentication. This achieves the integration of neighbor discovery and identity authentication at the physical layer, eliminating the need for traditional multi-round authentication handshakes and reducing authentication latency in high-speed dynamic scenarios. At the same time, the DNS curve, as a high-dimensional physical layer fingerprint containing information such as node spatial location, motion state, and propagation path, has stronger unforgeability than a single RSS, AoA, CFO, or Doppler value, effectively improving anti-spoofing capability and solving the defects of unreliable authentication and high latency in high-speed mobile scenarios in existing technologies.

[0073] Based on the above embodiments, obtaining the residual Doppler frequency shift information of the DNS discovery signal in different spatial directions includes: Beamforming is performed on the DNS discovery signal using an array antenna to obtain received signal components in multiple beam directions; Carrier synchronization and frequency offset estimation are performed on the received signal components in each beam direction, and the residual Doppler frequency shift value corresponding to each beam direction is extracted.

[0074] The receiving node performs spatial weighting processing on the received DNS discovery signal through its multi-antenna array, forming multiple receiving beams pointing in different spatial directions, thereby separating the signal components from different directions in space and obtaining the independent received signal components corresponding to each beam direction.

[0075] Specifically, the receiving node's antenna array receiver unit comprises multiple antenna elements arranged in a specific geometry, such as a uniform linear array, a uniform circular array, or other array structures. When the DNS detects a signal arriving at the array from a certain direction, a phase difference caused by the propagation path difference will form on different array elements, and this phase difference corresponds one-to-one with the direction of the signal's arrival. The beamforming unit utilizes this characteristic to perform a weighted summation of the received signals from each array element, forming a receiving beam pointing in a specific spatial direction. In the desired direction, the signals from each array element are in phase and superimposed, maximizing the signal gain; in other directions, the signals partially or completely cancel each other out, and interference is suppressed.

[0076] For each received signal component obtained after beamforming, the receiving node performs carrier synchronization processing and frequency offset estimation processing respectively, extracts the residual Doppler frequency shift value corresponding to that direction from the signal component in each beam direction, and thus obtains the correspondence between each spatial direction and the residual Doppler frequency shift value.

[0077] Specifically, after beamforming, the receiving node obtains received signal components in multiple beam directions, each of which contains Doppler pre-compensation information from the transmitting node in that direction. To extract the residual Doppler frequency shift values ​​for each direction, the carrier synchronization and frequency offset estimation unit performs the following processing on each received signal component in each beam direction: The carrier synchronization and frequency offset estimation unit uses the DNS to discover the pilot sequence or synchronization sequence carried in the signal, performs correlation operations with the local reference sequence, and estimates the total carrier frequency offset in the beam direction. Since the transmitting node has applied Doppler pre-compensation to each scanning direction, this frequency offset estimate actually represents the residual Doppler frequency shift in that direction. Ideally, if the pre-compensation of the transmitting node in a certain direction exactly cancels out the actual Doppler frequency shift in that direction, the extracted residual Doppler frequency shift value should be close to zero; if the pre-compensation is insufficient or excessive, the residual Doppler frequency shift value is non-zero, and its magnitude and sign reflect the deviation between the pre-compensation and the actual Doppler.

[0078] The receiving node repeats the above process for each beam direction in the scanning angle sequence to obtain the residual Doppler frequency shift value corresponding to all beam directions, forming a data point sequence of "spatial direction - residual Doppler frequency shift value".

[0079] The embodiments of this application separate signal components in different directions in the spatial domain by array antenna beamforming, which can effectively suppress multipath interference and noise, and improve the signal-to-noise ratio and accuracy of residual Doppler frequency shift measurement in each direction; performing independent carrier synchronization and frequency offset estimation for each beam direction can avoid mutual coupling between signals in different directions, and further improve the accuracy of residual Doppler frequency shift extraction.

[0080] Based on the above embodiments, the step of reconstructing the Doppler null curve according to the correspondence between the spatial direction and the residual Doppler frequency shift information includes: A data point sequence is constructed with each spatial direction as the horizontal axis and the corresponding residual Doppler frequency shift value as the vertical axis. The data point sequence is interpolated or fitted to form a curve showing the continuous residual Doppler frequency shift as a function of spatial direction, which serves as the Doppler zero-value curve.

[0081] The spatial direction refers to the spatial angular direction in which the receiving node points when performing beamforming through the array antenna, which corresponds to the preset scanning angle of the transmitting node. The transmitting node transmits the DNS discovery signal with Doppler pre-compensation in each scanning angular direction, and the receiving node receives and measures the residual Doppler frequency shift in the corresponding spatial direction.

[0082] The receiving node organizes each pair of measured "spatial direction-residual Doppler frequency shift values" data into a series of discrete data points, with the spatial direction as the horizontal axis and the residual Doppler frequency shift value as the vertical axis. Specifically, the receiving node obtains multiple spatial directions through beamforming and obtains the corresponding residual Doppler frequency shift values ​​for each spatial direction through carrier synchronization and frequency offset estimation. Each pair of "spatial direction-residual Doppler frequency shift values" data represents a specific residual Doppler frequency shift value measured in a certain spatial direction.

[0083] The receiving node converts the discrete data point sequence into a continuous function curve through interpolation or fitting algorithms. This curve describes the complete distribution law of the continuous change of the residual Doppler frequency shift with the spatial direction and is used as the Doppler zero-value curve.

[0084] Specifically, the sequence of "spatial direction-residual Doppler frequency shift values" data points obtained by the receiving node during beamforming and frequency offset estimation is discrete, with measurements only occurring in a finite number of spatial directions corresponding to a preset scan angle sequence. However, the actual azimuth of the transmitting node may lie in any direction, not necessarily exactly at the preset scan angle, and complete physical layer fingerprint extraction requires obtaining feature information of the curve in any direction. Therefore, it is necessary to convert the discrete data point sequence into a continuous curve.

[0085] The DNS curve reconstruction unit of the receiving node performs interpolation or fitting processing on the discrete data point sequence. Interpolation involves estimating intermediate values ​​among the discrete data points according to certain mathematical rules, ensuring the curve passes precisely through all known data points. Fitting, on the other hand, constructs an approximate curve that approximates all known data points overall, without necessarily passing precisely through each point. Through these processes, the receiving node obtains a continuous curve showing the residual Doppler frequency shift as a function of spatial direction. This curve is defined in any spatial direction and reflects the complete law of continuous change of the residual Doppler frequency shift with direction.

[0086] In one embodiment, the interpolation process can employ linear interpolation or spline interpolation. Spline interpolation constructs a low-order polynomial between adjacent data points, ensuring the entire curve has continuous first and second derivatives, thus achieving a smooth curve shape. In another embodiment, the fitting process can employ polynomial fitting or least squares fitting.

[0087] The embodiments of this application convert discrete measurement data into continuous Doppler zero-value curves through interpolation or fitting, which can improve the extraction accuracy of fingerprint features such as zero-point direction and effectively smooth measurement noise.

[0088] Based on the above embodiments, the step of comparing the physical layer fingerprint features with the reference fingerprint information and determining the identity authentication decision based on the comparison result includes: Calculate the similarity between the physical layer fingerprint features and the reference fingerprint information; the similarity includes at least one of curve similarity, orientation similarity, and distance similarity; If the similarity is greater than or equal to a preset threshold, the transmitting node is determined to be a legitimate node. If the similarity is less than a preset threshold, the transmitting node is determined to be an illegal node.

[0089] Curve similarity refers to the overall shape similarity between the Doppler zero-value curve of the node to be authenticated and the baseline curve in the baseline fingerprint information, and is used to measure the consistency of the two curves in terms of shape.

[0090] Orientation similarity refers to the degree of closeness between the orientation of the node to be authenticated and the reference orientation in the reference fingerprint information, and is used to measure the consistency of the spatial orientation of the transmitting node.

[0091] Distance similarity refers to the degree of closeness between the propagation distance of the node to be authenticated and the baseline distance in the baseline fingerprint information. It is used to measure the consistency of the spatial distance between the transmitting node and the receiving node.

[0092] After the local authentication decision unit of the receiving node obtains the physical layer fingerprint features of the node to be authenticated, it reads the baseline fingerprint information of the legitimate node from the fingerprint database module, and then calculates the similarity metric between the two. It should be understood that the similarity reflects the degree of proximity between the node to be authenticated and the legitimate node in terms of physical layer features. A higher similarity indicates that the spatial location, motion state, and signal propagation characteristics of the node to be authenticated and the legitimate node are more consistent; a lower similarity indicates that there are differences between the two, potentially indicating a spoofing attack. In one embodiment, the similarity includes at least one of curve similarity, orientation similarity, and distance similarity.

[0093] After obtaining the similarity score, the local authentication decision unit compares the similarity score with a preset threshold. It should be understood that the preset threshold is the boundary for distinguishing between legitimate and illegitimate nodes. When the similarity score is greater than or equal to the preset threshold, it indicates that the physical layer fingerprint features of the node to be authenticated match the baseline fingerprint information of the legitimate node sufficiently well, and the transmitting node can be considered a legitimate node, thus authentication passes. When the similarity score is less than the preset threshold, it indicates that the difference between the two exceeds the normal range, potentially indicating a spoofing attack, ID forgery, or other security threats. The transmitting node is then determined to be an illegitimate node, authentication fails, and the establishment of a communication link is refused or a security alarm is triggered.

[0094] Through the above comparison and judgment process, the receiving node transforms the physical layer fingerprint features into a clear identity authentication result, completing the entire authentication process from signal reception to identity judgment. The value of the preset threshold can be flexibly adjusted according to the security level requirements and false alarm tolerance of the actual application scenario. For example, a higher threshold value can be used in scenarios with high security requirements to reduce the probability of false alarms; a lower threshold value can be used in scenarios with poor link conditions to reduce the probability of missed alarms.

[0095] This application embodiment calculates the similarity between physical layer fingerprint features and baseline fingerprint information, and comprehensively measures node consistency from multiple dimensions such as curve shape, spatial orientation and propagation distance, effectively improving authentication reliability and anti-spoofing capability.

[0096] Based on the above embodiments, calculating the similarity between the physical layer fingerprint features and the reference fingerprint information includes: The direction of arrival of the transmitting node is determined based on the zero point direction of the Doppler zero-value curve; Based on the propagation delay of the DNS discovery signal, the propagation distance between the transmitting node and the receiving node is determined; The curve correlation between the Doppler zero-value curve and the baseline curve in the baseline fingerprint information is calculated as the curve similarity. Calculate the orientation error between the orientation of arrival and the reference orientation in the reference fingerprint information, and use it as the orientation similarity. The distance error between the propagation distance and the reference distance in the reference fingerprint information is calculated as the distance similarity.

[0097] The receiving node identifies the spatial direction corresponding to the residual Doppler frequency shift in the Doppler zero-value curve being zero or close to zero as the true orientation of the transmitting node relative to the receiving node, thereby obtaining the spatial orientation information of the transmitting node.

[0098] Specifically, when transmitting the DNS discovery signal, the transmitting node applies Doppler frequency compensation to each scanning direction according to its own velocity vector. This ensures that, in a specific direction, the pre-compensation of the transmitting node completely cancels out the actual Doppler frequency shift in that direction. This specific direction is the true azimuth of the transmitting node relative to the receiving node. This is because only when the beam pointing precisely aligns with the transmitting node does the radial velocity component and the projection of the transmitting node's actual velocity vector in that direction coincide, allowing the pre-compensation to accurately cancel out the actual Doppler. In the Doppler zero-value curve, this specific direction is represented by the intersection of the curve and the zero-value axis, i.e., the direction of the zero-value point of the curve. Therefore, the receiving node identifies the spatial direction corresponding to the zero-value point as the true azimuth of the transmitting node by detecting the zero-value point of the Doppler zero-value curve. After extracting the zero-value direction from the Doppler zero-value curve, the azimuth / range estimation unit maps it to an azimuth angle in space, such as the angle relative to the receiving node's true north direction or the angle relative to the array normal direction, thereby obtaining the azimuth information of the transmitting node relative to the receiving node. Through the above determination process, the receiving node does not need to rely on the location information actively reported by the transmitting node, nor does it need additional direction-finding signaling interaction. It can complete the estimation of the direction of arrival by using the physical layer characteristics of the signal itself discovered by DNS.

[0099] The receiving node discovers the propagation delay of the signal from the transmitting node to the receiving node by measuring the DNS, and calculates the straight-line distance between the transmitting node and the receiving node by multiplying the signal propagation speed in space by the delay.

[0100] Specifically, the DNS discovery signal sent by the transmitting node carries a pilot sequence or synchronization sequence, which the receiving node uses for accurate time synchronization and delay estimation. The azimuth / range estimation unit estimates the Time of Arrival (ToA) of the received DNS discovery signal, and performs correlation operations between the synchronization sequence in the signal and the local reference sequence to determine the propagation delay from the transmitting node to the receiving node. This propagation delay reflects the time it takes for the wireless signal to travel through space from the transmitting node to the receiving node. After obtaining the propagation delay, the azimuth / range estimation unit calculates the propagation distance between the transmitting and receiving nodes based on the propagation speed of the wireless signal in free space: Propagation distance = Speed ​​of light × Propagation delay. Since the speed of light is a known constant in free space, the propagation distance is directly proportional to the propagation delay. A larger propagation delay indicates that the transmitting node is farther from the receiving node; a smaller propagation delay indicates that the transmitting node is closer to the receiving node.

[0101] The receiving node measures the overall morphological similarity between the Doppler zero-value curve of the node to be authenticated and the baseline curve of legitimate nodes stored in the fingerprint database. By calculating the correlation coefficient between the two curves, such as the Pearson correlation coefficient or the peak value of the normalized cross-correlation function, the obtained correlation quantification value is used as the curve similarity, measuring the degree of matching between the two curves in shape. It should be understood that curve correlation reflects the degree of consistency between the two curves in overall morphological features such as zero-point direction, curve slope, curvature change, and zero-value width. When the node to be authenticated is a legitimate node, its motion state and spatial position are basically consistent with the baseline acquisition, and the reconstructed Doppler zero-value curve should have a high correlation with the baseline curve. When the node to be authenticated is an illegitimate node (such as a deceiving attacker), its spatial position, motion state, or propagation path differs from that of a legitimate node, and the reconstructed Doppler zero-value curve will deviate from the baseline curve in terms of zero-point direction, slope, or overall shape, resulting in a lower curve correlation.

[0102] The receiving node calculates the difference between the determined transmitting node's azimuth and the reference azimuth of legitimate nodes stored in the fingerprint database. This azimuth deviation is quantified as azimuth similarity, used to measure the degree of consistency between the transmitting node's actual spatial azimuth and the expected azimuth of legitimate nodes. It should be understood that azimuth error reflects the degree of deviation between the transmitting node's current spatial azimuth and the expected azimuth of legitimate nodes. The smaller the azimuth error, the closer the transmitting node's direction is to the reference direction of legitimate nodes, and the higher the azimuth similarity; the larger the azimuth error, the more likely there is a deviation between the transmitting node's spatial azimuth and that of legitimate nodes, possibly originating from different directions, and the lower the azimuth similarity.

[0103] The receiving node calculates the difference between the determined propagation distance between the transmitting and receiving nodes and the baseline distance of legitimate nodes stored in the fingerprint database. This distance deviation is quantified as a distance similarity, used to measure the consistency between the actual distance of the transmitting node and the expected distance of the legitimate node. It should be understood that the distance error reflects the degree of deviation between the current distance of the transmitting node and the expected distance of the legitimate node. The smaller the distance error, the closer the distance between the transmitting and receiving nodes is to the baseline distance of the legitimate node, and the higher the distance similarity; the larger the distance error, the more it indicates a deviation between the spatial distance of the transmitting node and the legitimate node, and the lower the distance similarity.

[0104] This application embodiment calculates curve similarity, orientation similarity, and distance similarity separately, and comprehensively evaluates the consistency between the transmitting node and the legitimate node from three dimensions: curve shape, spatial orientation, and propagation distance. It is difficult for attackers to forge all three dimensions of physical characteristics at the same time, which effectively improves the anti-spoofing capability and reliability of authentication.

[0105] Based on the above embodiments, the method further includes: The physical layer fingerprint features and / or the identity authentication decision are reported to the collaborative authentication fusion node. The collaborative authentication fusion node is used to receive the physical layer fingerprint features and / or identity authentication decisions reported by multiple receiving nodes, including this receiving node, and to perform consistency verification on the information reported by the multiple receiving nodes. Receive the collaborative authentication decision returned by the collaborative authentication fusion node.

[0106] The receiving node sends the physical layer fingerprint features and / or local identity authentication decision results extracted by itself to the collaborative authentication fusion node; the fusion node collects the information reported by multiple spatially separated receiving nodes and performs spatial consistency verification on the physical layer fingerprint features and / or identity authentication decisions reported by each node; the receiving node receives the collaborative authentication decision results returned by the fusion node to obtain the final determination of multi-node joint authentication.

[0107] Specifically, after receiving information reported by multiple receiving nodes, including itself, the collaborative authentication fusion node performs a consistency check on the information reported by each node. This consistency check involves the fusion node determining whether the physical layer fingerprint features and / or authentication decisions reported by each receiving node point to the same physical source. This can include determining whether the estimated directions of arrival of each receiving node converge at the same location in space; whether the estimated propagation distances of each receiving node satisfy the spatial geometric constraints between them; and whether the reconstructed Doppler zero-value curves of each receiving node correspond to a consistent motion state. If the reported information is spatially consistent, it indicates that each node is observing the same legitimate node. If they are inconsistent, there may be a spoofing attack, such as an attacker sending forged signals from different directions, or a strong multipath environment, where some nodes are distorted due to multipath effects.

[0108] After completing the reporting, the receiving node receives the collaborative authentication decision result returned by the collaborative authentication fusion node. The collaborative authentication decision supplements and verifies the local authentication decision. When the local decision may misjudge due to multipath interference or local disturbances affecting a single node, the collaborative decision provides a more reliable authentication result through spatial consistency verification across multiple nodes. In one embodiment, the collaborative decision uses the decision result of the collaborative authentication fusion node as the final authentication result; in another embodiment, the collaborative decision and the local decision are weighted and fused to obtain the final authentication result.

[0109] Through the above-described collaborative authentication interaction process, multiple spatially separated receiving nodes achieve joint observation and consistency verification of the same transmitting node, effectively solving the problem of misjudgment caused by multipath interference, obstruction and local interference affecting a single receiving node, and improving the reliability and robustness of identity authentication.

[0110] Based on the above embodiments, the method further includes: Obtain the signal quality parameters of the DNS discovery signal and / or the curve quality parameters of the Doppler zero-value curve; the signal quality parameters include received power and / or signal-to-noise ratio, and the curve quality parameters include curve distortion degree, zero-point offset and / or correlation coefficient with the reference curve; Based on the signal quality parameters and / or the curve quality parameters, identify whether the DNS discovery signal is an abnormal signal; If an abnormal signal is detected, authentication will be rejected or an alarm will be triggered.

[0111] At the same time as or before the physical layer fingerprint extraction and comparison decision, the receiving node obtains the signal quality parameters of the DNS discovery signal and / or the curve quality parameters of the Doppler zero value curve, and identifies whether the currently received signal is an abnormal signal, such as a spoofing attack signal, a multipath artifact signal, or a denial-of-service interference signal. If it is identified as an abnormal signal, it refuses authentication or triggers an alarm, so as to achieve effective detection and response to physical layer security threats.

[0112] Specifically, signal quality parameters include received power and / or signal-to-noise ratio (SNR), which reflect the signal quality of the DNS discovery signal at the physical layer. Received power can be measured using the Received Signal Strength Indicator (RSSI), and SNR can be calculated as the power ratio of the signal to the noise. Signal quality parameters can be used to identify denial-of-service interference. When an attacker sends a wideband noise-suppressed signal or a narrowband frequency-sweeping jamming signal, the received power may increase abnormally (high jamming signal power) or the SNR may decrease sharply (high noise power). When the variance of the received power or SNR fluctuation exceeds a preset fluctuation threshold, it indicates that denial-of-service interference may exist.

[0113] Curve quality parameters include curve distortion, zero-point offset, and / or correlation coefficient with a reference curve, used to reflect the morphological quality of the Doppler zero-value curve. Curve distortion can be quantified by the morphological difference between the curve and the reference curve; zero-point offset refers to the angular deviation between the zero-point direction of the curve to be authenticated and the zero-point direction of the reference curve; the correlation coefficient with the reference curve reflects the similarity of the overall shape of the curve to be authenticated and the reference curve. Curve quality parameters can be used to identify spoofing attacks and multipath artifacts. When an attacker forges a legitimate node ID and sends signals from different locations, the zero-point direction of the Doppler zero-value curve will shift, and the zero-point offset will exceed a preset tolerance. When a signal undergoes multipath reflection, the curve may exhibit distortion or multiple zeros, and the degree of curve distortion will exceed a preset distortion threshold, while the correlation coefficient with the reference curve will be lower than a preset correlation coefficient threshold.

[0114] The receiving node comprehensively identifies whether the DNS discovery signal is an abnormal signal based on the aforementioned signal quality parameters and / or curve quality parameters. If it is identified as an abnormal signal, it rejects authentication, discards the signal, and does not perform subsequent fingerprint comparison and identity authentication, or triggers a security alarm, such as reporting the abnormal event to the network management node.

[0115] Through the above-described abnormal signal identification process, this application embodiment achieves effective differentiation and proactive defense against spoofing attacks, multipath artifacts, and denial-of-service interference, further enhancing the security and reliability of the system.

[0116] In one embodiment, reference Figure 2 , Figure 2 This is a schematic diagram illustrating an embodiment of this application in a multi-UAV swarm communication scenario, in which the receiving node identifies legitimate signals, spoofing attacks, multipath artifacts, and DoS interference.

[0117] like Figure 2 As shown, the scenario includes multiple drone nodes and a ground control station. The legitimate node TX_L is a drone performing a reconnaissance mission, exhibiting genuine motion and periodically sending DNS discovery signals carrying its real identity ID according to a preset scan angle sequence. The deceptive node TX_A is a malicious drone attempting to impersonate the legitimate node and access the network by forging its ID; however, the deceptive node's actual spatial location and motion state differ from the legitimate node. Furthermore, the scenario contains reflective objects such as tall buildings or the ground, causing the DNS discovery signals sent by the legitimate node to form multipath reflection paths before reaching the receiving node. Simultaneously, the scenario also contains DoS interference sources, emitting broadband noise suppression signals, narrowband frequency sweep interference signals, pulse burst interference signals, or fake DNS curve interference signals.

[0118] Receiving nodes RX1, RX2, and RX3 are three spatially separated ground control stations or UAV nodes, each performing the following processing: The receiving node RX1 is located on the left side of the scene and receives wireless signals through an array antenna. RX1 first detects the identity ID information in the signal, reconstructs the DNS Doppler zero-value curve, and extracts physical layer fingerprint features. For the DNS discovery signal sent by the legitimate node TX_L, its identity ID is consistent with the legitimate node ID, and the reconstructed DNS curve matches the legitimate node's baseline DNS curve stored in the baseline fingerprint database, such as the curve shape being consistent and the zero-point direction being consistent with the legitimate node's orientation. Therefore, RX1 identifies it as a legitimate signal. For the spoofed signal sent by the deceitful node TX_A, although the identity ID is forged to be the legitimate node ID, because the deceitful node's spatial position and motion state are different from the legitimate node, its reconstructed DNS curve does not match the baseline DNS curve, such as the zero-point direction being offset and the curve shape being different. Therefore, RX1 identifies it as a spoofing attack signal.

[0119] For multipath signals that arrive after being reflected by a reflector, their propagation path is not a direct path. The propagation delay increases and the direction of arrival deviates from the true direction, resulting in distortion of the reconstructed Doppler zero-value curve, such as a distorted curve shape, the appearance of multiple zeros, or a decrease in the correlation coefficient with the reference curve. Therefore, RX2 identifies it as a multipath artifact signal.

[0120] When the RX3 detects an abnormal increase in received power or a sharp fluctuation in signal-to-noise ratio when it detects interference signals emitted by a DoS interference source, and is unable to reconstruct an effective DNS curve (e.g., inconsistent curve structure or unstable frequency offset residual), the RX3 identifies it as a DoS interference signal.

[0121] (2) Multi-receiving node collaborative authentication: Receiving nodes RX1, RX2 and RX2 are located in different spatial locations. After each extracts physical layer fingerprint features and / or local identity authentication decisions, they report the above information to the collaborative authentication fusion node, such as the ground control station or the swarm master node.

[0122] The collaborative authentication fusion node performs consistency verification on the information reported by each receiving node: For a legitimate signal sent by a legitimate node TX_L, the estimated directions of origin of the three receiving nodes converge in space to the same location, i.e. the location of the legitimate node. The estimated propagation distances of each node satisfy the spatial geometric constraints between each receiving node and the transmitting node. The reconstructed DNS curves of each node are consistent with the baseline fingerprint information. Therefore, the consistency check passes and the collaborative authentication decision is made to identify the node as legitimate.

[0123] For the spoofing signal sent by the spoofing node TX_A, since the spoofing node and the legitimate node are in different spatial locations, the estimated directions of the three receiving nodes converge at the location of the spoofing node instead of the location of the legitimate node. This is inconsistent with the reference direction and reference distance in the reference fingerprint information. Therefore, the consistency check fails and the collaborative authentication decision is that a spoofing attack exists.

[0124] For multipath reflection signals, only some receiving nodes (such as RX2 on the reflection path) detect curve distortion, while other receiving nodes (such as RX1 and RX3) receive normal direct path signals. The information reported by each receiving node is inconsistent. Based on this, the collaborative authentication fusion node identifies it as a multipath environment, and after comprehensive judgment, the authentication result of the direct path is still the standard.

[0125] When a DoS interference signal is detected, multiple receiving nodes detect abnormal power or drastic fluctuations in signal-to-noise ratio. The collaborative authentication fusion node integrates the information reported by each node, determines that an interference attack is currently in place, triggers a system alarm, and initiates anti-interference response measures.

[0126] Through the above processing, the receiving node and collaborative authentication fusion node in this embodiment of the application can effectively identify and distinguish legitimate signals, spoofing attacks, multipath artifacts and DoS interference, thus ensuring the secure communication of the UAV swarm network.

[0127] In one embodiment, reference Figure 3This embodiment includes one transmitting node (TX) to be authenticated and four spatially separated receiving nodes (RX1, RX2, RX3, and RX4). The transmitting node to be authenticated is a drone in a drone swarm, which sends a DNS discovery signal according to a preset scan angle sequence and declares its identity ID. The four receiving nodes are ground control stations or drone nodes in different spatial locations. Each node independently receives the DNS discovery signal from the TX, performs local authentication processing, and then reports the processing results to the collaborative authentication fusion node.

[0128] Each receiving node reconstructs its Doppler null curves C1-C4, estimates the azimuth of the transmitting node θ1-θ4, and calculates its local authentication scores s1-s4 before reporting them to the fusion node. The fusion node performs multi-azimuth intersection location verification, curve shape consistency verification, distance consistency verification, and motion state consistency verification on the information reported by each node to determine whether the observation results of each node point to the same physical source. If the azimuth rays of each node intersect at the same location, the curve shapes are consistent, the distances satisfy spatial geometric constraints, and the motion states point in the same direction, then the consistency verification passes. The fusion node performs a fusion decision on the four local authentication scores using a weighted average, Bayesian fusion, or voting mechanism, and combines this with the benchmark information in the joint fingerprint database to output the final authentication result.

[0129] Through the above-described multi-receiving node collaborative authentication process, the embodiments of this application overcome the problem of misjudgment caused by the susceptibility of a single receiving node to multipath interference, obstruction, or local interference, and further improve the reliability and robustness of identity authentication.

[0130] Figure 4 This is the second flowchart illustrating the wireless node authentication method provided in this application, as shown below. Figure 4 As shown, the method includes the following: Step 401: Obtain the motion state information of the transmitting node.

[0131] It should be noted that the execution subject of this application embodiment is the launching node.

[0132] During flight, the position and velocity of the transmitting node change continuously over time. In order to apply accurate Doppler frequency compensation in each scanning direction, the transmitting node needs to know its current motion state. Specifically, the transmitting node uses its equipped positioning, navigation, or motion sensing devices to collect its real-time motion-related parameters at the current moment, which may include position, velocity magnitude, velocity direction, acceleration, heading, and timestamp.

[0133] Step 402: Generate a DNS discovery signal based on the preset scan angle sequence and the motion state information.

[0134] The preset scan angle sequence refers to a set of multiple spatial angular directions pre-configured by the transmitting node before performing a Doppler null-value manipulated scan, used to sequentially transmit DNS discovery signals. This sequence is a crucial control parameter for the transmitting node in generating DNS discovery signals, determining the scan coverage, angular resolution, and scan order.

[0135] The DNS discovery signal is a signal formed by applying Doppler frequency compensation related to the scanning direction to the discovery signals in different scanning directions.

[0136] The transmitting node applies Doppler frequency compensation matching the direction and the current velocity vector to the discovery signal in each scanning direction according to the preset scanning angle sequence and its own current motion state information, and generates a direction-correlated pre-compensated DNS discovery signal, so that the receiving node can observe different residual Doppler frequency shift distributions in different directions of the signal.

[0137] Step 403: Send the DNS discovery signal so that the receiving node can reconstruct the Doppler zero curve and perform identity authentication based on the DNS discovery signal.

[0138] The transmitting node wirelessly transmits the generated DNS discovery signal, enabling the receiving node to receive the signal and reconstruct the Doppler zero-value curve. It then extracts the physical layer fingerprint features and compares them with the baseline fingerprint information to complete the authentication decision of the transmitting node's identity.

[0139] Specifically, the discovery signal transmitting unit of the transmitting node up-converts the baseband signal after directional correlation frequency compensation, amplifies it to a suitable transmission power through a power amplifier, and finally radiates it outward as a wireless signal through the transmitting antenna. The transmitting node transmits the pre-compensated discovery signal sequentially in each scanning direction according to the preset scanning angle sequence, forming a complete DNS discovery signal.

[0140] After the receiving node captures the DNS discovery signal in space through its array antenna, it performs beamforming, carrier synchronization and frequency offset estimation on the signal, reconstructs the Doppler zero curve, extracts the physical layer fingerprint features from the curve, and compares them with the reference fingerprint information to determine the legitimacy of the transmitting node's identity.

[0141] The purpose of the transmitting node sending the DNS discovery signal is to enable the receiving node to obtain the signal source for physical layer authentication. Since the DNS discovery signal carries different Doppler pre-compensation information in different scanning directions, the receiving node can reconstruct the Doppler null curve by measuring the residual Doppler frequency shift in each direction, and then extract physical layer fingerprint features such as null direction, null slope and curve shape. This eliminates the need for the transmitting node to actively report its own motion state and eliminates the need for additional multi-round authentication handshakes.

[0142] The wireless node authentication method provided in this application encodes its own motion state into the DNS discovery signal in a Doppler frequency compensation manner and sends it. It can provide the receiving node with a physical layer fingerprint carrier containing motion state and spatial location information without additional signaling interaction, effectively supporting the integrated realization of discovery and authentication, and reducing authentication latency and signaling overhead.

[0143] Based on the above embodiments, generating a DNS discovery signal according to a preset scan angle sequence and the motion state information includes: Based on the speed magnitude and direction of the transmitting node in the motion state information, and each scanning direction in the preset scanning angle sequence, calculate the Doppler frequency compensation amount corresponding to each scanning direction; Based on the Doppler frequency compensation amount corresponding to each scanning direction, the baseband detection signal is frequency modulated to generate a Doppler pre-compensated transmission signal; The DNS discovery signal is formed by transmitting Doppler-precompensated discovery signals in each scanning direction.

[0144] Based on the geometric relationship between its own velocity vector and each scanning direction, the transmitting node calculates the Doppler frequency compensation amount in each scanning direction one by one, and uses the calculated compensation amount to frequency modulate the baseband discovery signal, that is, superimpose a frequency offset corresponding to the compensation amount on the baseband signal to generate a Doppler pre-compensated transmission signal. Then, according to the scanning angle sequence, the pre-compensated discovery signal is transmitted in each scanning direction in sequence to form a complete DNS discovery signal.

[0145] Specifically, based on the magnitude and direction of the transmitting node's velocity, and each scanning direction in the preset scanning angle sequence, the Doppler frequency compensation for each scanning direction is calculated one by one. This compensation is the negative of the theoretical Doppler frequency shift in that scanning direction. When the transmitting node has a radial velocity component toward the receiving node in a certain scanning direction, the Doppler frequency shift is positive and the compensation is negative; when there is a radial velocity component away from the receiving node, the Doppler frequency shift is negative and the compensation is positive; when the radial velocity component is zero, the compensation is zero.

[0146] After obtaining the compensation amount corresponding to each scanning direction, the compensation unit performs frequency modulation on the baseband discovery signal. The baseband discovery signal is the original signal that the transmitting node is preparing to send, containing pilot sequences, synchronization sequences, and identification auxiliary information. Based on the calculated compensation amount, the compensation unit applies a corresponding frequency offset to the baseband discovery signal. For example, it superimposes a frequency offset value corresponding to the compensation amount onto the baseband signal using digital frequency modulation, causing the modulated baseband signal to have a frequency offset consistent with the compensation amount. For each scanning direction in the scanning angle sequence, the compensation unit uses the compensation amount corresponding to that direction to perform frequency modulation on the baseband signal, generating Doppler pre-compensated transmit signals with different frequency offset characteristics for each scanning direction.

[0147] Then, following the preset scan angle sequence, pre-compensated discovery signals are transmitted sequentially in each scan direction. Except for the frequency offset, the transmitted signals in each direction maintain consistency in time-frequency resources, modulation scheme, and signal content. The transmitted signals in all scan directions together constitute a complete DNS discovery signal.

[0148] In this embodiment, the transmitting node applies different Doppler frequency compensations to each scanning direction based on its own velocity vector, encoding the velocity information into frequency offset differences in each direction. This enables the receiving node to extract motion state information and reconstruct high-resolution Doppler zero-value curves without additional signaling, effectively supporting the integrated realization of discovery and authentication.

[0149] In one embodiment, reference Figure 5 This embodiment includes a transmitting node TX and a receiving node RX. The transmitting node TX is a drone that moves at a speed of |v| along the velocity direction v. The receiving node RX is a ground control station that is fixedly deployed in the actual propagation direction (azimuth angle θ) of the transmitting node.

[0150] Before sending the DNS discovery signal, the transmitting node first obtains its own motion status information through the airborne GNSS receiver and obtains the preset scan angle sequence.

[0151] The direction-dependent frequency compensation unit of the transmitting node calculates the Doppler frequency compensation for each scanning direction based on the geometric relationship between its own velocity vector and each scanning direction. Specifically, for each scanning direction in the scanning angle sequence... The projection component of the velocity vector of the transmitting node in that direction determines the theoretical Doppler frequency shift, and the compensation amount is the negative of this theoretical value. After independently calculating the compensation amount for each scanning direction in the scanning angle sequence, the compensation unit applies the corresponding frequency compensation to the baseband discovery signal, generating a pre-compensated Doppler transmission signal for each scanning direction. The discovery signal transmitting unit transmits the pre-compensated discovery signal sequentially in each scanning direction according to the order of the scanning angle sequence, forming a complete DNS discovery signal.

[0152] The receiving node RX is located in the actual propagation direction (azimuth angle θ) of the transmitting node TX, and receives the DNS discovery signal from the transmitting node through an array antenna. The receiving node performs beamforming in multiple spatial directions to acquire the received signal components in different spatial directions, and performs carrier synchronization and frequency offset estimation for each direction, extracting the residual Doppler frequency shift value for each direction. When the beam pointing direction of the receiving node is close to the actual propagation azimuth of the transmitting node (i.e., the θ direction), the pre-compensation of the transmitting node in that direction completely cancels out the Doppler frequency shift generated during actual propagation, and the residual Doppler frequency shift measured by the receiving node in that direction is close to zero. The receiving node arranges the residual Doppler frequency shift values ​​measured in each spatial direction in spatial order to reconstruct a "spatial direction - residual Doppler frequency shift" curve, i.e., the Doppler zero-value curve.

[0153] like Figure 5 As shown by the dashed curve, the transmitting node is positioned according to the scanning angle. Apply direction-dependent frequency compensation when scanning direction When the scanning direction approaches the true propagation azimuth θ, the residual Doppler frequency shift measured by the receiver is close to zero, which is the zero point of the DNS curve. When the scanning direction deviates from the true propagation azimuth θ, the absolute value of the residual Doppler frequency shift gradually increases, and the curve exhibits an approximately linear change. By detecting the direction of the zero point of this curve, the receiving node can determine the direction of arrival of the transmitting node θ. At the same time, by extracting features such as the slope, curvature, and correlation coefficient with the reference curve of the zero point of the curve, a physical layer fingerprint is constructed for identity authentication.

[0154] Through the DNS scanning process described above, this embodiment of the application utilizes the entire Doppler zero-value curve, rather than a single Doppler value, as the authentication fingerprint. This curve is jointly determined by the actual spatial location, velocity magnitude, velocity direction of the transmitting node, and the location of the receiving node, making it difficult for an attacker to simultaneously forge all of the above information. Furthermore, this scanning process completes both azimuth estimation and physical layer fingerprint extraction within a single signal transmission, effectively supporting the integrated implementation of discovery and authentication.

[0155] To further explain the wireless node authentication method provided in this application, please refer to the following embodiments.

[0156] This embodiment specifically proposes a rapid mobile wireless node discovery and collaborative authentication system based on the DNS Doppler zero-value curve, referencing... Figure 6 The system includes a transmitter node TX, three receiver nodes RX1, RX2, and RX3, a collaborative authentication fusion center FC, and a physical layer fingerprint database FP.

[0157] The transmitting node TX is a drone that acquires its own motion status information through onboard GNSS, applies Doppler frequency compensation matching the velocity vector to each scanning direction according to a preset scanning angle sequence, and generates and sends DNS discovery signals.

[0158] The three receiving nodes are spatially separated ground control stations, each independently receiving DNS discovery signals and performing beamforming, frequency offset estimation, DNS curve reconstruction, physical layer fingerprint extraction, azimuth / distance estimation, and local authentication, respectively. They then report the physical layer fingerprint features, local authentication scores, azimuth / distance estimation results, and anomaly detection results to the Collaborative Authentication Fusion Center (FC).

[0159] The Collaborative Authentication Fusion Center (FC) performs multi-node feature fusion and consistency verification on the information reported by each receiving node, including orientation intersection location verification, distance geometric constraint verification, and curve shape consistency verification. It also reads the baseline fingerprint information of legitimate nodes from the Physical Layer Fingerprint Database (FP) for matching. Based on the verification and matching results, it outputs the final authentication result, including legitimacy, spoofing, multipath, and DoS. After successful authentication, the FC can store the current fingerprint as the updated fingerprint in the FP, enabling dynamic updates to the fingerprint database.

[0160] Through the above system, the embodiments of this application realize the organic combination of single-node local authentication and multi-node collaborative authentication, effectively improving the reliability and anti-spoofing capability of wireless node identity authentication in high-speed mobile scenarios.

[0161] The wireless node authentication device provided in this application is described below. The wireless node authentication device described below can be referred to in correspondence with the wireless node authentication method described above.

[0162] refer to Figure 7 The wireless node authentication device provided in this application includes: Receiver module 701 is used to receive the Doppler zero value manipulated DNS discovery signal sent by the transmitting node; The residual Doppler frequency shift information acquisition module 702 is used to acquire the residual Doppler frequency shift information of the DNS discovery signal in different spatial directions; The Doppler zero-value curve reconstruction module 703 is used to reconstruct the Doppler zero-value curve based on the correspondence between the spatial direction and the residual Doppler frequency shift information. The authentication module 704 is used to extract physical layer fingerprint features based on the Doppler zero-value curve, compare the physical layer fingerprint features with the reference fingerprint information, and determine the identity authentication decision based on the comparison result.

[0163] The wireless node authentication device provided in this application receives the DNS discovery signal sent by the transmitting node, obtains residual Doppler frequency shift information in different spatial directions, reconstructs the Doppler zero-value curve, and then extracts physical layer fingerprint features and compares them with the reference fingerprint information to complete authentication. This achieves the integration of neighbor discovery and identity authentication at the physical layer, eliminating the need for traditional multi-round authentication handshakes and reducing authentication latency in high-speed dynamic scenarios. At the same time, the DNS curve, as a high-dimensional physical layer fingerprint containing information such as node spatial location, motion state, and propagation path, has stronger unforgeability than a single RSS, AoA, CFO, or Doppler value, effectively improving anti-spoofing capabilities and solving the defects of unreliable authentication and high latency in high-speed mobile scenarios in existing technologies.

[0164] refer to Figure 8 The wireless node authentication device also provided in this application further includes: Motion state information acquisition module 801 is used to acquire the motion state information of the transmitting node; DNS discovery signal generation module 802 is used to generate a DNS discovery signal based on a preset scan angle sequence and the motion state information; the DNS discovery signal is a signal formed by applying Doppler frequency compensation related to the scan direction to the discovery signals in different scan directions; The transmitting module 803 is used to transmit the DNS discovery signal so that the receiving node can reconstruct the Doppler zero value curve and perform identity authentication based on the DNS discovery signal.

[0165] The wireless node authentication device provided in this application provides a physical layer fingerprint carrier containing motion state and spatial location information to the receiving node by encoding its own motion state into the DNS discovery signal in a Doppler frequency compensation manner and sending it, without the need for additional signaling interaction. This effectively supports the integrated realization of discovery and authentication, and reduces authentication latency and signaling overhead.

[0166] Figure 9 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 9As shown, the electronic device may include a processor 910, a communications interface 920, a memory 930, and a communication bus 940, wherein the processor 910, the communications interface 920, and the memory 930 communicate with each other via the communication bus 940. The processor 910 can call logical instructions in the memory 930 to execute a wireless node authentication method. This method includes: receiving a Doppler zero-value manipulated DNS discovery signal sent by a transmitting node; acquiring residual Doppler frequency shift information of the DNS discovery signal in different spatial directions; reconstructing a Doppler zero-value curve based on the correspondence between the spatial directions and the residual Doppler frequency shift information; extracting physical layer fingerprint features based on the Doppler zero-value curve; comparing the physical layer fingerprint features with reference fingerprint information; and determining an authentication decision based on the comparison result.

[0167] The processor 910 can call logic instructions in the memory 930 to execute a wireless node authentication method, which includes: acquiring motion state information of the transmitting node; generating a DNS discovery signal according to a preset scan angle sequence and the motion state information; the DNS discovery signal is a signal formed by applying Doppler frequency compensation related to the scan direction to discovery signals in different scan directions; and sending the DNS discovery signal so that the receiving node can reconstruct the Doppler zero-value curve based on the DNS discovery signal and perform identity authentication.

[0168] Furthermore, the logical instructions in the aforementioned memory 930 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0169] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the wireless node authentication method provided by the above methods. The method includes: receiving a Doppler zero-value manipulated DNS discovery signal sent by a transmitting node; acquiring residual Doppler frequency shift information of the DNS discovery signal in different spatial directions; reconstructing a Doppler zero-value curve according to the correspondence between the spatial directions and the residual Doppler frequency shift information; extracting physical layer fingerprint features according to the Doppler zero-value curve; comparing the physical layer fingerprint features with reference fingerprint information; and determining an identity authentication decision based on the comparison result.

[0170] When the computer program is executed by the processor, the computer can execute the wireless node authentication method provided by the above methods. The method includes: acquiring the motion state information of the transmitting node; generating a DNS discovery signal according to a preset scan angle sequence and the motion state information; the DNS discovery signal is a signal formed by applying Doppler frequency compensation related to the scan direction to the discovery signal in different scan directions; and sending the DNS discovery signal so that the receiving node can reconstruct the Doppler zero value curve according to the DNS discovery signal and perform identity authentication.

[0171] In another aspect, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the wireless node authentication method provided by the above methods. The method includes: receiving a Doppler zero-value manipulated DNS discovery signal sent by a transmitting node; acquiring residual Doppler frequency shift information of the DNS discovery signal in different spatial directions; reconstructing a Doppler zero-value curve according to the correspondence between the spatial directions and the residual Doppler frequency shift information; extracting physical layer fingerprint features according to the Doppler zero-value curve; comparing the physical layer fingerprint features with reference fingerprint information; and determining an authentication decision based on the comparison result.

[0172] When executed by a processor, the computer program implements the wireless node authentication method provided by the above methods. The method includes: acquiring motion state information of the transmitting node; generating a DNS discovery signal based on a preset scan angle sequence and the motion state information; the DNS discovery signal is a signal formed by applying Doppler frequency compensation related to the scan direction to discovery signals in different scan directions; and sending the DNS discovery signal so that the receiving node can reconstruct the Doppler zero-value curve based on the DNS discovery signal and perform identity authentication.

[0173] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0174] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0175] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A wireless node authentication method, characterized in that, Applied to receiving nodes, including: Receive the Doppler zero value manipulation DNS discovery signal sent by the transmitting node; Obtain the residual Doppler frequency shift information of the DNS discovery signal in different spatial directions; Based on the correspondence between the spatial direction and the residual Doppler frequency shift information, the Doppler zero-value curve is reconstructed; Physical layer fingerprint features are extracted based on the Doppler zero-value curve, and the physical layer fingerprint features are compared with the reference fingerprint information. An identity authentication decision is determined based on the comparison result.

2. The wireless node authentication method according to claim 1, characterized in that, The step of obtaining the residual Doppler frequency shift information of the DNS discovery signal in different spatial directions includes: Beamforming is performed on the DNS discovery signal using an array antenna to obtain received signal components in multiple beam directions; Carrier synchronization and frequency offset estimation are performed on the received signal components in each beam direction, and the residual Doppler frequency shift value corresponding to each beam direction is extracted.

3. The wireless node authentication method according to claim 1, characterized in that, The step of reconstructing the Doppler zero-value curve based on the correspondence between the spatial direction and the residual Doppler frequency shift information includes: A data point sequence is constructed with each spatial direction as the horizontal axis and the corresponding residual Doppler frequency shift value as the vertical axis. The data point sequence is interpolated or fitted to form a curve showing the continuous residual Doppler frequency shift as a function of spatial direction, which serves as the Doppler zero-value curve.

4. The wireless node authentication method according to any one of claims 1 to 3, characterized in that, The physical layer fingerprint features include at least one of the following: The direction of the zero point of the Doppler zero-value curve; The slope of the Doppler zero-value curve at the zero point; The curvature characteristics of the Doppler zero-value curve; The correlation coefficient between the Doppler zero-value curve and the baseline curve; The zero-value depth or zero-value width of the Doppler zero-value curve.

5. The wireless node authentication method according to claim 1, characterized in that, The step of comparing the physical layer fingerprint features with the reference fingerprint information and determining the identity authentication decision based on the comparison result includes: Calculate the similarity between the physical layer fingerprint features and the reference fingerprint information; the similarity includes at least one of curve similarity, orientation similarity, and distance similarity; If the similarity is greater than or equal to a preset threshold, the transmitting node is determined to be a legitimate node. If the similarity is less than a preset threshold, the transmitting node is determined to be an illegal node.

6. The wireless node authentication method according to claim 5, characterized in that, The calculation of the similarity between the physical layer fingerprint features and the reference fingerprint information includes: The direction of arrival of the transmitting node is determined based on the zero point direction of the Doppler zero-value curve; Based on the propagation delay of the DNS discovery signal, the propagation distance between the transmitting node and the receiving node is determined; The curve correlation between the Doppler zero-value curve and the baseline curve in the baseline fingerprint information is calculated as the curve similarity. Calculate the orientation error between the incoming orientation and the reference orientation in the reference fingerprint information, and use it as the orientation similarity. The distance error between the propagation distance and the reference distance in the reference fingerprint information is calculated as the distance similarity.

7. The wireless node authentication method according to claim 1, characterized in that, The method further includes: The physical layer fingerprint features and / or the identity authentication decision are reported to the collaborative authentication fusion node. The collaborative authentication fusion node is used to receive the physical layer fingerprint features and / or identity authentication decisions reported by multiple receiving nodes, including this receiving node, and to perform consistency verification on the information reported by the multiple receiving nodes. Receive the collaborative authentication decision returned by the collaborative authentication fusion node.

8. The wireless node authentication method according to claim 1, characterized in that, The method further includes: Obtain the signal quality parameters of the DNS discovery signal and / or the curve quality parameters of the Doppler zero-value curve; the signal quality parameters include received power and / or signal-to-noise ratio, and the curve quality parameters include curve distortion degree, zero-point offset and / or correlation coefficient with the reference curve; Based on the signal quality parameters and / or the curve quality parameters, identify whether the DNS discovery signal is an abnormal signal; If an abnormal signal is detected, authentication will be rejected or an alarm will be triggered.

9. A wireless node authentication method, characterized in that, Applied to the transmitting node, including: Obtain the motion state information of the transmitting node; A DNS discovery signal is generated based on a preset scan angle sequence and the motion state information; the DNS discovery signal is a signal formed by applying Doppler frequency compensation related to the scan direction to the discovery signals in different scan directions. The DNS discovery signal is sent so that the receiving node can reconstruct the Doppler zero-value curve and perform identity authentication based on the DNS discovery signal.

10. The wireless node authentication method according to claim 9, characterized in that, The step of generating a DNS discovery signal based on a preset scan angle sequence and the motion state information includes: Based on the speed magnitude and direction of the transmitting node in the motion state information, and each scanning direction in the preset scanning angle sequence, calculate the Doppler frequency compensation amount corresponding to each scanning direction; Based on the Doppler frequency compensation amount corresponding to each scanning direction, the baseband detection signal is frequency modulated to generate a Doppler pre-compensated transmission signal; The DNS discovery signal is formed by transmitting Doppler-precompensated discovery signals in each scanning direction.

11. A wireless node authentication device, characterized in that, Applied to receiving nodes, including: The receiving module is used to receive the Doppler zero-value manipulated DNS discovery signal sent by the transmitting node; The residual Doppler frequency shift information acquisition module is used to acquire the residual Doppler frequency shift information of the DNS discovery signal in different spatial directions; The Doppler zero-value curve reconstruction module is used to reconstruct the Doppler zero-value curve based on the correspondence between the spatial direction and the residual Doppler frequency shift information; The authentication module is used to extract physical layer fingerprint features based on the Doppler zero-value curve, compare the physical layer fingerprint features with the reference fingerprint information, and determine the identity authentication decision based on the comparison result.

12. A wireless node authentication device, characterized in that, Applied to the transmitting node, including: The motion state information acquisition module is used to acquire the motion state information of the transmitting node; The DNS discovery signal generation module is used to generate a DNS discovery signal based on a preset scan angle sequence and the motion state information; the DNS discovery signal is a signal formed by applying Doppler frequency compensation related to the scan direction to the discovery signals in different scan directions. The sending module is used to send the DNS discovery signal so that the receiving node can reconstruct the Doppler zero curve and perform identity authentication based on the DNS discovery signal.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the wireless node authentication method as described in any one of claims 1 to 10.

14. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the wireless node authentication method as described in any one of claims 1 to 10.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the wireless node authentication method as described in any one of claims 1 to 10.

Images