Vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna

Abstract

The application discloses a kind of vehicle-mounted UWB-AOA circular polarization high-precision positioning antenna, it is related to vehicle antenna positioning technical field.The vehicle-mounted UWB-AOA circular polarization high-precision positioning antenna includes: dielectric substrate and radiation layer, and the feed layer below radiation layer, and radiation layer is installed at substrate bottom, it is characterized in that, still include: the one end array of feed layer is close to radiation layer is installed with circular polarization antenna, and vehicle positioning is carried out based on circular polarization antenna, metal shielding layer for isolating external interference is arranged below feed layer, UWB transceiver module is installed below shielding layer, time stamp controller is installed in UWB transceiver module, the present application is positioned based on circular polarization antenna vehicle, to ensure the receiving stability of signal in complex environment, in turn, still can obtain stable and reliable three-dimensional positioning result under complex environment, and then guarantee the high-precision positioning demand of vehicle under dynamic operation condition.

Description

Technical Field

[0001] This invention relates to the field of vehicle-mounted antenna positioning technology, specifically to a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna. Background Technology

[0002] With the development of intelligent and connected vehicles, vehicle positioning technology has become one of the core components for realizing intelligent driving and vehicle networking applications. Early vehicle positioning relied heavily on GNSS, which could provide basic geographic coordinate information for vehicles. However, in urban canyons, underground parking garages, and complex road environments, GNSS is easily affected by obstruction, multipath effects, and interference, making it difficult to meet lane-level and centimeter-level positioning requirements in terms of positioning accuracy and stability.

[0003] In recent years, ultra-wideband (UWB) technology has been widely used in high-precision positioning scenarios due to its high time resolution and anti-interference capabilities. It can make full use of the wide bandwidth characteristics of UWB signals to achieve sub-meter or even centimeter-level positioning accuracy. In order to further improve anti-interference performance and positioning reliability, circularly polarized antennas have been gradually introduced into vehicle positioning systems. They can maintain the consistency of signal polarization in different attitudes and complex environments, and reduce interference caused by reflection and multipath effects.

[0004] The limitations of existing technologies include at least the following problems: existing technologies struggle to maintain stable positioning accuracy in complex environments. When vehicles are in environments such as densely populated urban roads, tunnels, or underground parking lots, electromagnetic signals are often affected by effects such as reflection and scattering, resulting in multipath propagation. They are also subject to strong noise interference from onboard electronic devices and external communication devices. Due to the lack of comprehensive evaluation and dynamic correction of signal quality, existing technologies cannot promptly identify the differences between interfered signals and reliable signals, leading to large fluctuations in positioning results, decreased positioning accuracy, and difficulty in meeting the requirements of high-precision positioning. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna, which solves the problem that existing technologies cannot meet the high-precision positioning requirements of vehicles in complex environments.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna, comprising the following steps: a dielectric substrate and a radiating layer, and a feed layer located below the radiating layer, wherein the radiating layer is mounted on the bottom of the substrate. The invention is characterized by further comprising: a circularly polarized antenna array mounted on one end of the feed layer near the radiating layer, and vehicle positioning based on the circularly polarized antenna; a metal shielding layer for isolating external interference disposed below the feed layer; a UWB transceiver module mounted below the shielding layer; and a timestamp controller installed inside the UWB transceiver module.

[0007] Furthermore, the UWB transceiver module is equipped with a temperature sensor, the output of which is electrically connected to the temperature display bar 8 installed at the bottom of the UWB transceiver module. A sealing strip is provided at the joint between the UWB transceiver module and the shielding layer, and a sealing plate is provided inside the UWB transceiver module.

[0008] Furthermore, a display panel is installed at the front end of the substrate, and a status light bar for displaying the operating status of the positioning device is provided on its front side. A locking block is symmetrically arranged at the bottom of the shielding layer, and the locking block is elastically connected to the shielding layer by a spring.

[0009] Further, the specific steps for vehicle positioning based on circularly polarized antennas are as follows: Acquire the UWB transmitted signal of the designated vehicle and the UWB received signal of each circularly polarized antenna; analyze the initial positioning set of each circularly polarized antenna of the designated vehicle, including propagation time and phase angle; based on a pre-trained UWB signal analysis model and combined with the UWB received signal of each circularly polarized antenna of the designated vehicle, analyze the positioning signal feature set of its corresponding circularly polarized antenna, including time delay confidence feature value and azimuth signal feature value; based on the initial positioning set and positioning signal feature set of each circularly polarized antenna of the designated vehicle, analyze the corrected positioning set of its corresponding circularly polarized antenna; based on the corrected positioning set and positioning signal feature set of each circularly polarized antenna of the designated vehicle, analyze the three-dimensional position coordinates of the designated vehicle and upload them to the display panel.

[0010] Furthermore, the UWB transmitted signal includes a transmission timestamp, and the UWB received signal includes a reception timestamp and the received amplitude at each time point. The specific steps for analyzing the initial positioning set of each circularly polarized antenna of the vehicle are as follows: Based on the transmission timestamp of the vehicle and the reception timestamp of each circularly polarized antenna, analyze the propagation duration value of the corresponding circularly polarized antenna; based on the received amplitude of each circularly polarized antenna of the vehicle at each time point, analyze the phase angle of the corresponding circularly polarized antenna.

[0011] Further, the specific steps for analyzing the location signal feature set of each circularly polarized antenna of the vehicle are as follows: Input the UWB received signal of each circularly polarized antenna of the vehicle into the pre-trained UWB signal analysis model, and analyze the signal evaluation feature set of its corresponding circularly polarized antenna, including energy accumulation feature value, signal envelope stability feature value, channel impulse response clarity feature value, circular polarization feature value, noise correlation feature value, and multipath delay spread feature value; Based on the signal evaluation feature set of each circularly polarized antenna of the vehicle, analyze the time delay confidence feature value and location signal feature value of its corresponding circularly polarized antenna.

[0012] Furthermore, the UWB signal analysis model includes a UWB input processing layer for receiving UWB received signals, a UWB feature construction layer for extracting features of UWB received signals, and a UWB output layer for outputting UWB signal feature values.

[0013] Furthermore, the specific steps for analyzing the signal evaluation feature set of each circularly polarized antenna of the vehicle are as follows: In the UWB input processing layer of the UWB signal analysis model, the UWB received signal of each circularly polarized antenna of the vehicle is received and preprocessed; in the UWB feature construction layer of the UWB signal analysis model, based on the preprocessed UWB received signal of each circularly polarized antenna of the vehicle, the positioning feature vector of the corresponding circularly polarized antenna is extracted; in the UWB output layer of the UWB signal analysis model, based on the positioning feature vector of each circularly polarized antenna of the vehicle, the signal evaluation feature set of the corresponding circularly polarized antenna is output.

[0014] Furthermore, the specific steps for analyzing the corrected positioning set of each circularly polarized antenna of the vehicle are as follows: obtain the vehicle speed value and the temperature value of the UWB transceiver module, and analyze the propagation correction value of the corresponding circularly polarized antenna by combining the time delay confidence characteristic value and propagation duration value of each circularly polarized antenna; based on the azimuth confidence characteristic value and phase angle of each circularly polarized antenna of the vehicle, analyze the phase correction angle of the corresponding circularly polarized antenna.

[0015] Further, the specific steps for analyzing the three-dimensional position coordinates of the vehicle are as follows: Obtain the three-dimensional position coordinates of each circularly polarized antenna of the vehicle, and analyze the angle of arrival of several pairs of circularly polarized antennas of the vehicle in conjunction with the phase correction angle; Based on the three-dimensional position coordinates, propagation correction value, and positioning signal feature set of each circularly polarized antenna of the vehicle, and in conjunction with the angle of arrival of each pair of circularly polarized antennas, construct a weighted least squares equation system for the vehicle, and perform iterative solution processing to obtain the three-dimensional position coordinates of the vehicle body; Perform coordinate transformation processing on the three-dimensional position coordinates of the vehicle body to obtain the three-dimensional position coordinates of the vehicle.

[0016] The present invention has the following beneficial effects:

[0017] (1) The vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna can significantly reduce multipath reflection interference caused by surrounding buildings and other factors by installing a circularly polarized antenna in the feed layer array, thereby ensuring the signal reception stability in complex environments. The circularly polarized antenna is combined with the UWB transceiver module, and the propagation time and phase angle of the received signal are precisely calibrated by using a timestamp controller. At the same time, the positioning signal feature set is extracted by the UWB signal analysis model, thereby correcting the signal in all aspects, highlighting the contribution of reliable signals, suppressing the influence of interference signals, and thus obtaining stable and reliable three-dimensional positioning results in complex environments, thereby ensuring the high-precision positioning requirements of the vehicle under dynamic operating conditions.

[0018] (2) The vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna introduces a pre-trained UWB signal analysis model to conduct in-depth analysis of the UWB received signal of the circularly polarized antenna. This allows for the extraction of confidence features of the UWB received signal before signal calculation, such as signal envelope stability and clear channel impulse response. These features are then mapped to time delay confidence feature values ​​and azimuth confidence feature values, thereby measuring the reliability of each UWB received signal in the positioning calculation. This reduces interference caused by multipath effects and also analyzes the stability of the signal under different working conditions, making the positioning analysis more reliable and thus improving the overall positioning accuracy.

[0019] (3) The vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna obtains the vehicle speed value and the temperature value of the UWB transceiver module, and combines the time delay confidence feature value and propagation time value of each circularly polarized antenna to analyze the propagation correction value, so as to eliminate the Doppler effect caused by vehicle speed and the influence of temperature on the stability of crystal oscillator clock. At the same time, based on the azimuth confidence feature value and phase angle, the phase correction angle is extracted to correct the deviation caused by the change of signal propagation path. In the final three-dimensional positioning, the antenna three-dimensional coordinates, propagation correction value and confidence feature set are combined to construct a weighted least squares equation system, and the vehicle body coordinates are obtained by iterative convergence solution, so as to ensure that the positioning result can adapt to the change of vehicle operating state, and thus achieve a high-precision positioning effect even under high-speed driving or temperature fluctuation.

[0020] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0021] Figure 1 This is a three-dimensional structural diagram of a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to the present invention.

[0022] Figure 2This is a three-dimensional structural diagram of the temperature sensor, temperature display bar, and sealing bar components of a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to the present invention.

[0023] Figure 3 This is a three-dimensional structural diagram of the UWB transceiver module, timestamp controller, and sealing plate of a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to the present invention.

[0024] Figure 4 This is a flowchart illustrating the specific steps of vehicle positioning based on a circularly polarized antenna in the present invention, which is a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna.

[0025] Figure 5 This is a schematic diagram of the circular polarization antenna sequence data for setting the vehicle's azimuth analysis in a vehicle-mounted UWB-AOA circular polarization high-precision positioning antenna according to the present invention.

[0026] Figure 6 This is a flowchart illustrating the specific steps involved in analyzing and setting the signal evaluation feature set for each circularly polarized antenna in a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to the present invention.

[0027] Figure 7 This is a flowchart illustrating the specific steps involved in analyzing and setting the three-dimensional position coordinates of a vehicle in a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to the present invention.

[0028] The components in the attached diagram are labeled as follows: 1. Base plate, 101. Mounting port, 2. Radiation layer, 3. Feeding layer, 4. Shielding layer, 5. UWB transceiver module, 6. Timestamp controller, 7. Temperature sensor, 8. Temperature display bar, 9. Sealing bar, 10. Display panel, 11. Status light bar, 12. Locking block, 13. Spring, 14. Sealing plate. Detailed Implementation

[0029] Please see Figure 1-3This invention provides a technical solution: a vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna, comprising: a dielectric substrate 1 (the substrate 1 is made of FR4 material, which can effectively reduce signal transmission loss and improve the performance stability of the antenna), a radiating layer 2, and a feed layer 3 located below the radiating layer 2. The feed layer 3 uses a microstrip line feeding method. By precisely controlling the width and length of the microstrip line, good matching and efficient feeding of the antenna are achieved. The linewidth of the microstrip line is determined according to the dielectric constant of the FR4 material used in the substrate 1 and the substrate thickness, so that the microstrip transmission line can maintain a characteristic impedance of about 50 ohms in the operating frequency band (e.g., when the dielectric constant of the FR4 material is stable at about 4 and the substrate thickness is set to about 1.6 mm, the linewidth of the feed line is obtained from impedance calculation and optimization simulation in the range of 2 mm to 3 mm, which can effectively meet the 50 ohm impedance requirement). The length of the feed line depends on the operating frequency of the antenna. The matching design is performed based on the principle that the electrical length of the feeder line should be close to one-quarter or an integer multiple of the effective wavelength at the operating frequency, so as to achieve the best energy transmission effect in the target frequency band. (For example, at a center frequency of 6.5 GHz, the signal propagation speed in FR4 medium is lower than the speed of light in free space, thus shortening the wavelength. Under this condition, the feeder line length range is approximately 8 mm to 12 mm. By selecting an appropriate length within this range and fine-tuning it in conjunction with electromagnetic simulation, good impedance matching and radiation performance can be maintained in the ultra-wideband operating frequency band.) The radiating layer 2 is mounted on the bottom of the substrate 1. The radiating layer 2 adopts a special patch structure. By optimizing the size and shape of the patch, circular polarization radiation is achieved. The radius of the patch is designed according to the center frequency of the UWB band to ensure that a stable circular polarization electric field can be generated in the UWB band of 6.5 GHz-8.5 GHz. The feature is that it also includes:

[0030] Several circularly polarized antennas are arrayed at one end of the feed layer 3 near the radiation layer 2 (these are responsible for transmitting and receiving UWB signals to achieve vehicle positioning). Vehicle positioning is based on the circularly polarized antennas. The circularly polarized antennas are provided with signals of equal amplitude and 90° phase difference by an orthogonal feed network to generate a stable circularly polarized electric field in the ultra-wideband operating frequency band. Below the feed layer 3, a metal shielding layer 4 is set to isolate external interference. It is made of copper foil and can effectively shield external electromagnetic interference, improving the antenna's anti-interference capability. Below the shielding layer 4, a UWB transceiver module 5 is installed. It is responsible for processing the transmission and reception of UWB signals to realize communication between the vehicle and external devices. The UWB transceiver module 5 has a timestamp controller 6 installed inside to accurately calibrate the time reference of the received signal.

[0031] The UWB transceiver module 5 is equipped with a temperature sensor 7 for real-time temperature monitoring. Its output is electrically connected to a temperature display bar 8 installed at the bottom of the UWB transceiver module 5 to achieve real-time temperature monitoring. Users can observe the operating temperature of the UWB transceiver module 5 by observing the temperature display bar 8. When the temperature rises abnormally, heat dissipation measures can be taken to ensure positioning accuracy. A sealing strip 9 is provided at the joint between the UWB transceiver module 5 and the shielding layer 4 to prevent dust and moisture intrusion and improve the environmental adaptability of the device. A sealing plate 14 is provided inside the UWB transceiver module 5. The sealing plate 14 plays a sealing role to protect the electronic components inside the UWB transceiver module 5 and prevent dust, moisture and other contaminants from entering.

[0032] A display panel 10 is mounted on the front end of the substrate 1 and is electrically connected to the UWB transceiver module 5. The display panel 10 is used to display the working status, positioning information and other related data of the device. A status light bar 11 is provided on the front side to display the operating status of the positioning device. It can display the working status of the device in different colors or flashing frequencies, such as green for normal operation and red for fault alarm. The bottom sides of the shielding layer 4 are symmetrically provided with locking blocks 12 for installing the positioning device. The locking blocks 12 are elastically connected to the shielding layer 4 through springs 13. Mounting holes 101 are provided at the four corners of the substrate 1, the radiation layer 2, the power supply layer 3 and the shielding layer 4 for fasteners to be inserted and fixed, that is, to realize the installation and fixation between the various components of the device and ensure the stability of the overall structure.

[0033] Furthermore, a suitable installation location can be selected based on the vehicle's design and actual needs. Generally, it can be installed on the top or rear of the vehicle to ensure good signal transmission and reception. Measuring tools are used to determine the accurate coordinates of the installation location to ensure that the device can meet the positioning requirements after installation.

[0034] Specifically, such as Figure 4 As shown, the specific steps for vehicle positioning based on circularly polarized antennas are as follows: Acquire the UWB transmitted signal of the designated vehicle and the UWB received signal of each circularly polarized antenna; analyze the initial positioning set of each circularly polarized antenna of the designated vehicle, including propagation time and phase angle; based on a pre-trained UWB signal analysis model and combined with the UWB received signal of each circularly polarized antenna of the designated vehicle, analyze the positioning signal feature set of its corresponding circularly polarized antenna, including time delay confidence feature value and azimuth signal feature value; based on the initial positioning set and positioning signal feature set of each circularly polarized antenna of the designated vehicle, analyze the corrected positioning set of its corresponding circularly polarized antenna; based on the corrected positioning set and positioning signal feature set of each circularly polarized antenna of the designated vehicle, analyze the three-dimensional position coordinates of the designated vehicle and upload them to the display panel 10.

[0035] The UWB transmitted signal includes a transmission timestamp and the transmitted amplitude at each time point. The UWB received signal includes a reception timestamp and the received amplitude at each time point. The specific steps for analyzing the initial positioning set of each circularly polarized antenna on the vehicle are as follows: Based on the transmission timestamp of the vehicle and the reception timestamp of each circularly polarized antenna, analyze the propagation time value of the corresponding circularly polarized antenna. Specifically, perform difference processing on the reception timestamp of each circularly polarized antenna and the transmission timestamp to obtain the propagation time value of the corresponding circularly polarized antenna; based on the received amplitude of each circularly polarized antenna at each time point on the vehicle, analyze the propagation time value of the corresponding circularly polarized antenna. The phase angle of the circularly polarized antenna is determined by performing a Fourier transform on the received amplitude of each circularly polarized antenna of the vehicle at each time point (i.e., converting the received amplitude at each time point to the frequency domain based on the Fast Fourier Transform, then selecting the frequency point corresponding to the carrier center frequency in the frequency domain result. The carrier center frequency is determined by the operating frequency band of the UWB transceiver module 5, which can be set in the range of 3.1GHz to 10.6GHz. In this embodiment, 7.25GHz is used as an example for illustration. The complex spectrum value of this frequency point is extracted, and then phase operation is performed on its complex spectrum value) to obtain the phase angle of the corresponding circularly polarized antenna.

[0036] The specific steps for analyzing the location signal feature set of each circularly polarized antenna of the vehicle are as follows: Input the UWB received signal of each circularly polarized antenna of the vehicle into the pre-trained UWB signal analysis model, and analyze the signal evaluation feature set of the corresponding circularly polarized antenna, including energy accumulation feature value, signal envelope stability feature value, channel impulse response clarity feature value, circular polarization feature value, noise correlation feature value, and multipath delay spread feature value.

[0037] Based on the signal evaluation feature set of each circularly polarized antenna of the vehicle, the time delay confidence feature value and azimuth confidence feature value of the corresponding circularly polarized antenna are analyzed. Specifically, the energy concentration feature value, signal envelope stability feature value, and channel impulse response clarity feature value of each circularly polarized antenna of the vehicle are comprehensively analyzed (i.e., weighted processing) to obtain the time delay confidence feature value of the corresponding circularly polarized antenna. Based on the circular polarization feature value, noise-related feature value, and multipath delay spread feature value of each circularly polarized antenna of the vehicle, the azimuth confidence feature value of the corresponding circularly polarized antenna is analyzed (and the circular polarization feature value, noise-related feature value, and multipath delay spread feature value are marked as the azimuth analysis set).

[0038] The specific formula for calculating the azimuth signal characteristic value of a certain circularly polarized antenna of a vehicle is as follows: ;in, To set the azimuth signal characteristic value of a certain circularly polarized antenna of a vehicle, To set the circular polarization characteristic value of a certain circularly polarized antenna of a vehicle, These are the circular polarization adjustment coefficients stored in the database. To determine the noise-related characteristic value of a certain circularly polarized antenna on a vehicle, These are the noise-related adjustment coefficients stored in the database. To define the multipath delay spread characteristic value of a certain circularly polarized antenna of a vehicle, The delay extension adjustment coefficients are stored in the database, and in this embodiment, the circular polarization adjustment coefficients are stored in the database. Noise-related adjustment coefficient Delay expansion adjustment coefficient The values ​​were taken as 0.438, 0.542, and 0.364, respectively. A specific implementation example for calculating the azimuth signal characteristic value of a certain circularly polarized antenna of a vehicle is as follows. The available data includes: the circular polarization characteristic values, noise-related characteristic values, and multipath delay spread characteristic values ​​of the four circularly polarized antennas of the vehicle, as shown in Table 1 and... Figure 5 As shown:

[0039] Table 1. Example of circular polarized antenna sequence data for azimuth analysis of a vehicle.

[0040]

[0041] Circular polarization adjustment coefficients stored in the database The value is: 0.438;

[0042] Noise-related adjustment coefficients stored in the database The value is: 0.542;

[0043] Delay spread adjustment coefficients stored in the database The value is: 0.364;

[0044] Substituting the data from Table 1 and the above example into the specific formula for calculating the azimuth signal characteristic value of a certain circularly polarized antenna of a vehicle, we obtain:

[0045] Set the azimuth signal characteristic value of the vehicle's first circularly polarized antenna to ln(1+(0.853^0.438 / (1+0.542×0.195)))+0.364×exp(-√0.241)≈0.834;

[0046] The azimuth signal characteristic value of the second circularly polarized antenna of the vehicle is set to ln(1+(0.872^0.438 / (1+0.542×0.124)))+0.364×exp(-√0.213)≈0.904;

[0047] The azimuth signal characteristic value of the third circularly polarized antenna of the vehicle is set as ln(1+(0.853^0.438 / (1+0.542×0.283)))+0.364×exp(-√0.342)≈0.728;

[0048] Set the azimuth signal characteristic value of the vehicle's fourth circularly polarized antenna to ln(1+(0.817^0.438 / (1+0.542×0.164)))+0.364×exp(-√0.286)≈0.827.

[0049] In this implementation scheme, the propagation time and phase angle are extracted by comparing the transmitted UWB signal with the received UWB signals of each circularly polarized antenna. This allows the positioning data to have information in both the time and frequency domains, avoiding deviations caused by a single parameter. Secondly, by introducing a pre-trained UWB signal analysis model, the received UWB signal is transformed into signal evaluation features, which are used to generate time delay confidence values ​​and azimuth confidence values. In the corrected positioning set, the initial data and confidence feature values ​​are combined for correction, so that the positioning results can dynamically offset the errors caused by environmental interference and equipment drift. Finally, the corrected data is used for three-dimensional coordinate calculation and output on the display panel. This ensures that the vehicle positioning process not only has strong anti-interference capabilities but also maintains high accuracy in complex environments such as those with significant multipath effects.

[0050] Specifically, such as Figure 6 As shown, the UWB signal analysis model includes a UWB input processing layer for receiving UWB received signals, a UWB feature construction layer for extracting features of the UWB received signals, and a UWB output layer for outputting UWB signal feature values.

[0051] The specific steps for analyzing the signal evaluation feature set of each circularly polarized antenna of the vehicle are as follows: In the UWB input processing layer of the UWB signal analysis model, the UWB received signal of each circularly polarized antenna of the vehicle is received and preprocessed. Specifically, a bandpass filter is used to filter the received signal, retaining only the effective frequency components within the operating frequency band to remove DC drift and out-of-band noise. In the UWB feature construction layer of the UWB signal analysis model, based on the preprocessed UWB received signal of each circularly polarized antenna of the vehicle, the positioning feature vector of the corresponding circularly polarized antenna is extracted. In the WB output layer, based on the positioning feature vector of each circularly polarized antenna of the vehicle, the signal evaluation feature set of its corresponding circularly polarized antenna is output. Specifically, the energy accumulation feature, signal envelope stability feature, channel impulse response clarity feature, circular polarization feature, noise correlation feature, and multipath delay spread feature in the positioning feature vector of each circularly polarized antenna are processed by the Sigmoid function, and the results are mapped between 0 and 1 to obtain the energy accumulation feature value, signal envelope stability feature value, channel impulse response clarity feature value, circular polarization feature value, noise correlation feature value, and multipath delay spread feature value of its corresponding circularly polarized antenna.

[0052] The specific steps for extracting the positioning feature vector of each circularly polarized antenna of the vehicle are as follows: The received amplitude of any circularly polarized antenna at each time point after preprocessing is squared to obtain its corresponding energy value. The instantaneous power values ​​are then accumulated sequentially to form a cumulative energy sequence that increases with time. In this cumulative energy sequence, the point at which the cumulative energy first reaches 10% of the total energy (i.e., the sum of energy values ​​at all time points) is detected and used as the starting point of the main pulse. The point at which the cumulative energy first reaches 80% of the total energy is detected and used as the ending point of the main pulse. The interval between the starting and ending points is defined as the main pulse energy interval. Subsequently, the instantaneous power values ​​at all time points within the main pulse energy interval are integrated to obtain energy concentration characteristics, which characterize the concentration of signal energy on the direct path. When the energy is highly concentrated, the direct path is clear, and the reliability of ToA ranging is high.

[0053] The received amplitude at each time point within the main pulse energy range is read, and the difference between any two adjacent time points is processed (absolute value is taken) to obtain the fluctuation mean. The distribution probability of the received amplitude is statistically analyzed (that is, the received amplitude is divided into several amplitude intervals according to the amplitude size, and the proportion of time points in each amplitude interval is statistically analyzed). The result is analyzed based on the information entropy formula to obtain the received entropy value, and it is weighted with the fluctuation mean. The weighted result is transformed using the reciprocal suppression mapping function f(x)=1 / (1+x), i.e., 1 / (1+the weighted result), to extract the signal envelope stability feature, which is used to characterize the stability of the received amplitude over time within the main pulse energy range. When the envelope stability is high, the time delay boundary can be accurately determined, and the ToA ranging result is more reliable.

[0054] The energy value at each time point is read, the maximum energy value is calculated, and the time point corresponding to the maximum energy value is taken as the peak point. Then, a sampling interval of fixed length is selected before and after the peak point. The energy value of each time point within the sampling interval is read and summed to obtain the first path energy value. The total energy value (i.e., the sum of the energy values ​​of all time points) is calculated. The ratio of the first path energy value to the total energy value is processed to extract the clear characteristics of the channel impulse response. This is used to characterize the prominence of the direct path relative to the multipath path. When the proportion of the first path energy is high, the direct path is significant, the time delay positioning boundary is clear, and the ToA ranging accuracy is high.

[0055] Read the received amplitude at each time point of the preprocessed circularly polarized antenna, and calculate the mean received amplitude, variance received amplitude, maximum received amplitude, and minimum received amplitude respectively. Then, perform ratio processing on each of these ratios, i.e., variance received amplitude / mean received amplitude, (maximum received amplitude / minimum received amplitude) - 1. The ratio processing results are then weighted to extract circular polarization features, which are used to characterize the polarization purity of the received signal. When the polarization purity is high, the circularly polarized antenna can effectively suppress cross-polarization interference, and the signal directivity is more stable, which helps to improve the accuracy of AOA angle calculation.

[0056] The energy value at each time point is read, and the mean energy and standardized deviation of energy at each time point are calculated. Based on this, an energy threshold is set, which is the mean energy - 3 × the standardized deviation of energy. A noise interval is selected where the energy values ​​at several consecutive time points (the number of consecutive time points can be determined by the following steps: the ratio of the number of consecutive time points to the number of time points in the main pulse energy interval exceeds a preset threshold, such as 5%) are lower than the preset energy threshold. Autocorrelation analysis is performed on the energy values ​​at each time point within each noise interval. This involves sequentially shifting the energy sequence along the time axis by different delay steps (delay step refers to shifting the entire sequence by different delay steps when performing correlation calculations). The process involves multiplying the time step by the original energy sequence point by point and summing the results. For example, a delay step of zero indicates complete overlap with the original energy sequence, while a delay step of one indicates comparison with adjacent time points. The autocorrelation values ​​under different delay step lengths are obtained by summing the results after multiplying them point by point with the original energy sequence. The autocorrelation value with a delay step of zero serves as the benchmark. The autocorrelation values ​​under different delay step lengths are then compared with the benchmark. A weighted average is performed based on the ratio results to extract noise correlation features, which characterize the independence of noise components in the received signal. When the feature value is small, it indicates that the noise is approximately white noise, the interference independence is strong, and the AOA solution is more stable.

[0057] The received amplitude of the circularly polarized antenna at each time point is read, and the corresponding received amplitude at each time point is squared to convert the amplitude signal into a power signal, thereby obtaining a power delay sequence that varies with time points (used to characterize the magnitude of the signal energy received at different time points). The power delay sequence is then normalized by dividing the power value at each time point by the sum of the power values ​​at all time points, thus obtaining the proportion of the power value at each time point to the total received energy (i.e., the power distribution ratio), which reflects the probability of signal energy distribution on the time axis. Based on the above power distribution probability, the average delay position of the received signal on the time axis is calculated, specifically as follows:

[0058] The sampling time at each time point is multiplied by the power distribution ratio at that time point, and the products of all time points are accumulated to obtain the average delay value, which reflects the concentration trend of signal energy in the time distribution. The offset (absolute value) of each time point relative to the average delay position is analyzed, and the square of the offset is multiplied by the power distribution ratio and accumulated. The square root of the accumulated result is then taken to extract the multipath delay spread feature, which reflects the broadening of the received signal on the time axis. When this feature is small, it indicates that the received signal energy is mainly concentrated in the direct path, the energy in the reflection path is weak, and the multipath effect is slight. When this feature is large, it indicates that the received signal energy is distributed at multiple time delay points, the energy in the reflection path is significant, the multipath effect is serious, and the accuracy of the positioning result decreases. The energy concentration feature, signal envelope stability feature, channel impulse response clarity feature, circular polarization feature, noise correlation feature, and multipath delay spread feature are concatenated into a positioning feature vector.

[0059] The pre-training steps for the UWB signal parsing model are as follows:

[0060] A labeled dataset is obtained, consisting of multiple sets of UWB received signals collected under typical vehicle operating environments. Each set of samples includes the received amplitude sequence, received timestamp, and corresponding real location labels for different circularly polarized antennas in multiple consecutive time periods. The real location labels are labeled by a high-precision reference positioning system (such as a high-precision GNSS / RTK or laser ranging device) to ensure that the dataset has reliable supervision signals. Subsequently, the raw data is preprocessed, including signal normalization, bandpass filtering to remove out-of-band noise, and amplitude standardization, to reduce the impact of environmental differences on model training. After processing, the labeled dataset is divided into training set, validation set, and test set according to the proportion, for example, 80% as training set, 10% as validation set, and 10% as test set.

[0061] Secondly, the training set samples are input into the UWB signal analysis model. The model sequentially passes through the UWB input processing layer, the UWB feature construction layer, and the UWB output layer. In the input processing layer, the model performs preprocessing simulation on the signal to simulate the filtering and denoising process at the actual receiver. In the feature construction layer, the model extracts energy aggregation features, signal envelope stability features, channel impulse response clarity features, circular polarization features, noise correlation features, and multipath delay spread features through convolutional networks or fully connected networks. In the output layer, the model performs nonlinear mapping and normalization on the above features to obtain the corresponding feature values, which are then compared with the labeled real labels.

[0062] Furthermore, during training, by setting a loss function (such as mean squared error MSE or cross-entropy loss) and using optimization algorithms (such as Adam optimizer or stochastic gradient descent) to continuously adjust the model weights, the backpropagation mechanism is used to gradually reduce the difference between the predicted results and the true labels. The training process is evaluated in real time and hyperparameters are adjusted, including learning rate, batch size, network depth, etc., through the validation set to ensure that the model has good generalization ability in different scenarios.

[0063] Finally, after the model training converges, the model performance is evaluated using a test set. Evaluation metrics include the accuracy, stability, and noise resistance of the localization feature extraction. This ensures that the model can still output effective signal evaluation feature values ​​in complex, unseen scenarios. The trained UWB signal parsing model will be saved, and its parameters can be directly used in the real-time localization analysis stage of the vehicle, providing reliable support for the subsequent generation of corrected localization sets.

[0064] In this implementation scheme, a pre-trained UWB signal analysis model is used to analyze the received UWB signal, which can significantly improve the accuracy of the positioning process. For example, energy concentration features can reflect the concentration of energy along the direct path. When the feature value is high, it indicates that the direct path is clear and the boundary of the propagation time is easy to determine, thus making the time delay ranging results more reliable. Secondly, in this process, it can simultaneously evaluate key features such as multipath broadening and polarization purity. Based on multi-feature fusion, a correlation between signal quality and positioning accuracy is established, which enables the dynamic identification of reliable paths and suppression of interference components during the positioning analysis process, thereby improving the reliability of propagation time and angle of arrival calculation. Finally, a labeled dataset containing real positioning labels is constructed, and deep training is performed in combination with multi-dimensional signal features. The model can fully learn the signal variation patterns under different environments, thereby effectively improving the accuracy of feature extraction. After evaluation on the validation set and test set, the model's generalization ability in complex scenarios is guaranteed, thus providing reliable data support for vehicle positioning.

[0065] Specifically, the steps for analyzing the corrected positioning set of each circularly polarized antenna of the designated vehicle are as follows: Obtain the vehicle speed value (based on the vehicle speed sensor) and the temperature value of the UWB transceiver module 5 (based on the thermometer 7), and combine this with the time delay confidence characteristic value and propagation duration value of each circularly polarized antenna to analyze the corresponding propagation correction value. Specifically, based on the temperature value of the UWB transceiver module 5 of the designated vehicle and the temperature drift duration mapping table stored in the database (during the deployment phase, experimental calibration is performed on the operating characteristics of the crystal oscillator inside the UWB transceiver module 5 at different temperatures, converting the frequency offset at each temperature into a propagation duration deviation value, and storing it in the database to form a temperature drift duration mapping table), read the temperature drift duration value of the designated vehicle (if the temperature value is not within the temperature drift time...). On the long mapping table, interpolation algorithms are used to calculate the drift duration at a given temperature between adjacent temperature points in the database. Based on the vehicle speed and the electromagnetic wave propagation speed stored in the database, the vehicle speed drift duration is analyzed, i.e., (vehicle speed × propagation duration) / electromagnetic wave propagation speed. The time delay confidence feature value of each circularly polarized antenna is processed by the tanh function (mapping the result to between 0 and 1). Based on the time delay confidence feature value of each circularly polarized antenna after the tanh function processing, as well as the propagation duration, temperature drift duration, and vehicle speed drift duration, a comprehensive analysis is performed, i.e., (propagation duration - temperature drift duration - vehicle speed drift duration) × the time delay confidence feature value after the tanh function processing, to obtain the propagation correction value of the corresponding circularly polarized antenna.

[0066] Based on the azimuth signal characteristic value and phase angle of each circularly polarized antenna of the vehicle, the phase correction angle of the corresponding circularly polarized antenna is analyzed. Specifically, the azimuth signal characteristic value of each circularly polarized antenna of the vehicle is processed by the tanh function, and the azimuth signal characteristic value of each circularly polarized antenna after the tanh function processing is combined with the phase angle for comprehensive analysis, that is, phase angle × azimuth signal characteristic value after tanh function processing, so as to obtain the phase correction angle of the corresponding circularly polarized antenna.

[0067] In this implementation scheme, a joint correction method based on temperature, vehicle speed, and confidence features is introduced to ensure that the positioning process fully considers the impact of the dynamic environment on signal propagation characteristics during vehicle operation. Specifically, the temperature drift correction part uses a mapping table established during the deployment phase to quantify the frequency offset of the crystal oscillator at different temperatures into a correction value for the propagation time, and flexibly calls it in the application through interpolation, thereby effectively eliminating errors caused by temperature fluctuations. The vehicle speed correction part utilizes the relationship between vehicle speed and propagation time to convert the Doppler effect under motion into a quantifiable drift time value, achieving dynamic compensation for the propagation path under high-speed conditions. In addition, by performing nonlinear function processing on the time delay confidence feature value and the azimuth confidence feature value, low-confidence data can be filtered out, making the correction results more robust. Ultimately, this step not only improves the accuracy of propagation time and phase angle, but also significantly enhances the reliability of positioning in complex environments, enabling it to obtain high-precision positioning results even in complex environments.

[0068] Specifically, such as Figure 7 As shown, the specific steps for analyzing and setting the three-dimensional position coordinates of the vehicle are as follows: Obtain the three-dimensional position coordinates of each circularly polarized antenna of the vehicle (the antenna three-dimensional position coordinates are defined based on the vehicle body coordinate system, where the origin of the vehicle body coordinate system is set at the vehicle's geometric center, the X-axis is along the vehicle's forward direction, the Y-axis is along the vehicle's lateral direction pointing to the driver's left, and the Z-axis is vertically upward). Combined with the phase correction angle, analyze the angle of arrival of several pairs of circularly polarized antennas of the vehicle. Specifically: Read the phase correction angle values ​​of each circularly polarized antenna of the vehicle, and perform differential processing on any pair of circularly polarized antenna pairs to obtain several sets of circularly polarized antennas. The phase correction angle difference of the circularly polarized antenna pair (expressed in radians, and this value is the value after phase expansion processing to limit it to the range of [−π, π]) is analyzed based on the Euclidean distance formula to obtain the distance value of the corresponding circularly polarized antenna pair. The electromagnetic wave propagation speed value stored in the database and the carrier center frequency of the vehicle are read and comprehensively analyzed, i.e., [arcsin(electromagnetic wave propagation speed value × phase correction angle difference value) / (2 × π × distance value × carrier center frequency)], to obtain the angle of arrival of each circularly polarized antenna pair.

[0069] Based on the three-dimensional position coordinates, propagation correction values, and location signal feature sets of each circularly polarized antenna of the vehicle, and combined with the angle of arrival of each pair of circularly polarized antennas, a weighted least squares equation system for the vehicle is constructed and iteratively solved to obtain the three-dimensional position coordinates of the vehicle body. The specific steps are as follows:

[0070] Assuming the three-dimensional position coordinates of the vehicle body (in the vehicle body coordinate system) are the points to be determined (unknown, to be solved), Euclidean distance analysis is performed between these points and the three-dimensional position coordinates of each circularly polarized antenna to obtain the propagation distance value from the points to be determined of the vehicle body to each circularly polarized antenna (unknown, to be solved). Then, using the propagation correction value of each circularly polarized antenna and the electromagnetic wave propagation speed value stored in the database, a propagation time residual function for each circularly polarized antenna is constructed, specifically as follows: ,in, To set the vehicle's pending point to the 1st The propagation distance of a circularly polarized antenna. To set the vehicle's first Propagation correction value for a circularly polarized antenna, The electromagnetic wave propagation speed value stored in the database. =1, 2, 3, ... , The number of circularly polarized antennas is given. Based on the cosine function relationship, the three-dimensional position coordinates of the undetermined point of the vehicle and the two circularly polarized antennas in each pair are analyzed to determine the reference angle of arrival from the undetermined point of the vehicle to each pair of circularly polarized antennas. The angle of arrival residual function of each pair of circularly polarized antennas is constructed with the angle of arrival of each pair of circularly polarized antennas. Specifically: in, To set the vehicle's pending point to the 1st The reference angle of arrival for a pair of circularly polarized antennas. To set the vehicle's first Angle of arrival for a circularly polarized antenna. =1, 2, 3, ... , This represents the number of circularly polarized antenna pairs.

[0071] Read the time delay confidence feature value of each circularly polarized antenna of the designated vehicle, and sum them to obtain the time delay confidence feature sum value of the designated vehicle. Then, compare the time delay confidence feature value of each circularly polarized antenna with the time delay confidence feature sum value, and use the result as the propagation weight value of the propagation time residual function of the corresponding circularly polarized antenna.

[0072] The azimuth signal characteristic values ​​of the two circularly polarized antennas in each pair of circularly polarized antennas of the specified vehicle are read and averaged to obtain the mean azimuth signal characteristic value of each pair of circularly polarized antennas of the specified vehicle. The mean azimuth signal characteristic value of each pair of circularly polarized antennas is then summed to obtain the sum of azimuth signal characteristic values ​​of the specified vehicle. The mean azimuth signal characteristic value of each pair of circularly polarized antennas is then compared with the sum of azimuth signal characteristic values ​​to obtain the arrival weight value of the arrival angle residual function of the corresponding pair of circularly polarized antennas.

[0073] Based on the propagation time residual function and corresponding propagation weight value of each circularly polarized antenna, and the arrival angle residual function and corresponding arrival weight value of each pair of circularly polarized antennas, a weighted least squares equation system is constructed, which is as follows: ;in, For the first The propagation weight values ​​corresponding to the propagation time residual function of each circularly polarized antenna. For the first The arrival weight value corresponding to the arrival angle residual function of the circularly polarized antenna pair;

[0074] The weighted least squares equations can be solved iteratively using the Gauss-Newton method or the Levenberg-Marquardt method until they converge to a preset minimum value. The result is the undetermined point of the vehicle, i.e., the three-dimensional position coordinates of the vehicle body.

[0075] The three-dimensional position coordinates of the vehicle body are transformed to obtain the three-dimensional position coordinates of the vehicle body. The specific steps are as follows: Obtain the three-dimensional coordinates of the reference positioning point of the vehicle body in the global geographic coordinate system. The global geographic coordinate system can be the East-North-Sky (ENU) coordinate system, where the east direction is the X-axis, the north direction is the Y-axis, and the vertical upward is the Z-axis. The three-dimensional coordinates of the reference positioning point can be output in real time by GNSS and used as the translation reference of the vehicle body as a whole. Obtain the heading angle, pitch angle, and roll angle of the vehicle body (all of which can be obtained through the on-board inertial measurement unit IMU). Based on the above heading angle, pitch angle, and roll angle, construct a rotation matrix from the vehicle body coordinate system to the ENU coordinate system. Substitute the three-dimensional position coordinates of the vehicle body into the rotation matrix to obtain its relative three-dimensional coordinates in the ENU coordinate system. Translate and superimpose these coordinates with the three-dimensional coordinates of the reference positioning point to obtain the three-dimensional position coordinates of the vehicle body in the global ENU coordinate system.

[0076] In this implementation scheme, by combining the antenna's three-dimensional position coordinates, phase correction angle, and multi-dimensional feature weights, the positioning accuracy is significantly improved. When constructing the weighted least squares equation system, not only are the residuals of the corrected propagation value and angle of arrival considered, but each constraint is also assigned a weight based on confidence features. This allows high-confidence observation data to occupy a larger proportion in the solution, while the influence of low-confidence data is effectively weakened. This avoids the deviation of abnormal data from the final solution result. At the same time, by introducing iterative optimization methods such as the Gauss-Newton method or the Levenberg-Marquardt method, the equation system can quickly converge to the optimal solution, ensuring computational efficiency. Finally, through a coordinate transformation step, the result in the vehicle coordinate system is accurately mapped to the global ENU coordinate system, thereby realizing a unified positioning output for the vehicle in the actual geographical environment. This ensures that the vehicle can still output reliable positioning results when facing situations such as signal fading.

[0077] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0078] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna, comprising: The substrate (1) and the radiating layer (2), and the feed layer (3) located below the radiating layer (2), wherein the radiating layer (2) is mounted on the bottom of the substrate (1), characterized in that it further comprises: The feed layer (3) is equipped with a circularly polarized antenna array at one end near the radiation layer (2), and the vehicle positioning is based on the circularly polarized antenna. A metal shielding layer (4) for isolating external interference is provided below the feed layer (3). A UWB transceiver module (5) is installed below the shielding layer (4), and a timestamp controller (6) is installed inside the UWB transceiver module (5). The specific steps for vehicle positioning based on a circularly polarized antenna are as follows: Acquire the UWB transmit signal of the designated vehicle and the UWB receive signal of each circularly polarized antenna, and analyze the initial positioning set of each circularly polarized antenna of the designated vehicle, including the propagation duration value and phase angle; Based on a pre-trained UWB signal analysis model and combined with the UWB received signals of each circularly polarized antenna of the vehicle, the location signal feature set of the corresponding circularly polarized antenna is analyzed, including time delay confidence feature values ​​and azimuth signal feature values, i.e.: The UWB received signal is input into a pre-trained UWB signal analysis model to analyze the signal evaluation feature set of its corresponding circularly polarized antenna, including energy accumulation feature value, signal envelope stability feature value, channel impulse response clarity feature value, circular polarization feature value, noise correlation feature value, and multipath delay spread feature value. Based on the signal evaluation feature set, analyze the time delay confidence feature value and azimuth confidence feature value of the corresponding circularly polarized antenna; Based on the initial positioning set and positioning signal feature set of each circularly polarized antenna of the vehicle, the corrected positioning set of the corresponding circularly polarized antenna is analyzed. Based on the corrected positioning set and positioning signal feature set of each circularly polarized antenna of the vehicle, the three-dimensional position coordinates of the vehicle are analyzed and uploaded to the display panel (10), that is: Obtain the vehicle speed and the temperature of the UWB transceiver module; Based on the time delay confidence feature value, the propagation duration value is jointly corrected with respect to the temperature value and the vehicle speed value to obtain the propagation correction value; Based on the position information feature value, the phase angle is corrected to obtain the phase correction angle; Based on the three-dimensional position coordinates of each circularly polarized antenna, the propagation correction value, and the phase correction angle, a weighted least squares equation system is constructed, wherein the weights of the equation system are determined based on the time delay confidence feature value and the azimuth confidence feature value.

2. The vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to claim 1, characterized in that, The UWB transceiver module (5) is equipped with a thermometer (7), whose output end is electrically connected to a temperature display bar (8) installed at the bottom of the UWB transceiver module (5). A sealing strip (9) is provided at the joint between the UWB transceiver module (5) and the shielding layer (4). A sealing plate (14) is provided inside the UWB transceiver module (5).

3. The vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to claim 1, characterized in that, The front end of the substrate (1) is equipped with a display panel (10), and a status light strip (11) for displaying the operating status of the positioning device is provided on its front side. The bottom of the shielding layer (4) is symmetrically provided with a locking block (12), and the locking block (12) is elastically connected to the shielding layer (4) by a spring (13).

4. The vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to claim 1, characterized in that, The UWB transmitted signal includes a transmission timestamp, and the UWB received signal includes a reception timestamp and the received amplitude at each time point. The specific steps for analyzing and setting the initial positioning set for each circularly polarized antenna of the vehicle are as follows: Based on the vehicle's transmission timestamp and the reception timestamp of each circularly polarized antenna, the propagation duration of the corresponding circularly polarized antenna is analyzed. Based on the received amplitude of each circularly polarized antenna of the vehicle at each time point, the phase angle of the corresponding circularly polarized antenna is analyzed.

5. The vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to claim 3, characterized in that, The specific steps for analyzing and setting the location signal feature set of each circularly polarized antenna of the vehicle are as follows: The UWB received signal of each circularly polarized antenna of the vehicle is input into the pre-trained UWB signal analysis model to analyze the signal evaluation feature set of the corresponding circularly polarized antenna, including energy accumulation feature value, signal envelope stability feature value, channel impulse response clarity feature value, circular polarization feature value, noise correlation feature value, and multipath delay spread feature value. Based on the signal evaluation feature set of each circularly polarized antenna of the vehicle, the time delay confidence feature value and azimuth confidence feature value of the corresponding circularly polarized antenna are analyzed.

6. The vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to claim 4, characterized in that, The UWB signal analysis model includes a UWB input processing layer for receiving UWB signals, a UWB feature construction layer for extracting features of the received UWB signals, and a UWB output layer for outputting UWB signal feature values.

7. The vehicle-mounted UWB-AOA circularly polarized high-precision positioning antenna according to claim 5, characterized in that, The specific steps for analyzing and defining the signal evaluation feature set of each circularly polarized antenna of the vehicle are as follows: In the UWB input processing layer of the UWB signal analysis model, the UWB received signal of each circularly polarized antenna of the vehicle is received and preprocessed. In the UWB feature construction layer of the UWB signal analysis model, the positioning feature vector of the corresponding circularly polarized antenna is extracted based on the preprocessed UWB received signal of each circularly polarized antenna of the vehicle. In the UWB output layer of the UWB signal analysis model, based on the positioning feature vector of each circularly polarized antenna of the vehicle, the signal evaluation feature set of its corresponding circularly polarized antenna is output.

Images