Mobile RSU intelligent detection device and method

Abstract

The invention provides mobile RSU intelligent detection equipment and a mobile RSU intelligent detection method. The main control module is used for receiving and processing data information and serves as a data acquisition server, and the omnidirectional antenna is used for receiving broadcast electromagnetic signals of a roadside unit at a toll station lane or a highway portal; the spectrum analysis module is connected with the omnidirectional antenna and the main control module and is used for performing spectrum analysis on the received frequency band signal; the positioning and attitude determination module is in communication connection with the main control module and is used for acquiring the real-time position and attitude information of the equipment; and the moving speed detection module is connected with the main control module and is used for detecting the moving speed of the equipment and carrying out auxiliary correction on the data of the positioning and attitude determination module. The master control module, the spectrum analysis module, the omnidirectional antenna and the like are integrated on the mobile carrier, so that mobile detection of RSU equipment along a highway is realized, and the problems of limited coverage range of fixed detection equipment and low manual inspection efficiency are solved.

Description

Technical Field

[0001] This invention belongs to the technical field of highway toll collection, specifically relating to a mobile RSU intelligent detection device and method. Background Technology

[0002] The ETC system is a core infrastructure to ensure the efficient and smooth operation of the highway network. The roadside unit (RSU) is a key device for communication between the ETC system and the on-board unit (OBU). The stability of its working status, the quality of the communication signal, and the accuracy of its coverage are directly related to the success or failure of toll transactions and the efficiency of road traffic.

[0003] Currently, the inspection and maintenance of ETC-RSU equipment on highways mainly rely on the following two methods: I. Fixed Inspection Equipment: This type of equipment is typically pre-installed in specific locations such as toll lanes or gantries, enabling automated inspection of RSUs in fixed areas. However, it has significant limitations: First, its coverage is limited, making it unable to flexibly inspect all RSUs along the entire route, especially those not at pre-set inspection points; second, it lacks flexibility, failing to address temporary fault diagnosis or inspection needs arising from changes in the road network structure; and third, it has high construction costs, requiring deployment at every critical point.

[0004] II. Manual Inspection Method: Technicians carry portable testing instruments to the site to conduct individual inspections of the equipment. While this method offers some flexibility, its drawbacks are more pronounced: First, the inspection efficiency is extremely low, time-consuming and labor-intensive, making it difficult to meet the rapid inspection needs of a large-scale road network nationwide; second, the inspection results are easily affected by human factors, as different technicians' skill levels and judgment standards may lead to poor data consistency; third, it is unsafe and disruptive to traffic, as inspections often need to be conducted on the driving lanes, posing a threat to the personal safety of technicians and usually requiring temporary lane closures or traffic diversions, thus disrupting normal traffic flow and exacerbating congestion.

[0005] Therefore, there is a need to provide an improved technical solution that addresses the shortcomings of the existing technology. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art. This invention provides a mobile RSU intelligent inspection device and method.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A mobile RSU intelligent inspection device, the inspection device comprising: The main control module is used to receive and process data information, and as a data acquisition server, it provides control interface services and data query interface services to external acquisition software. An omnidirectional antenna is used to receive broadcast electromagnetic signals from roadside units at toll booth lanes or highway gantry locations and provide them to a spectrum analysis module for analysis. A spectrum analysis module, connected to the omnidirectional antenna and the main control module, is used to perform spectrum analysis on the received frequency band signals; The positioning and attitude determination module is communicatively connected to the main control module, used to acquire the real-time position and attitude information of the device and provide GPS satellite timing signals; The movement speed detection module, connected to the main control module, is used to detect the movement speed of the device and to assist in correcting the data from the positioning and attitude determination module.

[0008] Preferably, the main control module is equipped with data monitoring and analysis software to comprehensively collect radio frequency analysis data from the spectrum analyzer, real-time position and attitude information from the positioning and attitude determination module, GPS timing signals, and digital information on the movement of the detection equipment. Through a multi-data coupled field strength analysis algorithm, the software enables the drawing of the RSU field strength distribution map and the extraction of key detection information.

[0009] Preferably, the multivariate data coupled field strength analysis algorithm adopts multi-channel data denoising and interpolation methods, and introduces multi-resolution wavelet packet denoising and robust principal component analysis to decompose low-rank background and sparse anomalies. Combined with time-frequency domain synchronous sparse representation, it improves the ability to suppress impulse noise and quantization noise. For data points with abnormally high variation values, the structured predicted values ​​of the surrounding ±2 peak points are compared. Gaussian process regression or edge-preserving bilateral filtering is used to repair neighborhood consistency. If the deviation value exceeds the set threshold, the current peak point is removed and replaced with the reconstructed mean of the surrounding ±2 peak points. Based on the spatial electromagnetic wave propagation field strength attenuation formula and cubic spline interpolation method, the spatial distribution density of the overall data is supplemented, and lightweight ray tracing prior data is introduced to focus on characterizing shadow fading and multipath structure. Based on the free-space propagation loss model, a multi-state hybrid path loss model is adopted to improve the adaptability to complex road environments by estimating the path loss index and shadow fading standard deviation online. By integrating high-precision GPS information, the field strength coupling and smoothing prior are finally characterized on the spatial map, thereby forming the field strength distribution data of the required area point by point, and drawing a complete and smooth RSU field strength distribution map.

[0010] Preferably, the testing device further includes a power supply module, which is connected to the main control module and uses an AC / DC conversion unit to supply power to the testing device through an external AC power supply.

[0011] Preferably, the positioning and attitude determination module includes an RTK unit and a MENS integrated inertial navigation unit, and the MENS integrated inertial navigation unit is communicatively connected to the main control module; The RTK unit is communicatively connected to the MEMS integrated inertial navigation unit, which is connected to at least one mushroom-shaped antenna.

[0012] Preferably, there are multiple spectrum analysis modules, each connected to the main control module via an Ethernet interface, for the purpose of synchronous acquisition of multi-channel radio frequency signals.

[0013] Preferably, the detection device also includes a video monitor, which is connected to the main control module via an Ethernet interface, for real-time monitoring of the surrounding environment of the device and acquisition of video data.

[0014] Preferably, the main control module is an industrial control computer.

[0015] Preferably, the moving speed detection module is a ground speed radar, which is connected to the main control module through a conversion module. The conversion module is used to convert between the RS485 protocol and the interface protocol of the main control module.

[0016] A mobile RSU intelligent detection method, which performs monitoring using any of the above-mentioned detection devices, is characterized by comprising the following steps: Step S1: Receive signals from the RSU device via an omnidirectional antenna; Step S2: Perform spectrum analysis on the received signal using the spectrum analysis module to obtain signal quality parameters including antenna field strength, frequency, and occupied bandwidth. Step S3: Correction is performed based on the positioning and attitude determination module, and the geographical location and attitude data of the device are obtained in real time. Step S4: The moving speed data of the device is acquired in real time through the moving speed detection module and transmitted to the positioning and attitude determination module for compensation to assist in correction; Step S5: The main control module receives and integrates the signal quality parameters, geographical location data, attitude data, and movement speed data, performs corresponding matching between signal quality parameters and location information, and collects basic information of the toll station / gantry equipment.

[0017] Beneficial effects: By integrating the main control module, spectrum analysis module, omnidirectional antenna, etc. on a mobile carrier, mobile detection of RSU equipment along highways is realized, overcoming the problems of limited coverage of fixed detection equipment and low efficiency of manual inspection. It can quickly detect multiple long-distance RSUs while in motion, thus improving detection efficiency. Attached Figure Description

[0018] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. Wherein: Figure 1 This is a schematic diagram of the structural connection of the monitoring device in a specific embodiment of the present invention; Figure 2 This is a schematic diagram of the installation of the ground speed radar in a specific embodiment provided by the present invention; Figure 3 This is a schematic diagram of the installation of the omnidirectional antenna and inertial navigation unit in a specific embodiment provided by the present invention; Figure 4 The flowchart for data acquisition, monitoring, and algorithm processing is provided in a specific embodiment of the present invention.

[0019] In the diagram: 1. Trailer arm; 2. Ground speed radar; 3. Omnidirectional antenna; 4. Mushroom-shaped antenna. Detailed Implementation

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention are within the scope of protection of the present invention.

[0021] In the description of this invention, the terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," and "bottom," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and do not require the invention to be constructed and operated in a specific orientation; therefore, they should not be construed as limitations on the invention. The terms "connected" and "linked" used in this invention should be interpreted broadly. For example, they can refer to a fixed connection or a detachable connection; they can refer to a direct connection or an indirect connection through intermediate components. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0022] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0023] Roadside Units (RSUs) are part of the ETC system, installed on the roadside and using DSRC (Dedicated Short Range Communication) technology to communicate with Onboard Units (OBUs) for vehicle identification and electronic point deduction. This application provides a mobile intelligent RSU detection device and method for rapid detection of roadside units.

[0024] like Figure 1-4 As shown, the detection equipment includes a main control module, an omnidirectional antenna 3, a spectrum analysis module, a positioning and attitude determination module, and a movement speed detection module. The main control module is used to receive and process data information and acts as a data acquisition server, providing control interface services and data query interface services to external acquisition software. The main control module is preferably an industrial control computer, which can be connected to other parts through expansion interfaces to meet the real-time processing needs of multi-dimensional data.

[0025] The omnidirectional antenna 3 is a 5.8G omnidirectional antenna used to receive signals from the roadside units (RSUs) of tollbooth lanes or highway gantries, and to provide the collected electromagnetic signals broadcast by the RSUs to the spectrum analysis module for analysis. The omnidirectional antenna 3 has a 360° signal reception capability, which can ensure that the electromagnetic signals broadcast by the RSU devices are fully captured, avoiding detection omissions due to signal reception angle issues.

[0026] The spectrum analysis module connects to the omnidirectional antenna 3 and the main control module. It performs spectrum analysis on the received frequency band signals, extracting key signal quality parameters such as antenna field strength, frequency, and occupied bandwidth, and transmits the analysis results to the main control module. To achieve synchronous acquisition of multi-channel RF signals and improve the comprehensiveness and efficiency of signal acquisition, multiple spectrum analysis modules can be configured. These modules are connected to the main control module via Ethernet interfaces, ensuring data transmission stability and real-time performance. This allows for accurate assessment of the quality and stability of the RSU's transmitted signals, timely detection of potential signal interference or faults, and provides a reliable basis for RSU performance evaluation, improving detection precision and accuracy.

[0027] The positioning and attitude determination module communicates with the main control module to obtain the real-time position and attitude information of the device and provide GPS satellite timing signals to provide accurate timestamps and position references for the detection data. Combined with the spectrum analysis results, the main control module can more comprehensively and accurately understand the signal performance of the RSU device in different positions and under different motion states.

[0028] The movement speed detection module is connected to the main control module to detect the movement speed of the device in real time and transmit the detected movement speed data to the positioning and attitude determination module to assist in the correction of the data from the positioning and attitude determination module and improve the accuracy of the positioning and attitude determination data.

[0029] By integrating the main control module, spectrum analysis module, and 5.8G omnidirectional antenna 3 onto a mobile carrier (such as a car or drone, preferably a car), mobile detection of RSU equipment along highways is achieved. This overcomes the limitations of fixed detection equipment in terms of coverage and the low efficiency of manual inspection, enabling rapid detection of multiple RSUs along long road sections while in motion, thus improving detection efficiency.

[0030] In one optional embodiment, the main control module is equipped with data monitoring and analysis software, which can analyze the collected data returned by the spectrum analyzer, extract and display the frequency energy distribution, data center frequency, and occupied bandwidth. At the same time, it binds the field strength data at the test frequency with high-precision position information, thereby comprehensively collecting the radio frequency analysis data of the spectrum analyzer, the real-time position and attitude information of the positioning and attitude determination module, the GPS timing signal and the digital information of the movement of the detection equipment. Through a multi-data coupled field strength analysis algorithm, it realizes the drawing of the RSU field strength distribution map and the extraction of the main detection information.

[0031] For field strength data bound to high-precision time-series information, multi-channel data denoising and interpolation methods are adopted, and multi-resolution wavelet packet denoising and robust principal component analysis (RPCA) are introduced to decompose low-rank background and sparse anomalies. Combined with time-frequency domain synchronous sparse representation, the ability to suppress impulse noise and quantization noise is improved. For data points with abnormally high variation values, the structured predicted values ​​of the surrounding ±2 peak points are compared. Gaussian process regression (GPR) or edge-preserving bilateral filtering is used to repair neighborhood consistency. If the deviation value exceeds the set threshold, the current peak point is removed and replaced with the reconstructed mean of the surrounding ±2 peak points.

[0032] Based on the spatial electromagnetic wave propagation field strength attenuation formula and cubic spline interpolation method, the spatial distribution density of the overall data is supplemented, and lightweight ray tracing prior data is introduced to focus on characterizing shadow fading and multipath structure. On the basis of the free space propagation loss model, a multi-state hybrid path loss model is adopted to improve the adaptability to complex road environments by estimating the path loss exponent and shadow fading standard deviation online. At the same time, high-precision GPS information is integrated to finally characterize the field strength coupling and smoothing prior on the spatial map, thereby forming the field strength distribution data of the required area point by point, and drawing a complete and smooth RSU field strength distribution map.

[0033] The specific steps are as follows: Based on the field strength data bound to high-precision time-series information and high-precision positioning information, three or more linear detection data distribution maps are formed according to the 5.8GHz antenna distribution. During the data spectrum formation process, multi-channel adaptive noise reduction and anomaly pre-screening are performed simultaneously to suppress impulse noise and quantization error. Combined with peak finding and change point detection, abrupt sample changes are labeled to ensure that the linear detection trajectory maintains continuity and consistency in space and time.

[0034] For multiple linear detection data, the attenuation trend of RSU broadcast signal field strength is simulated according to the radio wave free space propagation loss attenuation curve. The cubic spline interpolation method is used to supplement the transverse spatial field strength data between detection lines. To improve the fitting reliability in complex environments, a LOS / NLOS hybrid path loss model and lightweight ray tracing prior are introduced to correct the path loss exponent and shadow fading parameters online. Constrained splines or thin plate splines are used in boundary and obstacle regions to avoid false smoothing across obstacles.

[0035] Furthermore, based on the supplemented data, an RSU field strength distribution map is drawn, outputting a complete, smooth coverage map with uncertainty annotations. Based on the drawn image, indices such as average field strength, field strength center, maximum field strength, and field strength width are calculated, and the evaluation system is expanded to include morphological and topological indices such as equivalent coverage area, 95% quantile coverage, and number of connected components. In high-density multipath regions, confidence intervals and quality labels are attached to the indices for conservative planning and redundancy calculation on the engineering side.

[0036] Field strength contour maps can intuitively display the intensity distribution of RSU signals in different geographical locations. Through the density and numerical changes of contour lines, the coverage area, transition zone, and weak field areas are clearly presented. On this basis, an RSU operating condition distribution map is overlaid to show the working status of RSU equipment in different geographical locations (online / offline, power offset, radiation pattern deviation, link quality level), and anomaly coloring and alarms are realized by combining historical baselines. Through the combined view, inspection personnel can quickly locate weak coverage areas and abnormal operating condition points, prioritize retesting and maintenance, and form an integrated closed loop from field strength distribution to operation and maintenance decision-making.

[0037] In an optional embodiment, the testing equipment further includes a power supply module connected to the main control module. The power supply module uses an AC / DC conversion unit to supply power to the testing equipment through an external AC power source, ensuring stable operation of the entire testing equipment during the testing process.

[0038] The positioning and attitude determination module includes an RTK unit and a MENS integrated inertial navigation unit, which is communicatively connected to the main control module. Through the collaborative work of the RTK unit and the MEMS integrated inertial navigation unit, high-precision positioning and attitude determination can be achieved, ensuring the accuracy of position and attitude data even in complex environments such as obstruction or weak signals. The RTK unit and the MEMS integrated inertial navigation unit are communicatively connected, and the MENS integrated inertial navigation unit is connected to at least one mushroom-shaped antenna 4. The mushroom-shaped antenna 4 has excellent satellite signal reception capabilities, which can further improve the accuracy and stability of positioning and attitude determination.

[0039] Furthermore, there are multiple spectrum analysis modules, each of which can be connected to the main control module via an Ethernet interface to achieve synchronous acquisition of multi-channel radio frequency signals. This enables the device to simultaneously detect multiple signal channels in different frequency bands or within the same frequency band.

[0040] Each spectrum analysis module connects to the main control module via an Ethernet interface to achieve synchronous acquisition of multi-channel radio frequency signals. Compared to a single spectrum analysis module, this significantly expands the detection frequency range and signal coverage. For example, in complex electromagnetic environments, there may be multiple Roadside Unit (RSU) signals at different frequencies, as well as other interference signals. Multiple spectrum analysis modules can simultaneously acquire and analyze these signals, providing a comprehensive understanding of the on-site radio frequency signal conditions without missing any critical information.

[0041] Furthermore, the testing equipment also includes a video monitor, which is connected to the main control module via an Ethernet interface. This monitor is used to monitor the surrounding environment of the equipment in real time and acquire video data, which can help staff understand the situation at the testing site and promptly identify and handle any abnormal problems that occur during the testing process.

[0042] Preferably, the moving speed detection module is a ground speed radar 2, which is fixed to the trailer interface at the rear of the vehicle via a trailer bar 1, and the ground speed radar 2 forms a 35° angle with the ground.

[0043] Ground speed radar 2, also known as Doppler navigation radar or airborne deflection ground speed radar 2, is an autonomous navigation device that uses the Doppler effect to measure the flight speed of an aircraft. It has the advantages of high detection accuracy and strong anti-interference ability, and can accurately obtain the real-time moving speed of the device.

[0044] The ground speed radar 2 is connected to the main control module through a conversion module. The conversion module is used to convert between the RS485 protocol and the main control module interface protocol to ensure normal data transmission between the ground speed radar 2 and the main control module.

[0045] In another optional embodiment, this application also provides a mobile RSU intelligent detection method, which performs monitoring through any of the above-mentioned detection devices, specifically including the following steps: Step S1: Receive signals from the RSU device through the omnidirectional antenna 3. Specifically, the omnidirectional antenna 3's 3360° signal reception range ensures complete capture of the RSU signal.

[0046] Step S2: The received signal is analyzed by the spectrum analysis module to obtain signal quality parameters including antenna field strength, frequency, and occupied bandwidth. Multiple spectrum analysis modules are used to realize the synchronous acquisition of multi-channel radio frequency signals, and the analyzed signal quality parameters are transmitted to the main control module in real time.

[0047] Step S3: The positioning and attitude determination module performs correction based on the location and attitude data of the device in real time, thereby achieving high-precision positioning and attitude determination and providing an accurate position reference for the detection data. Step S4: The moving speed detection module acquires the moving speed data of the device in real time and transmits the data to the positioning and attitude determination module. The positioning and attitude determination module combines the moving speed data to compensate for the geographical location and attitude data it has acquired, thereby achieving data auxiliary correction. In step S5, the main control module receives and integrates signal quality parameters, geographical location data, attitude data, and movement speed data, performs corresponding matching between signal quality parameters and location information, and simultaneously collects basic information of the toll station / gantry equipment.

[0048] Finally, the multivariate data coupling field strength analysis algorithm in the data monitoring and analysis software is used to match the corresponding signal quality parameters and location information. Based on the integrated data, a contour map of the broadcast signal field strength or a distribution map of the RSU operating conditions is generated for the RSU equipment. An overall analysis report is generated for the average field strength, maximum field strength, field strength distribution width, occupied bandwidth, and center frequency of the RSU equipment, thus completing the intelligent detection of the RSU equipment.

[0049] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention shall be within the scope of protection of the pending claims of the present invention.

Claims

1. A mobile RSU intelligent inspection device, characterized in that, The detection equipment includes: The main control module is used to receive and process data information, and acts as a data acquisition server to provide control interface services and data query interface services to external acquisition software. An omnidirectional antenna is used to receive broadcast electromagnetic signals from roadside units at toll booth lanes or highway gantry locations and provide them to a spectrum analysis module for analysis. A spectrum analysis module, connected to the omnidirectional antenna and the main control module, is used to perform spectrum analysis on the received frequency band signals; The positioning and attitude determination module is communicatively connected to the main control module, used to acquire the real-time position and attitude information of the device and provide GPS satellite timing signals; The movement speed detection module, connected to the main control module, is used to detect the movement speed of the device and to assist in correcting the data from the positioning and attitude determination module.

2. The mobile RSU intelligent inspection device according to claim 1, characterized in that, The main control module is equipped with data monitoring and analysis software to comprehensively collect radio frequency analysis data from the spectrum analyzer, real-time position and attitude information from the positioning and attitude determination module, GPS timing signals, and digital information on the movement of the detection equipment. Through a multi-data coupled field strength analysis algorithm, it realizes the drawing of the RSU field strength distribution map and the extraction of key detection information.

3. The mobile RSU intelligent inspection device according to claim 2, characterized in that, The multivariate data coupled field strength analysis algorithm adopts multi-channel data denoising and interpolation methods, and introduces multi-resolution wavelet packet denoising and robust principal component analysis to decompose low-rank background and sparse anomalies. Combined with time-frequency domain synchronous sparse representation, it improves the ability to suppress impulse noise and quantization noise. For data points with abnormally high variation values, the structured predicted values ​​of the surrounding ±2 peak points are compared. Gaussian process regression or edge-preserving bilateral filtering is used to repair neighborhood consistency. If the deviation value exceeds the set threshold, the current peak point is removed and replaced with the reconstructed mean of the surrounding ±2 peak points. Based on the spatial electromagnetic wave propagation field strength attenuation formula and cubic spline interpolation method, the spatial distribution density of the overall data is supplemented, and lightweight ray tracing prior data is introduced to focus on characterizing shadow fading and multipath structure. Based on the free-space propagation loss model, a multi-state hybrid path loss model is adopted to improve the adaptability to complex road environments by estimating the path loss index and shadow fading standard deviation online. By integrating high-precision GPS information, the field strength coupling and smoothing prior are finally characterized on the spatial map, thereby forming the field strength distribution data of the required area point by point, and drawing a complete and smooth RSU field strength distribution map.

4. The mobile RSU intelligent inspection device according to claim 1, characterized in that, The testing equipment also includes a power supply module, which is connected to the main control module and uses an AC / DC conversion unit to supply power to the testing equipment through an external AC power source.

5. The mobile RSU intelligent inspection device according to claim 1, characterized in that, The positioning and attitude determination module includes an RTK unit and a MENS integrated inertial navigation unit, which is communicatively connected to the main control module. The RTK unit is communicatively connected to the MEMS integrated inertial navigation unit, which is connected to at least one mushroom-shaped antenna.

6. The mobile RSU intelligent inspection device according to claim 1, characterized in that, There are multiple spectrum analysis modules, each connected to the main control module via an Ethernet interface, for the synchronous acquisition of multi-channel radio frequency signals.

7. The mobile RSU intelligent inspection device according to claim 1, characterized in that, The detection equipment also includes a video monitor, which is connected to the main control module via an Ethernet interface, for real-time monitoring of the surrounding environment and acquisition of video data.

8. The mobile RSU intelligent inspection device according to claim 1, characterized in that, The main control module is an industrial control computer.

9. The mobile RSU intelligent inspection device according to claim 1, characterized in that, The moving speed detection module is a ground speed radar, which is connected to the main control module through a conversion module. The conversion module is used to convert between the RS485 protocol and the interface protocol of the main control module.

10. A mobile RSU intelligent detection method, wherein monitoring is performed using any one of the detection devices according to claims 1-9, characterized in that, Includes the following steps: Step S1: Receive signals from the RSU device via an omnidirectional antenna; Step S2: Perform spectrum analysis on the received signal using the spectrum analysis module to obtain signal quality parameters including antenna field strength, frequency, and occupied bandwidth; Step S3: Correction is performed based on the positioning and attitude determination module, and the geographical location and attitude data of the device are obtained in real time. Step S4: The moving speed data of the device is acquired in real time through the moving speed detection module and transmitted to the positioning and attitude determination module for compensation to assist in correction; Step S5: The main control module receives and integrates the signal quality parameters, geographical location data, attitude data, and movement speed data, performs corresponding matching between signal quality parameters and location information, and collects basic information of the toll station / gantry equipment.

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