An internet of things cooperative positioning experiment system and method for high school teaching

Abstract

The application discloses a kind of high school teaching used Internet of Things cooperation positioning experimental system and method, the method includes hardware module and software module, with test verification, data acquisition and fusion, time synchronization, self-organizing network communication and interface configuration function;Experimental system contains inertial measurement unit IMU, global navigation satellite system GNSS and V2X etc. Sensor unit includes: initialize new node and configure sensor interface, realize high-precision time synchronization by time synchronization and compensation module, collect GNSS, IMU and V2X data and realize cooperation positioning by fusion positioning algorithm, store or export result and original data to host computer and analyze, generate visual experimental result;And realize the multifunctional platform of Internet of Things cooperation positioning experiment under the environment of high school teaching, can improve experimental teaching effect and student practical ability.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of experimental teaching, and particularly relates to a method and system for Internet of Things cooperative positioning experiment for university teaching. BACKGROUND

[0002] At present, the research and experimental teaching of positioning technology in the university teaching environment mostly use experimental equipment of single positioning technology, such as single-point positioning experimental equipment based on GNSS or IMU. In addition, there is no effective way to carry out deep and complex experiments of Internet of Things in the aspect of Internet of Things teaching experiment. The traditional experimental platform lacks high-precision positioning and multi-source sensor cooperative testing tools, and it is difficult to meet the deep multi-node multi-sensing cooperative positioning teaching demand of Internet of Things, that is, there is a problem of insufficient testing and verification function. In addition, sensor cooperative positioning needs accurate time synchronization, and different devices have differences in hardware architecture, communication protocol, data acquisition frequency, etc., which makes the unification of time stamp a difficulty. Moreover, the existing experimental equipment usually only provides simple positioning result output, lacks the storage and analysis function of original data, and cannot meet the demand of in-depth research on positioning error, trend analysis, model verification and other aspects in the experiment. Moreover, the interface configuration of the existing experimental platform is fixed, and the expansibility is poor, which cannot meet the demand of multi-source data fusion and sensor expansion. SUMMARY

[0003] In order to overcome the above problems of university Internet of Things experimental education, the present application provides a method and system for Internet of Things cooperative positioning experiment for university teaching, which aims to develop a university Internet of Things cooperative positioning experimental system integrating testing and verification, data acquisition, time synchronization, self-organizing network management and interface configuration. The system will support cooperative positioning experiments in teaching and scientific research through multi-sensor data acquisition and fusion, advanced time synchronization algorithm, data storage and uploading mechanism and expandable interface management design.

[0004] The present application provides a method for Internet of Things cooperative positioning experiment for university experimental education, which contains hardware modules and software modules, has testing and verification, data acquisition and fusion, time synchronization, self-organizing network communication and interface configuration functions, and uses devices including inertial measurement unit (IMU), global navigation satellite system (GNSS) and V2X sensor units, wherein the GNSS is used to obtain satellite positioning information, the IMU is used to obtain its own motion state, and the V2X is used to realize cooperative positioning function.

[0005] Specifically, the following steps are included:

[0006] S1, initializing a new node, configuring a sensor interface and realizing local area network connection of the new node through a self-organizing network communication module to configure a node ID;

[0007] S2, the initialized new node obtains a synchronization signal and a standard global time through a time synchronization and compensation module, judges whether to perform time synchronization through whether the synchronization signal P triggers, if triggering, performs clock correction of a local time of the new node through a constructed clock model to synchronize the local time to a global standard time axis, and realizes high-precision time synchronization; if not triggering, proceeds to the next step;

[0008] S3, obtains GNSS, IMU and data (V2X) of surrounding nodes required for cooperative positioning through a data acquisition and processing module, synchronizes data of different sensors and different time stamps to a unified time through a time synchronization and compensation module, realizes cooperative positioning based on the Internet of Things through a fusion positioning algorithm, and locally stores the result and the original data, judges whether to export data, if yes, proceeds to the next step, otherwise, returns to S2 cyclically.

[0009] S4, exports the experimental result and the original data to a host computer through a related interface, obtains an experimental reference true value through difference processing of the original data and a reference value, analyzes the result data in the experimental link, compares, generates visualized data and records the experimental result, so as to complete a whole set of experimental and data analysis of cooperative positioning of the Internet of Things.

[0010] Further, the step S2 specifically comprises:

[0011] S21, the time synchronization and compensation module sends a synchronization signal P to the node controller through a signal line at a fixed time interval, and sends the global standard time at this moment through a data line to the node controller.

[0012] S22, the node controller triggers an external interrupt immediately after receiving the synchronization signal P, and obtains the local time at the current moment in the interrupt program Because theoretically, the local time cannot be obtained in real time, and there is decoding delay , that is, for the standard global time corresponding to the local time , the processor can calculate it at moment, if is used to synchronize and update , it will be very complex, so synchronization signal and the standard time of the last synchronization signal are used for synchronization.

[0013] S23, judges whether it is continuous with the last signal, and performs difference between the local time read through the last step and the local time saved when the last synchronization signal is read , that is: ​

[0014] ;

[0015] wherein is the local time when the last synchronization signal P is triggered, which is set to 0 by default at initialization, is the local time when the current synchronization signal P is triggered, if the time difference between them is within the error range of the fixed time interval, it is considered that the signals are continuous, and the next step is entered; as shown in the following formula:

[0016] ;

[0017] wherein is a predefined tolerance error range, represents the fixed time interval of the synchronization signal P, which is set according to the system accuracy. If the condition is not met, it is considered that the last signal is lost or this signal is the first synchronization signal P captured after initialization, and the next time synchronization step S24 is skipped, and S25 is directly performed;

[0018] S24, according to the judgment of the previous step S23, if the synchronization signal is continuous, then this time synchronization step is performed, according to the formula:

[0019] ;

[0020] wherein is the local time maintained by the node controller in real time, is the interrupt delay of the node controller, which is set according to the hardware characteristics and interrupt mechanism of the node controller. Then the next step is entered, and the time at the moment of reading and decoding the synchronization signal P is obtained.

[0021] S25, reading and decoding the time at the moment of synchronization signal P, updating and ;

[0022] ;

[0023] ;

[0024] At this point, the node time synchronization is completed.

[0025] Further, the step S3 specifically includes:

[0026] S31, data acquisition, real-time acquisition of GNSS, IMU and V2X sensor data through the data acquisition and positioning module. GNSS provides high-precision global positioning information, IMU obtains acceleration and angular velocity information of the node, and V2X obtains data required for cooperative positioning from surrounding nodes, including relative distance, speed and other state parameters.

[0027] S32, unify the data of the different sensors to the same standard time axis through a time synchronization and compensation module. The time synchronization mechanism is used to compensate and align the collection time of the sensor data, ensuring the time sequence consistency of the input data of the fusion algorithm.

[0028] S33, perform abnormality detection on the observation data, and if all are normal, proceed to the next step, otherwise, re-collect.

[0029] S34, based on the multi-source data after time synchronization, use Kalman filtering algorithm, particle filtering algorithm or other applicable fusion algorithm to solve the positioning, and obtain the real-time position and motion state of the node.

[0030] S35, store the final positioning result and the original sensor data locally for subsequent analysis and verification.

[0031] S36, judge whether the data is exported from the local storage to the host computer or the cloud, if yes, jump to the fourth step S4 for export, otherwise, jump back to the first step S2 for circulation.

[0032] Further, an Internet of Things cooperative positioning experiment system for college teaching, characterized in that it comprises a self-organizing network communication module, a data acquisition module, a time synchronization and compensation module, a data processing and calculation module, a data recording module, an interface configuration and management module, and a network control module. Among them:

[0033] The self-organizing network communication module is used to support the node to obtain the ID from the self-organizing network terminal and add it to the self-organizing network.

[0034] The data acquisition module is used to collect data from V2X, IMU and GNSS sensors;

[0035] The time synchronization and compensation module is used to synchronize the local time of multiple nodes with the global standard time, and realize the unification of distributed nodes;

[0036] The data processing and calculation module is used for data processing and cooperative positioning calculation;

[0037] The interface configuration and management module is used to configure the sensor interface and the functionally expandable college teaching platform;

[0038] The data recording module is used for data storage and running log saving;

[0039] The network control module is used to communicate with the remote server or cloud platform through wired or wireless means, realize data transmission and remote monitoring.

[0040] Further, an interface configuration and management module of the Internet of Things cooperative positioning experiment system used in college teaching adopts a configurable software and hardware interface, supports multiple communication protocols such as SPI, I2C, UART, CAN, USB, and has scalability and configurability. The module can realize fast transmission and interaction of data, upload result data and original data to a PC end, support batch export and analysis of experimental data, and perform trend analysis, error evaluation and model verification on the exported experimental data through a built-in analysis tool, thereby facilitating teaching experiment evaluation and improvement.

[0041] Further, a networked control module of the Internet of Things cooperative positioning experiment system used in college teaching supports remote configuration management function, and allows system parameters and algorithm configuration to be adjusted through a remote server to adapt to different experimental requirements and environmental conditions.

[0042] Compared with the prior art, the present application has the following advantages:

[0043] 1) For distributed Internet of Things nodes and multi-source sensor time axis misalignment, the present application is based on a time synchronization and compensation module, and can realize microsecond-level high-precision time synchronization through a synchronization signal and the like, ensure time consistency of multi-sensor data, and improve positioning accuracy.

[0044] 2) The GNSS, IMU and V2X sensors are integrated, multi-source information cooperation is performed through data acquisition, Kalman filtering and other fusion positioning algorithms are used to provide high-precision positioning results in complex environments.

[0045] 3) The present application adopts modular design and has flexible interfaces, supports multiple communication protocols (SPI, I2C, UART, CAN, USB, etc.), has flexible hardware interface configuration and function expansion capability, can dynamically adjust sensor types and connection modes according to experimental requirements, and can upload local data through external interfaces or networked modules.

[0046] 4) The present application has comprehensive experimental functions, and the system supports complete function processes such as data acquisition, real-time positioning and experimental result visualization; experimental data supports batch export and error analysis, and facilitates generation of experimental reports and trend analysis charts. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 FIG. 1 is a schematic diagram of a hardware module structure of the Internet of Things cooperative positioning experiment system used in college teaching according to an embodiment of the present application;

[0048] Figure 2 FIG. 2 is a flowchart of the Internet of Things cooperative positioning experiment method according to the embodiment of the present application;

[0049] Figure 3The flow chart of time synchronization for the embodiment one of the present application;

[0050] Figure 4 The flow chart of multi-sensor fusion positioning for the embodiment one of the present application;

[0051] Figure 5 The software module structure schematic diagram of the Internet of Things cooperative positioning experimental system for high school teaching provided by the embodiment two of the present application. DETAILED DESCRIPTION

[0052] In order to make the technical solutions of the present application clearer, the technical solutions provided by the present application will be described in detail below in combination with specific embodiments, and the present application will be further described in combination with the drawings. It can be understood that the specific embodiments described here are only part of the embodiments of the present application, which are used to explain the present application, rather than limit the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor are within the scope of protection of the present application.

[0053] Embodiment one: as Figure 1 The structure schematic diagram of the hardware device of the Internet of Things cooperative positioning experimental system for high school teaching of the embodiment one of the present application comprises a GNSS receiver unit 1, an IMU unit 2, a V2X unit 3, an upper computer 4, a WIFI unit 5, a storage card 6 and a node controller (controller). The GNSS receiver unit, the IMU unit, the V2X unit, the WIFI module and the storage card are connected with the controller, and the upper computer is connected with the controller through a serial port or the WIFI unit.

[0054] Among them:

[0055] The GNSS receiver unit is used for receiving satellite positioning signals, GPS time and second pulse signals for time synchronization;

[0056] The IMU is used for obtaining its own motion state and attitude information, and realizing cooperative positioning by combining GNSS and V2X information;

[0057] The V2X unit is used for obtaining roadside nodes and surrounding motion node information, realizing local area network connection with surrounding nodes, obtaining relative distances with surrounding nodes, and realizing cooperative positioning;

[0058] The WIFI unit is used for interacting with cooperative positioning nodes through wireless network, realizing uploading of related data or convenient function configuration.

[0059] The storage card is used for saving positioning data, sensor original data and related log information such as node error information.

[0060] The host computer is used for analyzing data stored in the Internet of Things cooperative positioning node, and calculating positioning coordinate trajectories which can be used as experimental true values through software, and performing error analysis and other experimental analysis.

[0061] The controller is configured to receive and process measurement data from the GNSS receiver unit, the IMU unit, and the V2X unit.

[0062] As Figure 2 is a flowchart of a method for an Internet of Things cooperative positioning experiment for a university teaching according to an embodiment of the present application. The embodiment can be applied to a university Internet of Things cooperative positioning experiment. Unlike a common and relatively simple indoor Internet of Things experiment, the method uses multi-sensor cooperation, processes multi-sensor and multi-node time synchronization problems, fuses information obtained by multiple sensors in a complex environment, stores results and original data, and cooperates with host computer software to realize data analysis and experiments.

[0063] The method specifically includes the following steps:

[0064] Step 1: node initialization, configuring sensor interfaces of the experimental node, assigning a second pulse external trigger interrupt channel for the GNSS receiver on the node controller; assigning an Ethernet communication channel for the V2X sensor to connect with the node controller; assigning communication channels for the above-mentioned units and the IMU and the memory card and dividing appropriate buffer zones to meet the time requirements of data processing and ensure the real-time performance of the system; through the V2X unit, assigning the ID of the current node, and adding the new node to the experimental ad hoc network to ensure that the new node can communicate and interact with other networked nodes. In the initialization process, the new node checks the hardware interface state and completes the function check of the sensor to ensure the normal operation of the equipment.

[0065] Step 2: time synchronization, obtaining a synchronization signal and a standard global time through a time synchronization and compensation module, determining whether to perform time synchronization through the synchronization signal P, if the synchronization signal P is triggered, performing clock correction of the local time of the new node through a clock model and a filtering algorithm constructed by the time synchronization and compensation module and the node controller to synchronize the local time to the global standard UTC time axis to realize high-precision time synchronization; if not, proceeding to the next step.

[0066] Specifically, the controller determines whether to receive a standard second pulse signal P (i.e., a time synchronization signal) and optimal position information from the GNSS receiver, and when the controller receives the signal, immediately triggers an interrupt to enter an interrupt program, otherwise, jumps to the next step.

[0067] Specifically, the optimal position information contains GPS time and latitude and longitude information, and the GPS time can be converted into universal time coordinated (UTC) time, and the second pulse signal P has a time interval of 1 second. The frequency is generated stably, and the error for a typical GNSS receiver does not exceed 20ns.

[0068] Specifically, the interrupt routine immediately queries the local time maintained by the controller at this moment. ,in represent The corresponding actual time; because in actual experiments, the description and recording of time by units such as controllers are discrete, therefore... Expressed in a discrete manner as Because in actual operation, there is a decoding delay in the information sent by the controller and receiver. That is, it cannot be done in local time. The corresponding global standard time can be directly calculated at any given moment. The controller must It takes a long time to calculate, if we use To update synchronously It would be very complicated, so the standard time of the synchronization signal and the previous synchronization signal is used. Synchronize.

[0069] To determine if the signal is continuous with the previous signal, specifically, use the local time read in the previous step. The local time saved since the last time the synchronization signal was read. To perform the difference, that is:

[0070] ;

[0071] in The default value of 0 during initialization indicates the local time when the synchronization signal P was last triggered. It is the local time when the synchronization signal P is triggered. If the difference between its time difference and the fixed time interval is within the error range, it is as shown in the following formula;

[0072] ;

[0073] in It is a predefined tolerance range. The pulse interval, expressed above, is 1 second, set according to the system precision. If this formula is satisfied, the signal is considered continuous, and a local time update is performed, as shown in the following formula; otherwise, no local time update is performed.

[0074] ;

[0075] in It is the local time maintained in real time by the node controller. is the interrupt delay of the node controller, which is a constant value set according to the hardware characteristics and interrupt mechanism of the controller. Through this method, the local time can be synchronized with the GPS time every second.

[0076] Then read and decode the optimal position information to obtain the standard global time , update and ;

[0077] ;

[0078] ;

[0079] Further, for the local time , if the minimum time accuracy is set to 0.1 ms, it is impossible to achieve 0.1 ms accuracy synchronization by the second pulse signal, and the error will still accumulate within one second. In practice, controllers and other units use crystal oscillators to provide them, and the general crystal oscillator frequency error is usually several tens of PPM (parts per million), i.e. several tens of microseconds of error per second, assuming it is seconds. Then the time within each second can be aligned according to the following formula by the coefficient :

[0080] ;

[0081] Step three, data acquisition, real-time acquisition of GNSS, IMU and V2X sensor data through the data acquisition and processing module. GNSS provides high-precision global positioning information, IMU obtains the acceleration and angular velocity information of the node, and V2X obtains the data required for cooperative positioning from surrounding nodes, including relative distance, speed and other state parameters.

[0082] Specifically, in practice, the frequencies of IMU, V2X and GNSS are arranged from high to low, so first of all, the position is estimated by constantly outputting data through the IMU, and the state of the node is set as where is the target position, is the velocity, is the attitude. The position and velocity updates provided by the IMU are described by the following inertial navigation equation:

[0083] ;

[0084] ;

[0085] where the subscript , is the time series, is the acceleration provided by the IMU, is the IMU data time interval. The pose update is done by:

[0086] ;

[0087] where denotes quaternion multiplication is an operation law, is the incremental pose obtained by integrating angular velocity, is the angular velocity output by the IMU.

[0088] Then the predicted target state according to the IMU output is expressed as the prediction step of Kalman:

[0089] ;

[0090] ;

[0091] is the predicted state quantity, is the state transition matrix (determined by the IMU dynamic equation), is the control input (such as acceleration and angular velocity), is the predicted state covariance matrix, is the process noise covariance matrix.

[0092] More specifically

[0093] ;

[0094] ;

[0095] where is the identity matrix, used to describe the autocorrelation of the state, and other parameter meanings are the same as described above.

[0096] When the positioning information of V2X or the positioning information of GNSS comes, the update step of Kalman filtering is performed, first for the observation model is defined as:

[0097] ;

[0098] where is the observation matrix, is the measurement noise, and other parameter meanings are the same as described above, then the update step is expressed as:

[0099] ;

[0100] ;

[0101] ;

[0102] wherein represents a filtering gain, is an observation noise, correspond to the state and covariance at time k, respectively, and superscript represents a prediction at time k, and other parameters have the same meaning as described above. represents a state prediction at time k, and other parameters have the same meaning as described above. Thus, the target state update is obtained.

[0103] Specifically, the positioning data and the previously received raw data are first stored in the corresponding buffer, and when the amount of data in the buffer reaches the set value, the data of the corresponding size is stored in the storage card for saving at one time.

[0104] Specifically, it is judged whether to export data, and if yes, the next step is performed, otherwise, it returns to step two.

[0105] Step four: according to the condition, the data stored in the storage card is exported to the host computer in the mode of WIFI or wired connection.

[0106] Further, first, the data of the RTK (Real-Time Kinematic) base station is loaded, and second, the exported raw data and the base station data are differentially processed on the solving software to obtain a positioning value with higher accuracy, usually millimeter level, which is used as a reference true value. Then, the data is analyzed, compared, visualized data is generated, and experimental results are recorded, so as to complete a whole set of Internet of Things cooperative positioning experiment and data analysis.

[0107] Embodiment two: referring to Figure 5 The software module composition of the Internet of Things cooperative positioning experiment system for college teaching provided by the embodiment two of the application comprises: a self-organizing network communication module, a data acquisition module, a time synchronization and compensation module, a data processing and calculation module, a data recording module, an interface configuration and management module, and a network connection control module. The data processing and calculation module is connected with the data acquisition module, the time synchronization and compensation module, the self-organizing network module, and the data recording module through the interface configuration and management module and the network connection control module, and is used for positioning, time synchronization and compensation, self-organizing network communication, and data recording of the collected data.

[0108] The interface configuration and management module is used for configuring the sensor interface and the functionally expandable college teaching platform, and comprises setting the communication interface parameter configuration and related parameter setting of the self-organizing network communication module, the communication channel setting and rate parameter setting of the data acquisition module and the data recording module, and the interface configuration of the network connection module.

[0109] ​The self-organizing network communication module supports the node to obtain the ID from the self-organizing network terminal through a wireless communication protocol and to be added to the self-organizing network, including obtaining a unique ID in the network, realizing the communication and data interaction with other nodes, supporting the dynamic joining and leaving of multiple nodes, having high flexibility and stability, and being suitable for the multi-node cooperative positioning experiment in the teaching environment of a college.

[0110] The data acquisition module is used for collecting data from sensors such as V2X, IMU and GNSS, collecting satellite positioning information by using a high-precision GNSS receiver, obtaining acceleration and angular velocity data by IMU, obtaining relative position information, speed information and other cooperative positioning required parameters from adjacent nodes by the V2X module, supporting multiple data communication protocols (such as UART, SPI, I2C), having extensibility, and being capable of connecting additional sensors according to experimental requirements.

[0111] The time synchronization and compensation module performs high-precision time synchronization and compensation on the collected data, ensures that the time stamps of all nodes and sensor data are consistent, adopts a time synchronization mechanism based on a synchronization signal, and finally unifies the data on a global UTC time axis by combining a time compensation algorithm, solves the multi-source sensor time axis alignment problem, and improves the cooperative positioning accuracy;

[0112] The data processing and calculation module performs fusion processing and positioning calculation on the sensor data after time synchronization, performs cooperative positioning calculation on GNSS, IMU and V2X data based on algorithms such as Kalman filtering, calculates the real-time position and motion state of the node, and realizes high-precision cooperative positioning.

[0113] The data recording module locally stores the positioning results, original sensor data and experiment logs generated during the experiment, saves the data by using an embedded storage device (such as an SD card or an eMMC storage chip), simultaneously supports batch exporting of the stored data to an upper computer or a cloud platform, facilitates subsequent analysis and verification of the experimental results, and can support accumulation and tracing of long-term experimental data;

[0114] The networked control module is responsible for the connection between the experimental system and the external network, supports remote data transmission and remote monitoring of the experimental process, can upload the experimental data to a cloud platform through the module, facilitates teachers and students to access the experimental results at any time and anywhere, supports communication with a remote server, realizes system parameter adjustment and firmware update functions.

[0115] It should be noted that in the above-mentioned embodiments, each module included is only divided according to the function logic, and is not limited to the above-mentioned division, as long as the corresponding function can be realized; in addition, the specific names of each functional unit are only for the convenience of mutual differentiation, and are not used to limit the protection scope of the present application.

[0116] Finally, the foregoing merely illustrates the principles of the application. It will be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the application and are thus within its spirit and scope. Thus, the application is not intended to be limited to the particular embodiments shown and described, but it is intended to cover all such modifications that are within the scope of the application. Accordingly, the application is not limited to that which can be described in the above disclosure. It is intended to cover all alternatives, modifications and equivalents falling within the scope of the claims.

Claims

1. A high school teaching Internet of Things cooperative positioning experiment method based on a high school teaching Internet of Things cooperative positioning experiment system, characterized in that, The system comprises a hardware device and a software module, wherein the hardware device comprises a GNSS receiver unit (1), an IMU unit (2), a V2X unit (3), a host computer (4), a WIFI unit (5), a storage card (6) and a controller; The GNSS receiver unit (1), the IMU unit (2), the V2X unit (3), the WIFI unit (5) and the storage card (6) are connected to the controller, and the host computer (4) is connected to the controller through a serial port or the WIFI unit (5); The IMU unit (2) is used for acquiring self-motion state and attitude information, and realizes cooperative positioning in combination with the GNSS receiver unit (1) and the V2X unit (3) information; The V2X unit (3) is used for acquiring roadside node and surrounding motion node information, and realizes local area network connection with surrounding nodes to acquire relative distances of the surrounding nodes and realize cooperative positioning; The software module comprises a self-organizing network communication module, a data acquisition module, a time synchronization and compensation module, a data processing and calculation module, a data recording module, an interface configuration and management module and a network connection control module; the data processing and calculation module is connected to the data acquisition module, the time synchronization and compensation module, the self-organizing network module and the data recording module through the interface configuration and management module and the network connection control module, and is used for positioning, time synchronization and compensation, self-organizing network communication and data recording on the collected data. The method comprises the following steps: S1, initializing a new node, configuring a sensor interface and realizing local area network connection of the new node through a self-organizing network communication module by configuring a node ID; wherein the node refers to a positioning device terminal in a network, and the new node refers to a new device terminal joining the network; S2, the new node after initialization acquires a synchronization signal P and a standard global time through the time synchronization and compensation module, judges whether to perform time synchronization through whether the synchronization signal P is triggered, and if triggered, performs clock correction of a local time of the new node through a clock model to synchronize the local time to a global standard time axis to realize high-precision time synchronization; if not triggered, proceeds to the next step; The step S2 specifically comprises: S21, the time synchronization and compensation module sends a synchronization signal P to the node controller through a signal line at a fixed time interval Δt, and sends the global standard time T at this moment through a data line P (t) to the node controller; S22, the node controller receives the synchronization signal P and triggers an external interrupt, and acquires the local time L at the current time in the interrupt program P (t); S23, judge whether the signal is continuous with the last one, the local time L read by the last step P (t) make difference with the local time L saved when the last time the synchronous signal is read P (t - ) Δt DIFF = L P (t) - L P (t - ) (1) where L P (t - ) is the local time when the last synchronization signal P is triggered, L P (t) is the local time when the current synchronization signal P is triggered. If the time difference between L P (t) and L - (t) is within a fixed time interval, the signals are considered to be continuous, and the next step is entered. |Δt DIFF -Δt|<εt (2) Wherein εt is a predefined tolerance error range, and Δt represents a fixed time interval of the synchronization signal P; If the condition is not met, it is considered that the last signal is lost or the current signal is the moment of capturing the synchronization signal P for the first time after initialization, and both cases are skipped to directly proceed to S25; S24, according to the judgment of S23, if the synchronization signal is continuous, a time synchronization step is performed according to the formula: L(t) = L P (t) = T P (t - )+ Δt - Δt int (3) where L(t) is the local time maintained by the node controller in real time, Δt int is the interrupt delay of the node controller, which is set according to the hardware characteristics and interrupt mechanism of the node controller; then go to the next step, read and decode to obtain T P (t); S25, read and decode the time T of the transmission synchronization signal P moment P (t), update T P (t - ) and L P (t - ) T P (t - )=T P (t) (4) L P (t - )=T P (t - )=T P (t) (5) At this point, the node time synchronization is completed; S26, crystal oscillator error compensation: time L[t]_ms within each second is compensated by a coefficient θ = Δerr 1s Alignment is performed according to the following formula; where Δerr 1s represents the crystal frequency error; S3, GNSS, IMU and V2X data are acquired through the data acquisition module, the data of different sensors and different time stamps are synchronized to a unified time through the time synchronization and compensation module, cooperative positioning based on the Internet of Things is realized through a fusion positioning algorithm, and the results and original data are locally stored, whether the data needs to be exported is judged, if yes, the next step is performed, otherwise, the cycle returns to S2. S4, export the experimental results and raw data to the host computer through the relevant interface, obtain the experimental reference true value by differentiating the raw data from the reference value, analyze and compare the result data in the experimental link, generate visual data and record the experimental results, so as to complete a complete set of Internet of Things cooperative positioning experiment and data analysis.

2. The Internet of Things cooperative positioning experiment method for high school teaching according to claim 1, characterized in that: the GNSS receiver unit (1) is used to receive satellite positioning signals, GPS time and second pulse signals for time synchronization; the host computer (4) is used to analyze the data stored in the Internet of Things cooperative positioning node, calculate the positioning coordinate trajectory that can be used as the experimental true value through software, and perform experimental analysis; the WIFI unit (5) is used to interact with the cooperative positioning node through wireless network to upload related data or configure functions; the storage card (6) is used to save positioning data, sensor raw data and related log information; the controller is used to receive and process the measurement data of the GNSS receiver unit (1), the IMU unit (2) and the V2X unit (3).

3. The Internet of Things cooperative positioning experiment method for high school teaching according to claim 1, characterized in that: the ad hoc network communication module is used to support the node to obtain ID from the ad hoc network terminal and add to the ad hoc network; the data acquisition module is used to acquire data from the V2X unit, the IMU unit and the GNSS receiver unit; the time synchronization and compensation module is used to synchronize the local time of multiple nodes with the global standard time, and realize the unification of distributed nodes; the data processing and calculation module is used for data processing to realize cooperative positioning calculation; the interface configuration and management module is used to configure the sensor interface and the function expandable high school teaching platform; the data recording module is used for data storage and running log saving; the network control module is used to communicate with the remote server or cloud platform through wired or wireless mode, realize data transmission and remote monitoring. 4.The high school teaching Internet of Things cooperative positioning experiment method of claim 1, wherein, The interface configuration and management module adopts configurable software and hardware interface, supports SPI, I2C, UART, CAN and USB multiple communication protocols, uploads the result data and raw data to the PC end, supports batch export and analysis function of experimental data, and through the built-in analysis tool, the exported experimental data is analyzed, error is evaluated and model is verified, which is convenient for teaching experiment evaluation and improvement.

5. The high school teaching IoT cooperative positioning experiment method of claim 1, wherein, The network control module supports remote configuration management function, allows to adjust system parameters and algorithm configuration through remote server to adapt to different experimental requirements and environmental conditions. 6.The high school teaching and learning Internet of Things cooperative positioning experiment method according to claim 1, wherein, The step S3 specifically includes: S31, data acquisition, real-time acquisition of GNSS, IMU and V2X sensor data through the data acquisition module; GNSS provides high-precision global positioning information, IMU acquires acceleration and angular velocity information of the node, and V2X acquires data required for cooperative positioning from surrounding nodes, including relative distance, speed and other state parameters; S32, unify the data of the different sensors to the same standard time axis through a time synchronization and compensation module; time synchronization is completed using S24 and S25, compensation and alignment of the collection time of the sensor data are achieved, and the time sequence consistency of the input data of the fusion algorithm is ensured; S33, judge whether the data is continuous and whether there is packet loss according to the time stamp, perform abnormality detection on the data, if normal, proceed to the next step, otherwise, re-collect; S34, based on the multi-source data after time synchronization, use a fusion algorithm to solve the positioning, obtain the real-time position and motion state of the node, wherein the fusion algorithm includes a Kalman filter algorithm and a particle filter algorithm; S35, store the final positioning result obtained in S34 and the original sensor data locally, for subsequent analysis and verification; S36, judge whether the data is exported from the local storage to the host computer or the cloud, if yes, jump to the fourth step S4 for export, otherwise, jump back to the first step S2 for circulation.

7. The high school teaching IoT collaborative positioning experiment method of claim 6, wherein, The step S34 specifically includes: Since the frequencies of the IMU, V2X and GNSS are arranged from high to low, firstly, the position is estimated through the IMU output data continuously, when the positioning information of the V2X or the GNSS arrives, the Kalman filter algorithm is updated, so as to obtain the real-time position and motion state of the node.

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