A geographic data collection method, system and computer-readable storage medium

Abstract

The present invention discloses a geographic data collection method, system, and computer-readable storage medium. The geographic data collection method uses a terminal device to collect geographic features transmitted to a micro base station as first positioning data, and uses the geographic features of the RSSI parameters and PDR parameters of the communication signal between the underground sensor and the micro base station as second positioning data. A positioning coordinator fuses the first positioning data and the second positioning data to obtain a positioning result suitable for a dense networking environment. Furthermore, the method monitors the channel quality of each communication frequency band in the communication network to generate a communication frequency band set, dynamically updates the communication frequency band set based on the interference conditions of each communication frequency band, and provides a recommendation for the channel with the lowest interference for the communication process of geographic data collection.

Description

Technical Field

[0001] The present invention relates to geographic positioning technology, and in particular to a geographic data collection method, system and computer-readable storage medium. Background Art

[0002] Underground positioning is an important method to ensure the safety of underground workers, and it is also a necessary means to ensure the normal operation of various types of automated equipment in the mine. The existing technology provides some technical solutions to improve the accuracy of underground positioning. For example, CN111586838B discloses a positioning method based on the integration of RFID, Zigbee and UWB technologies. Currently, various intelligent environmental data acquisition technologies are gradually moving towards commercial use. Due to the high density of personnel and equipment distribution in mines, which belongs to intensive networking, the terminal devices carried by personnel and the terminal devices on automated machinery have a short communication distance with the base station, so that the terminal receives more uplink signals from the base station, and the base station can also receive more downlink signals from the terminal, which interferes with the underground geographic data collection. As a result, it is difficult to achieve high-precision positioning in mines in the existing networking environment. Therefore, it is necessary to further improve the existing technology. Summary of the Invention

[0003] To address the above issues, the present invention provides a geographic data collection method that uses the RSSI and PDR parameters of the communication signals between underground sensors and micro base stations to obtain lateral positioning coordinates. It then uses the air pressure values ​​monitored by a terminal device deployed at any mobile target to determine the longitudinal positioning coordinates. By integrating these lateral and longitudinal positioning coordinates, the terminal device can be accurately located. Furthermore, a dynamically updated set of communication frequency bands is used to select the channel with the lowest interference for communication between the micro base station and the underground sensor. Furthermore, the present invention also provides a geographic data collection system and computer-readable storage medium for implementing the geographic data collection method.

[0004] The invention objectives of this application can be achieved through the following technical solutions:

[0005] A geographic data collection method comprises the following steps:

[0006] Step 1: Set up a macro base station in the collection area and multiple micro base stations on the fully mechanized mining surface. Any micro base station can form a self-organized network with the macro base station.

[0007] Step 2: Deploy terminal devices on any mobile target, deploy multiple underground sensors in the mine, and control multiple underground sensors with any micro base station;

[0008] Step 3: The micro base station communicates with the underground sensor in any communication frequency band, records the channel quality Q of each communication frequency band, and forms a communication frequency band set with multiple communication frequency bands whose channel quality is greater than the real-time threshold T and sends it to the macro base station;

[0009] Step 4: At least one terminal device sends a first reference signal to the micro base station. The micro base station reads the first reference signal to determine first positioning data of the mobile target and stores the data in the positioning coordinator.

[0010] Step 5: The terminal device sends a second reference signal to the underground sensor i, and the underground sensor i measures and locates the PDR parameter of the second reference signal to obtain the first geographic feature;

[0011] Step 6: The terminal device sends a third reference signal to the underground sensor j, and the underground sensor j measures and locates the RSSI parameter of the third reference signal to obtain a second geographic feature;

[0012] Step 7: The underground sensor i and the underground sensor j transmit the first geographic feature and the second geographic feature to the micro base station. The micro base station determines the second positioning data of the mobile target and stores the second positioning data to the positioning coordinator.

[0013] Step 8: The micro base station senses the power of the communication frequency band and periodically traverses the channel quality Q of each communication frequency band. If the channel quality Q is greater than or equal to the real-time threshold T, it proceeds to step 9; otherwise, it proceeds to step 10.

[0014] Step 9: The micro base station updates the communication frequency band set, and the positioning coordinator obtains corrected positioning data based on the first positioning data and the second positioning data, and sends the corrected positioning data to the macro base station;

[0015] Step 10: The positioning coordinator deletes the first positioning data and the second positioning data, switches the communication frequency band of the channel, updates the communication frequency band set, and proceeds to step 3.

[0016] In the present invention, the first reference signal is a positioning reference signal, and the air pressure monitoring value monitored by the terminal device is called to determine the positioning depth of the terminal device according to the air pressure monitoring value.

[0017] In the present invention, the first positioning data is the positioning depth fed back by the terminal device at time t. The first positioning data at least includes a longitudinal coordinate and a timestamp. The longitudinal coordinate is the positioning depth fed back by the terminal device at time t.

[0018] In the present invention, the second reference signal is a detection reference signal, the positioning sensor module calculates the PDR parameter of the terminal device according to the second reference signal, and obtains the first geographic feature based on the PDR parameter.

[0019] In the present invention, the first geographical feature is that the positioning sensor module identifies the movement direction and speed of the terminal device and estimates the positioning data obtained by the terminal device.

[0020] In the present invention, the third reference signal is a detection reference signal, and the positioning sensor module calculates the RSSI of the terminal device according to the third reference signal, and obtains the second geographic feature based on the RSSI.

[0021] In the present invention, the second geographic feature is the observation value of the RSSI channel transmission of the terminal device identified by the positioning sensor module to estimate the positioning data of the terminal device.

[0022] In the present invention, the second positioning data is the horizontal positioning coordinates of the fusion of the first geographical feature and the second geographical feature, and includes the positioning data of the first geographical feature and the second geographical feature.

[0023] A system for geographic data collection, which is used to implement the geographic data collection method, includes: a macro base station, a micro base station, an underground sensor, a positioning coordinator, and a terminal device, wherein the underground sensor includes: a positioning sensor module and a monitoring sensor module.

[0024] The positioning sensor module is used to send detection reference signals and report terminal location information;

[0025] The monitoring sensor module includes gas sensor, mining pressure sensor, and CO concentration sensor;

[0026] The macro base station accesses the backbone fiber from the IPRAN and records the communication frequency band set;

[0027] The micro base station performs full-duplex communication with the terminal equipment and underground sensors in the mine, and the micro base station is used to receive the first positioning data or the second positioning data of the underground sensors;

[0028] The positioning coordinator is used to process the first positioning data or the second positioning data stored in the micro base station.

[0029] A computer-readable storage medium stores a computer program, which implements the geographic data collection method when executed by a processor.

[0030] The geographic data collection method, system, and computer-readable storage medium of the present invention have the following beneficial effects: By adjusting communication channels using a real-time updated communication frequency band set within a macro base station, the channel least affected by interference is selected for communication, effectively reducing interference issues associated with geographic data collection in dense networks. Furthermore, by using the PDR and RSSI parameters detected by communication signals between micro base stations and underground sensors as positioning benchmarks, and supplementing positioning with the depth position based on air pressure monitoring by terminal devices, a geographic data collection method combining horizontal and vertical positioning coordinates is constructed. This optimizes interference issues associated with geographic data collection in densely networked environments underground mines, improves positioning accuracy, and reduces positioning distortion issues in harsh environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic diagram of the arrangement structure of a geographic data collection method of the present invention;

[0032] Figure 2 is a flow chart of a geographic data collection method of the present invention;

[0033] Figure 3 This is a hardware structure diagram of the underground sensor of the present invention;

[0034] Figure 4 A flow chart of a terminal device and a micro base station acquiring first positioning data according to the present invention;

[0035] Figure 5 A block diagram of a geographic data collection system according to the present invention;

[0036] Figure 6 This is a schematic diagram of obtaining second positioning data by fusing the first feature and the second feature based on optimized Kalman filtering in the present invention. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0038] Geographic data collection in underground mines requires the establishment of a highly dense communication network environment. This network is deployed to implement technical methods such as data transmission, mining decision-making, image processing, and remote maintenance and control during the coal mining industry. Underground mines are characterized by narrow, long, and numerous branches. Radio wave transmission is easily affected by rough coal walls, and the layout of related equipment is prone to strong magnetic interference. Therefore, deploying communication networks for geographic data collection in underground mines has become a key technical means for the development of the intelligent coal mining industry in the new era. In this deployed mine network environment, terminal devices can receive more uplink signals from base stations, and base stations can also receive downlink signals from more devices. Deploying communication networks underground, due to the large number of terminal devices and the narrow, long, and branched environment, significantly shortens the communication distance between base stations and terminal devices. Geographic data collection in this dense network environment is susceptible to interference, and positioning accuracy cannot be guaranteed.

[0039] Example 1

[0040] like Figure 1The geographic data collection method implemented by the present invention constructs a macro base station by introducing a trunk optical fiber processed by IPRAN in the mine area. The macro base station is connected to multiple micro base stations under the mine, and the micro base stations and the macro base station form a self-network. There are multiple underground sensors distributed under the mine. The underground sensors are for the underground environment monitoring stage of the mine, including: gas sensors, mine pressure sensors, and CO sensors. In particular, in this embodiment, the underground sensor adds a positioning and communication function on the basis of an ordinary sensor, and is composed of a positioning sensing module and a monitoring sensing module. Among them, the positioning sensing module is used for positioning data transmission and reception and sensing functions, and the monitoring sensing module is used for the existing environmental monitoring function of the sensor. The terminal device is networked with the underground sensor and the micro base station, and the adjacent underground sensors communicate with the terminal device and transmit data with the nearest micro base station.

[0041] like Figure 2 The interference suppression-based high-precision mine positioning method implemented by the present invention improves positioning accuracy in a mine network environment by fusing positioning data from underground sensors and terminal devices. Based on a set of communication frequency bands, the macro base station provides the most optimal communication channel decision for the micro base station's communication ad hoc network, ensuring that the real-time communication channel is the communication frequency band with the least interference and the best quality in the environment, achieving interference suppression and further improving positioning accuracy standards. In this embodiment, this high-precision mine positioning method includes the following steps:

[0042] Step 1: Install IPRAN-processed backbone optical fibers in the monitoring area to construct a macro base station. Multiple micro base stations are installed on the fully-mechanized mining surface, and any micro base station forms an ad hoc network with the macro base station. In a dense networking environment, the number of base stations and coverage density are further increased. Therefore, a network architecture design is adopted that is primarily based on a central macro base station and has multiple micro base stations in a distributed configuration. Generally speaking, the macro base station access network includes wireless LAN, optical fiber, cellular technology, and digital subscriber lines. In this embodiment, based on the actual needs of the mine, the macro base station is connected to optical fiber to establish the network environment underground.

[0043] Step 2: Place terminal equipment on any mobile target, place multiple underground sensors in the mine, and any micro base station controls the data transmission and reception of multiple underground sensors. Multiple underground sensors need to be placed in the mine to collect real-time environmental data in the mine. In this embodiment, a gas concentration sensor is selected as a component of the underground sensor. Figure 3 The preferred gas concentration sensor is based on the ARM chip to build a monitoring sensor module. The periphery includes an alarm module, a minimum system module, a keyboard module, a display module, a communication module, and a signal processing module. A positioning sensor module is added separately to perform full-duplex communication with the ARM to form an underground sensor.

[0044] Step 3: The micro base station communicates with the underground sensor within any communication frequency band, recording the channel quality Q of each communication frequency band. Multiple communication frequency bands with channel quality greater than the real-time threshold T are combined into a communication frequency band set and sent to the macro base station. The micro base station performs power detection on the current communication frequency band and scans the interference power of each frequency band to form a communication frequency band set. The micro base station and the underground sensor select the optimal channel frequency band for communication based on the communication frequency band set.

[0045] In this embodiment, OFDM technology is used to collect the channel quality Q for each communication frequency band. The CSI-Tools tool in the micro base station's built-in network card periodically collects data packets received by the built-in network card. The micro base station converts these data packets into a complex vector, where any element in the complex vector corresponds to the CSI of the next subcarrier in the current communication channel. The communication frequency band set is a matrix consisting of the CSI of the subcarriers in each communication channel, stored as complex numbers, with 8-bit precision for both the real and imaginary parts of the storage structure.

[0046] In this embodiment, the communication system baseband is controlled by automatic gain, and the average power of the baseband signal needs to be controlled within a certain range, so as to minimize the power fluctuation of subsequent signals due to interference and avoid the occurrence of missed detection and false alarm problems. In the process of setting the real-time threshold T, the typical threshold parameter T is used. d With the real-time threshold parameter T s Combined construction, T=T d ×T s , real-time threshold parameter T s The energy of the current communication channel is determined by calculating the average energy E through the energy monitoring algorithm. The energy of the current communication channel can be equal to the average energy E in a short time. The typical threshold parameter is determined by multiple prior tests. In this embodiment, the preferred typical threshold parameter T d The value is 31 (CQI standard).

[0047] Step 4: At least one terminal device sends a first reference signal to the micro base station. The micro base station reads the first reference signal and determines the first positioning data of the mobile target, which is stored in the positioning coordinator. The first reference signal is a positioning reference signal. The air pressure value monitored by the terminal device is used as the positioning depth.

[0048] Since the mine is a deep straight channel structure, the atmospheric pressure at different mine depths varies greatly. Using this difference as a depth positioning standard has higher positioning accuracy than traditional Wi-Fi networks. In this embodiment, the terminal device has an air pressure monitoring function, and the air pressure information in the current environment is obtained through the air pressure monitoring device of the terminal device. Taking into account that the air pressure value is affected by the ambient temperature and weather factors, different ambient temperatures and weather factors will affect the standard value of the depth calculated by the air pressure value. Therefore, it is preferred to set multiple reference points at a known depth in the mine, and obtain the actual depth positioning H of the point to be measured based on the comparison and conversion between the real-time air pressure monitoring value and the reference point, H=h+18410×[1+(t m / 273.15)]·lg(P0 / P1), where t m =(t0+t) / 2, h represents the depth value of a certain reference point, P1 is the monitoring pressure value of the measured point, P0 is the monitoring pressure value of the reference point, t m is the current average temperature value, t is the temperature value of the point to be measured, and t0 is the temperature value of the reference point.

[0049] The process of obtaining the first positioning data is as follows Figure 4 As shown, the terminal device storage module erases the air pressure monitoring data of the previous cycle, monitors the temperature and air pressure values ​​of the current test point, reads the temperature and air pressure values ​​of the reference point, and obtains the depth value of the test point by calculation. Under the condition that the data volume is sufficient and the depth positioning accuracy is met, the stored depth value is called and filtered to obtain the positioning depth parameter, and the first positioning data is formed based on the positioning depth parameter and a timestamp.

[0050] Step 5: The terminal device sends a second reference signal to underground sensor i. Underground sensor i measures the PDR parameter of the second reference signal to obtain the first geographic feature. The second reference signal is a detection reference signal. The positioning sensor module calculates the PDR parameter of the terminal device based on the second reference signal.

[0051] The terminal device collects the current movement speed through the acceleration sensor and gyroscope, and calculates the signal transmission direction and step length within a specific time period.

[0052] In this embodiment, the PDR positioning detection is based on the transmission information of the second reference signal. The micro base station is at a certain time t k-1 Analyze the second reference signal of the terminal device and record t k-1 The positioning result of the terminal device at this moment is: [Mt k-1 , Nt k-1 ], based on the terminal equipment at t k Movement speed Vt at the moment k and heading angle βt k , detect terminal equipment at tk The positioning coordinates at this moment are: , The positioning coordinates are stored in the positioning coordinator as the first geographic feature.

[0053] Step 6: The terminal device sends a third reference signal to underground sensor j. Underground sensor j measures the RSSI parameter of the third reference signal to obtain a second geographic feature. The third reference signal is a detection reference signal, and the positioning sensor module calculates the RSSI parameter of the terminal device based on the third reference signal. The second geographic feature is the RSSI channel observation value used by the positioning sensor module to identify the terminal device and estimate the terminal device's positioning data.

[0054] In this embodiment, the positioning data of the terminal device is detected based on the RSSI channel transmission attenuation equation, wherein the RSSI channel transmission attenuation equation is: RSSI lose =RSSI0-10·α0·log(l / l0)+W, where RSSI lose represents the attenuation value of the current channel, RSSI0 is the signal strength when the distance between the terminal device and the underground sensor is 10, α0 is the loss factor, and W is the error value between the communication channel in the line-of-sight state and the non-line-of-sight state. Preferably, the error value W between the communication channel in the line-of-sight state and the non-line-of-sight state is measured using a third reference signal transmitted by the terminal device.

[0055] Step 7: Underground sensors i and j transmit the first and second geographic features to the micro base station. The micro base station determines the second positioning data for the mobile target and stores it in the positioning coordinator. The second positioning data is the lateral positioning coordinates of the fusion of the first and second geographic features, including the positioning data of the first and second geographic features. The micro base station fuses the first and second geographic features using a Kalman filter to generate the second positioning data.

[0056] Step 8: The micro base station senses the power of the communication frequency band and periodically traverses the channel quality Q of each communication frequency band. If Q ≥ T, the process proceeds to Step 9, indicating that the communication channel interference within the communication frequency band is severe, affecting positioning accuracy. If Q < T, the process proceeds to Step 10, indicating that the communication channel interference within the communication frequency band is not affected or is minimal, and does not affect positioning accuracy.

[0057] Step 9: The micro base station updates the communication frequency band set. The positioning coordinator obtains corrected positioning data based on the first and second positioning data and sends the corrected positioning data to the macro base station. The micro base station ranks the channel quality within all communication frequency bands based on historical communication frequency band interference and the real-time uploaded center quality list of each communication frequency band. Communication channels with higher rankings have lower interference and are recommended with higher priority.

[0058] Step 10: The positioning coordinator deletes the first positioning data and the second positioning data, switches the communication frequency band, and updates the communication frequency band set. At this time, the communication channel interference in the communication frequency band is serious, and the first positioning data and the second positioning data collected by the communication frequency band obtained in this period are invalid. The macro base station controls the replacement of the communication frequency band according to the recommended priority of the communication frequency band set in the next period and enters step 3.

[0059] Example 2

[0060] This embodiment discloses a system and computer-readable storage medium for geographic data collection, and the system and computer-readable storage medium are used to implement the geographic data collection method. Figure 5 , including: macro base station, micro base station, underground sensor, positioning coordinator, terminal equipment, among which the underground sensor includes: positioning sensor module and monitoring sensor module.

[0061] The positioning sensor module communicates with the micro base station, sends a detection reference signal, and reports the detected terminal location information;

[0062] Monitoring sensor modules include but are not limited to: gas sensors, mining pressure sensors, CO concentration sensors;

[0063] The macro base station access is connected to the backbone optical fiber from the IPRAN to maintain normal network communication in the mine and record the communication frequency band set;

[0064] The micro base station and the macro base station form an ad hoc network, and the micro base station conducts full-duplex communication with the terminal equipment and underground sensors in the mine to receive positioning data;

[0065] The positioning coordinator is used to process the positioning data stored in the micro base station.

[0066] Example 3

[0067] The fusion of the first geographical feature and the second geographical feature to obtain the second positioning data is achieved through Kalman filtering technology. This embodiment details a preferred geographical feature fusion method based on optimized Kalman filtering.

[0068] The process of the Kalman filter algorithm for fusion calculation of the first geographic feature and the second geographic feature includes two basic steps: time update and state update.

[0069] The time update equation is:

[0070]

[0071] The state update equation is:

[0072]

[0073] Among them, the corresponding time at time k and time k-1 is and is the estimated value of the posterior state of the Kalman filter, which is the result obtained after the Kalman filter fusion update. Represents the prior state estimate under the k-th time condition, which is an intermediate parameter of the Kalman filter fusion calculation. k With P k-1 Identify the corresponding posterior estimated covariance at time k and time k-1 respectively. is the prior estimated covariance at time k. H represents the transformation matrix of the location variable change. k Represents the measured value. K k is the Kalman filter gain, which is an intermediate parameter of the Kalman filter fusion calculation. A is the state transition matrix of the Kalman filter. B is the excitation noise covariance of the Kalman filter process, which represents the error between the state transition represented by A and the actual state transition. C is the noise covariance, u k-1 is the signal increment of the input at time k-1.

[0074] Model reference for the fusion of the first geographic feature and the second geographic feature after the optimized Kalman filter Figure 6 The model consists of two sub-filters, one for processing the first and second geographic features, respectively. The processed features are then fused in the main filter to obtain the globally optimal estimate. The main filter assigns weights to the first and second geographic features, and the weights of each local filter are determined based on the optimal output of the sub-filters.

[0075] The weight distribution is determined by the error covariance between the first and second geographic features. The time update process predicts the fused positioning. The state at time k is represented by the estimated value of the Kalman filter at time k-1. The fusion result of the main filter is corrected to ensure that the measurement value at the current moment can correct the fusion result and obtain the posterior estimate of the second positioning data at the current moment.

[0076] Example 4

[0077] This embodiment describes a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the geographic data collection method is implemented.

[0078] For the purposes of this specification, a "computer-readable storage medium" can be any device that can contain, store, communicate, propagate, or transport a program for use with or in conjunction with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable storage media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disk read-only memory (CDROM). In addition, a computer-readable storage medium can even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or otherwise processing it in a suitable manner as needed, and then stored in a computer memory.

[0079] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A geographic data collection method, characterized in that: The following steps are involved: Step 1: Set up a macro base station in the monitoring area and multiple micro base stations on the fully mechanized mining surface. Any micro base station can form a self-network with the macro base station. Step 2: Deploy terminal devices on any mobile target, deploy multiple underground sensors in the mine, and control multiple underground sensors with any micro base station; Step 3: The micro base station communicates with the underground sensor in any communication frequency band, records the channel quality Q of each communication frequency band, and forms a communication frequency band set with multiple communication frequency bands whose channel quality is greater than the real-time threshold T and sends it to the macro base station; Step 4: At least one terminal device sends a first reference signal to the micro base station. The micro base station reads the first reference signal to determine first positioning data of the mobile target and stores the data in the positioning coordinator. Step 5: The terminal device sends a second reference signal to the underground sensor i, and the underground sensor i measures and locates the PDR parameter of the second reference signal to obtain the first geographic feature; Step 6: The terminal device sends a third reference signal to the underground sensor j, and the underground sensor j measures and locates the RSSI parameter of the third reference signal to obtain a second geographic feature; Step 7: The underground sensor i and the underground sensor j transmit the first geographic feature and the second geographic feature to the micro base station. The micro base station determines the second positioning data of the mobile target and stores the second positioning data to the positioning coordinator. Step 8: The micro base station senses the power of the communication frequency band and periodically traverses the channel quality Q of each communication frequency band. If the channel quality Q is greater than or equal to the real-time threshold T, it proceeds to step 9; otherwise, it proceeds to step 10. Step 9: The micro base station updates the communication frequency band set, and the positioning coordinator obtains corrected positioning data based on the first positioning data and the second positioning data, and sends the corrected positioning data to the macro base station; Step 10: The positioning coordinator deletes the first positioning data and the second positioning data, switches the communication frequency band of the channel, updates the communication frequency band set, and proceeds to step 3.

2. The geographic data collection method according to claim 1, characterized in that: The first reference signal is a positioning reference signal, which calls the air pressure monitoring value monitored by the terminal device and determines the positioning depth of the terminal device according to the air pressure monitoring value.

3. The geographic data collection method according to claim 1, characterized in that: The first positioning data is the positioning depth fed back by the terminal device at time t. The first positioning data includes at least a longitudinal coordinate and a timestamp. The longitudinal coordinate is the positioning depth fed back by the terminal device at time t.

4. The geographic data collection method according to claim 1, wherein: The second reference signal is a detection reference signal. The positioning sensor module calculates the PDR parameter of the terminal device according to the second reference signal and obtains the first geographic feature based on the PDR parameter.

5. The geographic data collection method according to claim 1, characterized in that: The first geographic feature is that the positioning sensor module identifies the movement direction and speed of the terminal device and estimates the positioning data obtained by the terminal device.

6. The geographic data collection method according to claim 1, characterized in that: The third reference signal is a detection reference signal. The positioning sensor module calculates the RSSI of the terminal device according to the third reference signal and obtains the second geographic feature based on the RSSI.

7. The geographic data collection method according to claim 1, characterized in that: The second geographic feature is that the positioning sensor module identifies the observed value of the RSSI channel transmission of the terminal device and estimates the positioning data of the terminal device.

8. The geographic data collection method according to claim 1, characterized in that: The second positioning data is the horizontal positioning coordinates of the fusion of the first geographic feature and the second geographic feature, and includes the positioning data of the first geographic feature and the second geographic feature.

9. A geographic data collection system for implementing the geographic data collection method according to claim 1, characterized in that: include: Macro base station, micro base station, underground sensor, positioning coordinator, terminal equipment, wherein the underground sensor includes: positioning sensor module, monitoring sensor module, The positioning sensor module communicates with the micro base station, sends a detection reference signal, and reports the detected terminal location information; Monitoring sensor modules include: gas sensor, mining pressure sensor, CO concentration sensor; The macro base station access is connected to the backbone optical fiber from the IPRAN to maintain normal network communication in the mine and record the communication frequency band set; The micro base station and the macro base station form an ad hoc network. The micro base station conducts full-duplex communication with the terminal equipment and underground sensors in the mine to receive positioning data. The positioning coordinator is used to process the positioning data stored in the micro base station.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the geographic data collection method according to claim 1 is implemented.

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