Personnel positioning method based on Beidou and LoRa ad hoc network

Abstract

The invention discloses a personnel positioning method based on a Beidou and LoRa ad hoc network, and relates to the technical field of Beidou and LoRa ad hoc networks. By combining a Beidou positioning module and a LoRa communication module, accurate transmission and error prediction of positioning information in a complex terrain or an urban environment are realized, specifically, the LoRa module forms an ad hoc network through automatic scanning and carries out detailed signal strength and quality data measurement and analysis in a multi-path effect influence area, so that the accuracy and the accuracy of the positioning information are improved. Through deep analysis of the multipath effect, the system can evaluate and predict positioning errors in advance, thereby improving accuracy and reliability of positioning information, effectively coping with delay and interference caused by signal reflection, and ensuring stable communication and accurate positioning in a complex environment.

Description

Technical Field

[0001] The present invention relates to the technical field of Beidou and LoRa self-organizing network, and in particular to a personnel positioning method based on Beidou and LoRa self-organizing network. Background Art

[0002] Beidou and LoRa self-organizing network refers to the use of Beidou satellite navigation system and LoRa (Long Range) technology to achieve a self-organizing network communication mode. The Beidou system provides accurate positioning and time synchronization, while LoRa technology supports long-distance, low-power wireless communication. By combining the two, devices can automatically form a network and transmit information without traditional communication infrastructure, which is particularly suitable for scenarios such as remote areas or emergency communications.

[0003] In the prior art, personnel positioning based on Beidou and LoRa ad hoc networks is usually achieved through terminal devices carrying Beidou positioning modules and LoRa communication modules. The Beidou module provides real-time location information of personnel, while the LoRa module transmits this location information to a centralized control center or other devices through ad hoc networking technology. Ad hoc networking technology allows multiple devices to automatically connect to form a network in an environment without a base station, thereby achieving long-distance, low-power personnel positioning and monitoring, which is especially suitable for complex environments such as outdoor, mountainous or emergency rescue. However, in complex terrain or urban environments, LoRa signals may be affected by multipath effects, that is, delays and interference caused by signal reflections. This situation may affect the signal reception of the Beidou positioning module and the data transmission of the LoRa communication module, resulting in significant errors in positioning information. Summary of the invention

[0004] The purpose of the present invention is to provide a personnel positioning method based on Beidou and LoRa self-organizing network to solve the shortcomings in the background technology.

[0005] In order to achieve the above object, the present invention provides the following technical solution: a personnel positioning method based on Beidou and LoRa self-organizing network, comprising the following steps:

[0006] S1: Equip the terminal device carried by the personnel with a Beidou positioning module and a LoRa communication module, wherein the Beidou positioning module is used to receive positioning signals from Beidou satellites, and the terminal device is used to perform preliminary processing on the received Beidou positioning signals;

[0007] S2: The LoRa communication module is used to automatically scan other devices nearby to form an ad hoc network. The terminal device transmits the positioning signal to other devices or relay nodes through the LoRa network and determines the multi-path target area for the positioning signal to be transmitted to the receiving end;

[0008] S3: Set up several test points in the multipath target area, and measure the signal strength data and signal quality data of each test point at different times and directions using a LoRa signal analyzer;

[0009] S4: Comprehensively analyze the signal strength data and signal quality data of each test point to evaluate the impact of multipath effect on LoRa signal;

[0010] S5: Further analyze the impact of multipath effect on LoRa signal, and evaluate the accuracy of positioning information based on the analysis results to predict and warn positioning errors in advance.

[0011] Preferably, in S3, the signal strength data is a fading depth anomaly index, and the method for obtaining the fading depth anomaly index is:

[0012] At the specified test point and test environment, the signal strength value obtained by the LoRa signal analyzer each time is marked as Ri, where i is the measurement number index; at each test point, based on the measurement data Ri, the average value Ravg and standard deviation σR of the signal strength are calculated; at each test point, the maximum value Rmax and the minimum value Rmin of the signal strength are identified, and the signal fading depth D is calculated, that is, the difference between the maximum and minimum values ​​of the signal strength is calculated, and the expression is: D = Rmax-Rmin; based on the measurement results of historical data, the expected fading depth D in a normal environment is determined norm , calculate the fading depth anomaly index AF, the expression is: σD is the standard deviation of the signal fading depth value.

[0013] Preferably, in S2, the signal quality data is an adjacent channel interference ratio, and the adjacent channel interference ratio is obtained by:

[0014] Use a spectrum analyzer to measure the signal power on the target channel and record the measured target channel signal power as P target ; On the adjacent channel, also use the spectrum analyzer to measure the signal power and record the measured adjacent channel signal power P adjacent ; Calculate the adjacent channel leakage power ratio, the expression is: Among them, P leakage is the signal power leaking to the adjacent channel, AC is the adjacent channel leakage power ratio, and the adjacent channel selectivity is calculated as: Among them, P interference is the interference signal power received in the adjacent channel, AS is the adjacent channel selectivity, and the adjacent channel interference ratio is calculated as follows: Where WD is the adjacent channel interference ratio.

[0015] Preferably, in S4, the signal strength data and signal quality data of each test point are comprehensively analyzed to evaluate the impact of the multipath effect on the LoRa signal, specifically:

[0016] The fading depth anomaly index and adjacent channel interference ratio are normalized, and the influence analysis coefficient of multipath effect on LoRa signal is calculated by the normalized fading depth anomaly index and adjacent channel interference ratio.

[0017] Preferably, the acquired multipath effect influence degree analysis coefficient on the LoRa signal is compared with a preset influence degree analysis coefficient reference threshold. If the multipath effect influence degree analysis coefficient on the LoRa signal is greater than or equal to the preset influence degree analysis coefficient reference threshold, it means that the multipath effect has a high influence degree on the LoRa signal, and it is classified as a high influence degree effect; if the multipath effect influence degree analysis coefficient on the LoRa signal is less than the preset influence degree analysis coefficient reference threshold, it means that the multipath effect has a low influence degree on the LoRa signal, and it is classified as a low influence degree effect.

[0018] Preferably, in S5, the influence of the multipath effect on the LoRa signal is further analyzed, and the accuracy of the positioning information is evaluated according to the analysis results, so as to predict and warn the positioning error in advance, specifically:

[0019] When the multipath effect impact analysis coefficient on the LoRa signal is greater than or equal to the preset impact analysis coefficient reference threshold, it is classified as a high impact effect, and the multipath effect impact analysis coefficient on the LoRa signal generated in the subsequent fixed time period that is greater than or equal to the preset impact analysis coefficient reference threshold is collected, and the positioning error is evaluated through the impact analysis coefficient WP, and the accuracy of the positioning information is predicted and warned.

[0020] Preferably, the positioning error is evaluated by the influence degree analysis coefficient WP, and the expression is: ε=γ×WP+δ; wherein ε is the predicted positioning error, WP is the influence degree analysis coefficient, γ is the regression coefficient, and δ is the constant term;

[0021] By calculating the value of the positioning error ε and comparing it with the preset positioning error threshold εthreshold, early prediction and warning can be achieved;

[0022] If ε≥εthreshold, it means that the accuracy of the positioning information is significantly affected, and an early warning signal is generated, indicating that remedial measures need to be taken;

[0023] If ε<εthreshold, it means that the accuracy of the positioning information is within the acceptable range and the positioning error is small, and no warning signal is generated at this time.

[0024] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0025] 1. The present invention can effectively solve the problem of positioning error caused by multipath effect in complex terrain or urban environment. By equipping with Beidou positioning module and LoRa communication module, the equipment can not only receive and preliminarily process positioning signals in real time, but also automatically connect in an environment without base stations through ad hoc networking technology to form a stable communication network. By setting test points in the area with significant multipath effect, accurately measuring and comprehensively analyzing signal strength and quality data, further evaluating the impact of multipath effect on the signal, and making early predictions and warnings of positioning errors.

[0026] 2. The present invention can evaluate and predict the accuracy of positioning information in real time, and timely identify and warn of possible positioning errors by normalizing the fading depth anomaly index and adjacent channel interference ratio, and combining historical data with preset thresholds. This mechanism greatly improves the accuracy and reliability of the positioning system in complex environments, and is particularly suitable for scenarios that require high-precision positioning, such as emergency rescue, thereby effectively reducing the potential risks caused by positioning errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0028] Figure 1 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] For examples, see Figure 1 As shown, the personnel positioning method based on Beidou and LoRa self-organizing network described in this embodiment includes the following steps:

[0031] S1: Equip the terminal device carried by the personnel with a Beidou positioning module and a LoRa communication module, wherein the Beidou positioning module is used to receive positioning signals from Beidou satellites, and the terminal device is used to perform preliminary processing on the received Beidou positioning signals;

[0032] S2: The LoRa communication module is used to automatically scan other devices nearby to form an ad hoc network. The terminal device transmits the positioning signal to other devices or relay nodes through the LoRa network and determines the multi-path target area for the positioning signal to be transmitted to the receiving end;

[0033] S3: Set up several test points in the multipath target area, and measure the signal strength data and signal quality data of each test point at different times and directions using a LoRa signal analyzer;

[0034] S4: Comprehensively analyze the signal strength data and signal quality data of each test point to evaluate the impact of multipath effect on LoRa signal;

[0035] S5: Further analyze the impact of multipath effect on LoRa signal, and evaluate the accuracy of positioning information based on the analysis results to predict and warn positioning errors in advance.

[0036] Among them, in S1, the terminal device carried by the personnel is equipped with a Beidou positioning module and a LoRa communication module. The Beidou positioning module is used to receive positioning signals from Beidou satellites, and the terminal device is used to perform preliminary processing on the received Beidou positioning signals, mainly including:

[0037] Select Beidou positioning module: Select the appropriate Beidou positioning module according to the project requirements, and ensure that it has the required accuracy, power consumption, size and other characteristics. Common Beidou positioning modules include single Beidou or multi-mode (supporting Beidou and GPS, GLONASS, etc.) positioning chips.

[0038] Select LoRa communication module: Select a LoRa communication module that meets the project requirements, considering factors such as transmission distance, frequency (such as 868MHz or 915MHz), power consumption, and data rate.

[0039] Hardware integration: Integrate the Beidou positioning module and LoRa communication module into the terminal device. Design the circuit board (PCB) to connect the module to the main processor and consider the layout of the antenna to ensure the signal reception quality.

[0040] Power management: Design a reasonable power management solution for terminal devices, including battery selection and charging circuit design, to ensure the battery life of the device.

[0041] Beidou positioning signal reception: Write firmware in the main processor to control the Beidou positioning module to receive positioning signals from Beidou satellites, parse satellite data packets, and extract key information such as latitude and longitude, altitude, and time.

[0042] Preliminary data processing: preliminary processing of the received positioning signal, including data formatting, filtering (such as noise elimination), time synchronization, etc., to ensure the accuracy and consistency of the positioning data.

[0043] Tests are conducted in actual application environments to verify the positioning and communication performance of the equipment under different terrain and climate conditions, with special attention paid to the accuracy of Beidou positioning and the reliability of LoRa signals.

[0044] Design the interface between the terminal device and the upper-layer application, and transmit the processed positioning data to the remote server or other devices through the LoRa communication module. You can choose to use standard communication protocols (such as MQTT, CoAP) for data transmission. If the device needs to interact directly with the user, develop a user interface (such as a display, buttons) or display the positioning information through a mobile phone application.

[0045] Design the housing according to the environment in which the device is used, ensuring it is waterproof, dustproof, and shockproof. Choose appropriate materials and manufacturing processes to ensure the durability of the device.

[0046] Deploy the terminal device to the target person and ensure that the device is properly connected to the supporting network infrastructure (such as LoRa gateway, server). Remotely monitor the device through the background system, regularly check the device's positioning data and communication status, and promptly detect and handle device anomalies.

[0047] S2: The LoRa communication module is used to automatically scan other devices nearby to form an ad hoc network. The terminal device transmits the positioning signal to other devices or relay nodes through the LoRa network and determines the multi-path target area for the positioning signal to be transmitted to the receiving end.

[0048] Initialize the LoRa module: When the terminal device starts, the LoRa communication module is initialized and communication parameters such as frequency band, channel, power, etc. are configured to ensure compatibility with other devices.

[0049] Device scanning and discovery: The LoRa module sends broadcast signals at fixed time intervals, which contain the unique identification of the device (such as device ID, network ID).

[0050] Signal monitoring: At the same time, the LoRa module monitors the broadcast signals of other devices and records the received device ID and signal strength (RSSI, Received Signal Strength Indicator).

[0051] Device screening: Filter out valid nearby devices based on the received broadcast signal strength and device ID. You can set a signal strength threshold to only keep devices with signal strength exceeding a certain value to ensure connection quality.

[0052] Device list maintenance: Store valid device information in the device list and update it regularly to ensure that the device information in the list is up to date.

[0053] Select the communication protocol: Based on the device list, the LoRa module negotiates with nearby devices to use the self-organizing network protocol (such as the Mesh network protocol) and determines the role of each device in the network (such as node, relay node, terminal node, etc.).

[0054] Network formation: According to the protocol, the devices automatically form a self-organizing network structure and determine the communication path between the devices.

[0055] The positioning information (such as latitude and longitude, timestamp) received from the Beidou positioning module is formatted and encapsulated into a data packet. The data packet can contain information such as source device ID, target device ID, data type, checksum, etc.

[0056] According to the topology of the ad hoc network, the optimal transmission path is selected to send the data packet to the target device or relay node. Routing algorithms (such as AODV, Ad-hoc On-demand Distance Vector) are usually used to select the path, giving priority to the path with small transmission delay and few hops.

[0057] The LoRa module sends data packets to the next node or relay node. If the target device is the final receiving end, it is sent directly; if the target device is a relay node, it continues to forward the data packet to the final receiving end.

[0058] After receiving the data packet, the receiving device (or relay node) returns an acknowledgment message (ACK) to the sending device. If the acknowledgment message is not received, the source device can trigger a retransmission mechanism and send the data packet again until the acknowledgment message is received. The maximum number of retransmissions can be set to avoid network congestion.

[0059] By analyzing the geographic environment of the target area, using signal propagation models (such as ray tracing models and free space models) to simulate the signal propagation path, we can identify areas that may cause multipath effects. These areas usually contain objects such as tall buildings, hills, and dense forests that can reflect or scatter signals.

[0060] During the data packet transmission process, the arrival time of signals on different paths is recorded. Through the time difference measurement technology (TDOA, Time Difference of Arrival), the multi-path propagation signal is identified and the path area with large delay is determined.

[0061] Several test points are arranged in the area where multipath effect may occur. The signal strength and quality are measured through these test points, and the signal changes of each path are recorded.

[0062] Use a LoRa signal analyzer to measure the test points and collect signal data under multipath effects. The reliability of the data can be increased by measuring the signal at different time points multiple times.

[0063] S3: Set up several test points in the multipath target area, and use the LoRa signal analyzer to measure the signal strength data and signal quality data of each test point at different times and in different directions.

[0064] Identify multipath target areas: By analyzing the geographic environment, building layout, and terrain features, identify target areas where multipath effects may occur. These areas typically include urban blocks with tall buildings, valleys, dense forests, etc.

[0065] Determine the distribution of test points: Determine the distribution of test points in areas where multipath effects may be strong. Test points should cover key locations in the entire area, including near reflective surfaces (such as walls, building edges), open areas, before and after obstacles, and at different heights.

[0066] Set the test point location: Set the test points at certain intervals in the target area. The interval between the test points should be determined according to the propagation characteristics of the LoRa signal, usually between tens of meters and hundreds of meters, to ensure that all multipath effect sources in the area can be covered. In areas with height differences (such as mountains or multi-story buildings), set test points at different heights to capture the multipath effect of the signal in the vertical direction. Set additional test points in places where there may be interference sources (such as metal objects, power equipment) to evaluate the impact of these interference sources on the LoRa signal.

[0067] Mark test points: Use a GPS device or map to mark the location of each test point and record the specific coordinates, altitude, and surrounding environment description of the test point.

[0068] Establish a test point information database: record the location information, environmental description and expected multipath effects of all test points in a database for subsequent data analysis and processing.

[0069] LoRa signal analyzer calibration: Before taking measurements, make sure the LoRa signal analyzer has been calibrated and the measurement parameters (such as frequency, bandwidth, power range) have been set. The accuracy of the device can be verified by measuring a standard signal source.

[0070] Determine the measurement mode: Select an appropriate measurement mode, such as continuous measurement or interval measurement, and set the measurement time interval (such as measuring every few seconds).

[0071] Measure signal strength at the test points: At each test point, measure the signal strength (RSSI) using a LoRa signal analyzer. Make sure the antenna is pointed consistently and keep the same measurement height and angle to ensure measurement consistency.

[0072] Take multiple measurements at different time periods (e.g., morning, afternoon, night) to capture changes in signal strength at different times and environmental conditions. Record the time and environmental conditions (e.g., weather, temperature) for each measurement.

[0073] The measured RSSI values ​​and their corresponding time, location, and direction are recorded in the database for subsequent analysis.

[0074] Measuring signal-to-noise ratio (SNR): At each test point, a LoRa signal analyzer is used to measure the signal-to-noise ratio (SNR). This data reflects the clarity and stability of the signal and can indicate the degree of interference caused by multipath effects.

[0075] Measuring signal delay: If the signal analyzer supports the time difference measurement technique (TDOA), the propagation delay of the signal can be measured to identify signal delay problems caused by multipath propagation.

[0076] Signal fading and interference analysis: During the measurement process, the instantaneous fading of the signal (such as deep fading) and possible interfering signals (such as interference from other radio frequency bands) are recorded. These data are critical for evaluating multipath effects.

[0077] Measuring signals in different directions: At each test point, adjust the direction of the antenna to point in different directions (such as east, south, west, and north), and measure the signal strength and quality in each direction. This can capture the directional changes caused by multipath effects such as reflection and refraction.

[0078] Record direction information: After each measurement, record the antenna's pointing angle and store it in association with the measured RSSI and SNR values.

[0079] Data aggregation and analysis: All measurement data (RSSI, SNR, delay, direction, etc.) are sorted by test point and input into analysis software or database to ensure data integrity and consistency.

[0080] The signal strength data is the fading depth anomaly index, which is used to measure whether the signal fading depth at certain specific locations is abnormal during signal propagation, that is, whether there is a significant deviation compared with the fading depth in a normal environment. The fading depth anomaly index is obtained as follows:

[0081] At the specified test point and test environment, the signal strength value obtained by the LoRa signal analyzer each time is marked as Ri, where i is the measurement number index; at each test point, based on the measurement data Ri, the average value Ravg and standard deviation σR of the signal strength are calculated; at each test point, the maximum value Rmax and the minimum value Rmin of the signal strength are identified, and the signal fading depth D is calculated, that is, the difference between the maximum and minimum values ​​of the signal strength is calculated, and the expression is: D = Rmax-Rmin; based on the measurement results of historical data, the expected fading depth D in a normal environment is determined norm , calculate the fading depth anomaly index AF, the expression is: σD is the standard deviation of the signal fading depth value.

[0082] The greater the signal fading depth, the more significant the impact of multipath effect on LoRa signal. A larger fading depth means that when receiving the signal, the signal interference and fluctuation caused by multipath propagation are more severe, resulting in significant changes in signal strength at different times or locations. This drastic change will increase the instability and bit error rate of communication, thus having a negative impact on the reliability and positioning accuracy of the LoRa network.

[0083] The signal quality data is the adjacent channel interference ratio, which is an important indicator for evaluating the interference between the target channel and the adjacent channel. It represents the ratio between the signal power in the target channel and the adjacent channel interference signal power. The adjacent channel interference ratio is obtained by:

[0084] Use a spectrum analyzer to measure the signal power on the target channel. The signal power represents the total signal power received in the target channel, usually in decibel milliwatts (dBm). The measured target channel signal power is recorded as P. target ; On the adjacent channel, also use a spectrum analyzer to measure the signal power. The signal power includes the signal power leaked from the target channel and the signal power of the adjacent channel itself. Record the measured adjacent channel signal power P adjacent ; Calculate the adjacent channel leakage power ratio, which represents the ratio of the target channel signal power to the signal power leaked into the adjacent channel. The expression is: Among them, P leakageis the signal power leaking to the adjacent channel, which can be directly measured by a spectrum analyzer or estimated by separating the target channel leakage part from the adjacent channel signal power. AC is the adjacent channel leakage power ratio. Calculate the adjacent channel selectivity, that is, the selectivity of the spectrum analyzer to the adjacent channel signal, which represents the ratio of the signal power received by the spectrum analyzer in the target channel to the interference signal power received in the adjacent channel. The expression is: Among them, P interference is the interference signal power received in the adjacent channel, AS is the adjacent channel selectivity, and the adjacent channel interference ratio is calculated as follows: Where WD is the adjacent channel interference ratio.

[0085] The larger the adjacent channel interference ratio, the better the interference isolation effect between the target channel and the adjacent channel, which means that the multipath effect has a relatively small impact on the LoRa signal. In this case, the signal has less interference in the target channel, so the negative impact of signal reflection, refraction and other phenomena caused by the multipath effect on communication quality will also be weakened, ensuring the stability of the signal and the reliability of transmission.

[0086] S4: Comprehensively analyze the signal strength data and signal quality data of each test point to evaluate the impact of multipath effect on LoRa signal.

[0087] The fading depth anomaly index and adjacent channel interference ratio are normalized, and the influence analysis coefficient of multipath effect on LoRa signal is calculated by the normalized fading depth anomaly index and adjacent channel interference ratio.

[0088] For example, the present invention can use the following formula to calculate the influence degree analysis coefficient of multipath effect on LoRa signal, and the calculation expression is: Where WP is the influence analysis coefficient of multipath effect on LoRa signal, AF is the fading depth anomaly index, WD is the adjacent channel interference ratio, and a 1 、a 2 are the fading depth anomaly index and the proportional coefficient of the adjacent channel interference ratio, and a 2 >a 1 >0.

[0089] The obtained multipath effect on the LoRa signal impact analysis coefficient is compared with the preset impact analysis coefficient reference threshold. If the multipath effect on the LoRa signal impact analysis coefficient is greater than or equal to the preset impact analysis coefficient reference threshold, it means that the multipath effect has a high impact on the LoRa signal, and it is classified as a high impact effect; if the multipath effect on the LoRa signal impact analysis coefficient is less than the preset impact analysis coefficient reference threshold, it means that the multipath effect has a low impact on the LoRa signal, and it is classified as a low impact effect.

[0090] a 1 、a 2 is a weight parameter, which reflects the importance of the fading depth anomaly index and adjacent channel interference ratio in the impact analysis. According to the actual situation and experimental results, the size of these parameters is adjusted to achieve accurate evaluation of multipath effects in different environments.

[0091] A preset reference threshold for the impact analysis coefficient. It is determined based on historical data or requirements in a specific application scenario and is used to distinguish between high-impact and low-impact thresholds.

[0092] S5: Further analyze the impact of multipath effect on LoRa signal, and evaluate the accuracy of positioning information based on the analysis results to predict and warn positioning errors in advance.

[0093] When the multipath effect impact analysis coefficient on the LoRa signal is greater than or equal to the preset impact analysis coefficient reference threshold, it is classified as a high impact effect, and the multipath effect impact analysis coefficient on the LoRa signal generated in the subsequent fixed time period that is greater than or equal to the preset impact analysis coefficient reference threshold is collected, and the positioning error is evaluated through the impact analysis coefficient WP, and the accuracy of the positioning information is predicted and warned.

[0094] The positioning error is evaluated by the influence degree analysis coefficient WP, and the expression is: ε=γ×WP+δ; where ε is the predicted positioning error, indicating the positioning deviation caused by the multipath effect, WP is the influence degree analysis coefficient, γ is the regression coefficient, which is used to adjust the influence weight of WP on the positioning error, usually obtained through experiments or historical data fitting, and δ is a constant term, which is used to adjust the offset of the model, usually the minimum positioning error.

[0095] By calculating the value of the positioning error ε and comparing it with the preset positioning error threshold εthreshold, early prediction and warning can be achieved.

[0096] High error warning: If ε≥εthreshold, it means that the accuracy of the positioning information may be significantly affected. At this time, a warning signal is generated, indicating that remedial measures need to be taken.

[0097] Low error assessment: If ε<εthreshold, it means that the accuracy of the positioning information is within an acceptable range and the positioning error is small, and no warning signal is generated.

[0098] In this embodiment, the Beidou positioning module and the LoRa communication module are integrated into the terminal device carried by personnel, which not only realizes efficient positioning and communication functions, but also can automatically form an ad hoc network and accurately measure signal data in an environment with complex multipath effects. Through comprehensive analysis of signal strength and quality, the impact of multipath effects on LoRa signals can be deeply evaluated and positioning errors can be predicted. This early warning mechanism improves the accuracy of positioning information, ensures reliable communication and precise positioning in complex environments, and is particularly suitable for emergency rescue and personnel positioning applications in complex terrain.

[0099] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0100] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0101] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0102] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0103] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0104] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0105] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0106] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A personnel positioning method based on Beidou and LoRa self-organizing network, characterized in that: The following steps are involved: S1: Equip the terminal device carried by the personnel with a Beidou positioning module and a LoRa communication module, wherein the Beidou positioning module is used to receive positioning signals from Beidou satellites, and the terminal device is used to perform preliminary processing on the received Beidou positioning signals; S2: The LoRa communication module is used to automatically scan other devices nearby to form an ad hoc network. The terminal device transmits the positioning signal to other devices or relay nodes through the LoRa network and determines the multi-path target area for the positioning signal to be transmitted to the receiving end; S3: Set up several test points in the multipath target area, and measure the signal strength data and signal quality data of each test point at different times and directions using a LoRa signal analyzer; S4: Comprehensively analyze the signal strength data and signal quality data of each test point to evaluate the impact of multipath effect on LoRa signal; S5: Further analyze the impact of multipath effect on LoRa signal, and evaluate the accuracy of positioning information based on the analysis results to predict and warn positioning errors in advance.

2. A personnel positioning method based on Beidou and LoRa self-organizing network according to claim 1, characterized in that: In S3, the signal strength data is a fading depth anomaly index, and the method for obtaining the fading depth anomaly index is: At the specified test point and test environment, the signal strength value obtained by the LoRa signal analyzer each time is marked as Ri, where i is the measurement number index; at each test point, based on the measurement data Ri, the average value Ravg and standard deviation σR of the signal strength are calculated; at each test point, the maximum value Rmax and the minimum value Rmin of the signal strength are identified, and the signal fading depth D is calculated, that is, the difference between the maximum and minimum values ​​of the signal strength is calculated, and the expression is: D = Rmax-Rmin; based on the measurement results of historical data, the expected fading depth D in a normal environment is determined norm , calculate the fading depth anomaly index AF, the expression is: σD is the standard deviation of the signal fading depth value.

3. A personnel positioning method based on Beidou and LoRa self-organizing network according to claim 2, characterized in that: In S2, the signal quality data is an adjacent channel interference ratio, and the adjacent channel interference ratio is obtained by: Use a spectrum analyzer to measure the signal power on the target channel and record the measured target channel signal power as P target ; On the adjacent channel, also use the spectrum analyzer to measure the signal power and record the measured adjacent channel signal power P adjacent ; Calculate the adjacent channel leakage power ratio, the expression is: Among them, P leakage is the signal power leaking to the adjacent channel, AC is the adjacent channel leakage power ratio, and the adjacent channel selectivity is calculated as: Among them, P interference is the interference signal power received in the adjacent channel, AS is the adjacent channel selectivity, and the adjacent channel interference ratio is calculated as follows: Where WD is the adjacent channel interference ratio.

4. A personnel positioning method based on Beidou and LoRa self-organizing network according to claim 3, characterized in that: In S4, the signal strength data and signal quality data of each test point are comprehensively analyzed to evaluate the impact of multipath effect on LoRa signal, specifically: The fading depth anomaly index and adjacent channel interference ratio are normalized, and the influence analysis coefficient of multipath effect on LoRa signal is calculated by the normalized fading depth anomaly index and adjacent channel interference ratio.

5. A personnel positioning method based on Beidou and LoRa self-organizing network according to claim 4, characterized in that: The obtained multipath effect on the LoRa signal impact analysis coefficient is compared with the preset impact analysis coefficient reference threshold. If the multipath effect on the LoRa signal impact analysis coefficient is greater than or equal to the preset impact analysis coefficient reference threshold, it means that the multipath effect has a high impact on the LoRa signal, and it is classified as a high impact effect; if the multipath effect on the LoRa signal impact analysis coefficient is less than the preset impact analysis coefficient reference threshold, it means that the multipath effect has a low impact on the LoRa signal, and it is classified as a low impact effect.

6. A personnel positioning method based on Beidou and LoRa self-organizing network according to claim 1, characterized in that: In S5, the impact of multipath effect on LoRa signal is further analyzed, and the accuracy of positioning information is evaluated based on the analysis results, so as to predict and warn the positioning error in advance. Specifically: When the multipath effect impact analysis coefficient on the LoRa signal is greater than or equal to the preset impact analysis coefficient reference threshold, it is classified as a high impact effect, and the multipath effect impact analysis coefficient on the LoRa signal generated in the subsequent fixed time period that is greater than or equal to the preset impact analysis coefficient reference threshold is collected, and the positioning error is evaluated through the impact analysis coefficient WP, and the accuracy of the positioning information is predicted and warned.

7. A personnel positioning method based on Beidou and LoRa self-organizing network according to claim 6, characterized in that: in, The positioning error is evaluated by the influence degree analysis coefficient WP, and the expression is: ε=γ×WP+δ; where ε is the predicted positioning error, WP is the influence degree analysis coefficient, γ is the regression coefficient, and δ is the constant term; By calculating the value of the positioning error ε and comparing it with the preset positioning error threshold εthreshold, early prediction and warning can be achieved; If ε≥εthreshold, it means that the accuracy of the positioning information is significantly affected, and an early warning signal is generated, indicating that remedial measures need to be taken; If ε<εthreshold, it means that the accuracy of the positioning information is within the acceptable range and the positioning error is small, and no warning signal is generated at this time.

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