Indoor and outdoor seamless fusion navigation method and system for wind power plant

Abstract

The invention relates to the technical field of navigation positioning, in particular to a wind power plant indoor and outdoor seamless fusion navigation method and system, and the method comprises the steps: obtaining GNSS signal position data at each moment, RFID electronic tag position data at each moment and IMU position data of a worker at the current moment; switching indoor and outdoor positioning modes according to the number of all reference satellites, the position precision diffusion factor at each moment and the adjusted signal-to-noise ratio of the GNSS signal; according to the GNSS signal position data, the RFID electronic tag position data and the IMU position data at the current moment and the positioning mode corresponding to the current moment, the navigation position of the worker at the current moment is obtained. According to the invention, the accuracy of navigation positioning is improved.

Description

Technical Field

[0001] The present invention relates to the field of navigation and positioning technology, and in particular to a wind farm indoor and outdoor seamless integration navigation method and system. Background Art

[0002] Wind farms are often located in remote areas such as offshore, mountainous, and plains. Workers conducting wind farm inspections may face risks such as natural disasters, equipment failures, and traffic accidents. Worker inspections not only help detect and repair equipment failures and optimize energy use, but also ensure equipment safety and extend its service life. Therefore, regular and accurate positioning and inspections by workers are crucial. Furthermore, worker positioning technology provides numerous advantages for wind farm operations. It can quickly locate workers to prevent them from entering dangerous areas, and monitor their working status and behavior, improving efficiency and reducing labor costs, providing strong support for the stable operation and efficient management of wind farms.

[0003] Wind farm inspection areas encompass both indoor and outdoor areas. Based on the differences in technical systems, location awareness technologies are categorized into two types: outdoor, exposed environments, and indoor, non-exposed environments. This is particularly important when personnel lose their positioning signals while moving from indoors to outdoors or vice versa. Satellite navigation is primarily used for outdoor, exposed environments. In non-exposed indoor environments, satellite navigation signals are unavailable, necessitating a positioning solution that covers the entire wind farm. Summary of the Invention

[0004] The present invention provides a wind farm indoor and outdoor seamless fusion navigation method and system, which is used to solve the problem of positioning signal loss caused by switching between indoor and outdoor environments during wind farm inspection.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A first aspect of the present invention is to provide a method for seamlessly integrating indoor and outdoor navigation in a wind farm, comprising: The distance between the reader and the worker is obtained through the RFID electronic tag and the reader, and the time difference between the RFID electronic tag reaching different readers is obtained; the acceleration and angular velocity of the worker at each moment are continuously measured through the inertial measurement unit (IMU); Obtain the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system; based on the relationship between the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system, eliminate some satellites and record the remaining satellites after elimination as reference satellites; obtain the GNSS signal position data at each moment through the reference satellite and the GNSS receiving device; obtain the RFID electronic tag position data at each moment based on the distance between the reader and the staff member and the time difference between the RFID electronic tag reaching different readers; and obtain the IMU position data of the staff member at the current moment through the pre-integration model based on the acceleration and angular velocity of the staff member at several moments before the current moment; Obtain the position accuracy spread factor and the signal-to-noise ratio of each reference satellite at each moment, and obtain the weight of each reference satellite based on the signal-to-noise ratio of each reference satellite; obtain the adjusted signal-to-noise ratio of the GNSS signal at each moment through the weight of each reference satellite and the signal-to-noise ratio of all reference satellites; switch between indoor and outdoor positioning modes based on the number of all reference satellites, the position accuracy spread factor at each moment, and the adjusted signal-to-noise ratio of the GNSS signal; The navigation position of the staff at the current moment is obtained based on the current GNSS signal position data, RFID electronic tag position data, IMU position data and the positioning mode corresponding to the current moment.

[0006] Furthermore, removing some satellites based on the relationship between the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system includes:

[0007] Where, represents the position vector of each satellite in the geocentric coordinate system, represents the position vector of the receiver in the geocentric coordinate system, represents the modulus of the vector, represents the inverse sine function, Indicates the elevation angle of each satellite; The satellites whose elevation angle is less than the preset elevation angle threshold are eliminated.

[0008] Furthermore, the method of obtaining the RFID electronic tag location data at each moment based on the distance between the reader and the staff and the time difference between the RFID electronic tag reaching different readers includes: The RFID tag location data at each moment is obtained through signal strength positioning method or arrival time difference positioning method; (1) The specific process of obtaining the RFID electronic tag location data at each moment through the signal strength positioning method is as follows: Signal strength attenuation model:

[0009] Where, Indicates the The distance between the reader and the staff, Indicates the reference distance; Indicates the The signal strength reflected by the active RFID tag of the staff member received by each reader; Indicates the signal strength reflected at the reference distance; represents the path loss exponent, represents random noise that follows a Gaussian distribution; The signal strength attenuation model is used to infer the The distance between the reader and the staff:

[0010] Among them, The distance between the reader and the worker and the The relationship between the coordinates of a reader and the coordinates of a staff member is as follows:

[0011] Where, Indicates the The coordinates of the reader, Indicates the location coordinates of the staff member's RFID electronic tag; By combining the distances between the three readers and the staff and the relationship between the coordinates of the readers and the coordinates of the staff, the position coordinates of the staff's RFID electronic tags are obtained. ; (2) The specific process of obtaining the RFID electronic tag location data at each moment through the arrival time difference positioning method is as follows: The signal arrival time difference ranging is specifically expressed by the formula:

[0012] Where, Indicates that the staff's active RFID electronic tag has reached the The time of arrival at the first reader The time difference between the reader times, represents the speed of light, Indicates that the staff has arrived The reader and The distance difference between the readers;

[0013]

[0014]

[0015] Where, Indicates the The distance between the reader and the staff, Indicates the The coordinates of the reader, Indicates the location coordinates of the staff member's RFID electronic tag; Perform pairwise matching among the three readers, construct a set of equations, and jointly obtain the position coordinates of the staff's RFID electronic tags ; The obtained RFID tag location coordinates The coordinate conversion formula is used to convert the position coordinates in the global coordinate system. The coordinate conversion formula is specifically expressed as:

[0016] Where, Indicates the location coordinates obtained by the RFID electronic tag. The rotation matrix representing the reader installation posture, Represents the global position translation vector of the reader, Represents the position coordinates in the global coordinate system; The position data of the RFID electronic tag at each moment is obtained through the position coordinates in the global coordinate system.

[0017] Furthermore, the method of obtaining the IMU position data of the staff member at the current moment through the pre-integration model based on the acceleration and angular velocity of the staff member at several moments before the current moment includes: The displacement increment and velocity increment of the worker are obtained by the acceleration measured by the IMU; the displacement increment and velocity increment are specifically expressed by the formula:

[0018]

[0019] Where, Indicates the time The acceleration of the staff at that moment, Indicates the A moment, Indicates the A moment, Represents the zero bias estimate of the accelerometer in the inertial measurement unit IMU; Represents the rotation matrix from the IMU body coordinate system to the global coordinate system, represents small increments in time, Indicates the From moment to moment The displacement increment between moments, Indicates the From moment to moment The speed increment between moments; The attitude increment is obtained by measuring the angular velocity of the IMU. The attitude increment is specifically expressed by the formula:

[0020] Where, Indicates the time The angular velocity of the staff member at a moment, Represents the zero bias estimate of the gyroscope in the inertial measurement unit IMU, represents an exponential function with a natural constant as the base, Indicates the The time corresponding to the moment, Indicates the The time corresponding to the moment, Indicates the From moment to moment The increment of posture between moments; According to the displacement increment, the velocity increment and the attitude increment, the IMU position data of the staff member at the current moment is obtained through a pre-integration model; Among them, the displacement increment, the velocity increment and the posture increment formula are and It is obtained by calculating the zero-bias estimation equation, which is specifically expressed as:

[0021] Where, Indicates the GNSS signal position coordinates, represents the norm, Indicates the The position at a moment, Represents the predicted position coordinates; It means finding the parameters that minimize the objective function. Represents the bias estimate and ; Indicates the number of all moments in the preset time window.

[0022] Furthermore, obtaining a weight of each reference satellite according to the signal-to-noise ratio of each reference satellite; and obtaining an adjusted signal-to-noise ratio of the GNSS signal at each moment through the weight of each reference satellite and the signal-to-noise ratios of all reference satellites include:

[0023] Where, Indicates the The signal-to-noise ratio of the reference satellites, Indicates the The signal-to-noise ratio of the reference satellites, represents the number of all reference satellites, Indicates the The weight of the signal-to-noise ratio of each reference satellite;

[0024] Where, Indicates the adjusted signal-to-noise ratio of the GNSS signal at each moment.

[0025] Furthermore, the switching of indoor and outdoor positioning modes according to the number of all reference satellites, the position accuracy spread factor at each moment, and the adjusted signal-to-noise ratio of the GNSS signal includes: When the staff is outdoors, they first use the first positioning mode to locate and obtain the GNSS signal every second; when the continuous When the GNSS signal of 10 seconds meets the preset first signal quality reference range of medium and low quality, the positioning mode is switched from the first positioning mode to the second positioning mode. Otherwise, the positioning mode is not switched and the first positioning mode is maintained. No GNSS signal is detected for seconds or continuously When the RFID reader detects an active RFID electronic tag, it switches the positioning mode from the second positioning mode to the third positioning mode. Otherwise, it does not switch the positioning mode and maintains the second positioning mode. When the GNSS signal of 100 seconds meets the preset second signal quality reference range of medium to low quality, the positioning mode is automatically switched back to the first positioning mode from the third positioning mode; otherwise, the positioning mode is not switched and the third positioning mode is maintained; in, Indicates the preset reference number; Among them, the preset first signal quality reference range is: C / N <38 dB-Hz, number of satellites <4, PDOP >5; the preset second signal quality reference range is: C / N >40 dB-Hz, number of satellites ≥6, PDOP <2; among them, C / N represents signal-to-noise ratio, dB-Hz represents decibel-hertz; PDOP represents position precision spread factor.

[0026] Furthermore, obtaining the navigation position of the staff member at the current moment according to the current moment GNSS signal position data, RFID electronic tag position data, IMU position data and the positioning mode corresponding to the current moment includes: Get the weights corresponding to different location data in each positioning mode; The navigation position of the staff at the current moment is obtained by fusing the position data using the weights corresponding to different position data in each positioning mode, the current GNSS signal position data, the RFID electronic tag position data, and the IMU position data through the extended Kalman filter algorithm.

[0027] The second aspect of the present invention is to provide a wind farm indoor and outdoor seamless integration navigation system, comprising: Data acquisition module: used to obtain the distance between the reader and the worker through the RFID electronic tag and the reader, and then obtain the time difference between the RFID electronic tag reaching different readers; the inertial measurement unit (IMU) continuously measures the acceleration and angular velocity of the worker at each moment; Position analysis module: used to obtain the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system; based on the relationship between the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system, some satellites are eliminated and the remaining satellites are recorded as reference satellites; the GNSS signal position data at each moment is obtained through the reference satellite and the GNSS receiving device; the RFID electronic tag position data at each moment is obtained based on the distance between the reader and the staff and the time difference between the RFID electronic tag reaching different readers; based on the acceleration and angular velocity of the staff at several moments before the current moment, the IMU position data of the staff at the current moment is obtained through the pre-integration model; Positioning switching module: used to obtain the position accuracy spread factor and the signal-to-noise ratio of each reference satellite at each moment, and obtain the weight of each reference satellite based on the signal-to-noise ratio of each reference satellite; obtain the adjusted signal-to-noise ratio of the GNSS signal at each moment through the weight of each reference satellite and the signal-to-noise ratio of all reference satellites; switch between indoor and outdoor positioning modes based on the number of all reference satellites, the position accuracy spread factor at each moment, and the adjusted signal-to-noise ratio of the GNSS signal; Fusion navigation module: used to obtain the navigation position of the staff at the current moment based on the current GNSS signal position data, RFID electronic tag position data, IMU position data and the positioning mode corresponding to the current moment.

[0028] The third aspect of the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein when the processor executes the computer program, the method for seamlessly integrating indoor and outdoor navigation of a wind farm is implemented.

[0029] A fourth aspect of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for seamlessly integrating indoor and outdoor navigation in a wind farm.

[0030] Compared with the existing technology, the beneficial effects of the present invention are as follows: through the relationship between the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system, some satellites are eliminated, and the remaining satellites after elimination are recorded as reference satellites, and the error caused by low-elevation-angle satellites is reduced by eliminating satellites; the GNSS signal position data at each moment is obtained through the reference satellite and the GNSS receiving device; the RFID electronic tag position data at each moment is obtained according to the distance between the reader and the staff and the time difference between the RFID electronic tag reaching different readers; the IMU position of the staff at the current moment is obtained through the pre-integration model according to the acceleration and angular velocity of the staff at several moments before the current moment. data; obtain the weight of each reference satellite according to the signal-to-noise ratio of each reference satellite; obtain the adjusted signal-to-noise ratio of the GNSS signal at each moment through the weight of each reference satellite and the signal-to-noise ratio of all reference satellites; switch the indoor and outdoor positioning modes according to the number of all reference satellites, the position accuracy diffusion factor at each moment and the adjusted signal-to-noise ratio of the GNSS signal; obtain the navigation position of the staff at the current moment according to the GNSS signal position data, RFID electronic tag position data, IMU position data and the positioning mode corresponding to the current moment, which solves the problem of positioning signal loss caused by switching between indoor and outdoor environments during wind farm inspections and improves the accuracy of navigation positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 The present invention provides a schematic flow chart of the steps of a method for seamlessly integrating indoor and outdoor navigation in a wind farm; Figure 2The present invention provides a module flow diagram of a wind farm indoor and outdoor seamless integration navigation system. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions 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 embodiments described are only 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 making creative efforts should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] In response to the problems existing in the background technology, a wind farm indoor and outdoor seamless integration navigation method and system is studied and designed, which has important practical significance.

[0036] like Figure 1 As shown, the first aspect of the present invention is to provide a method for seamlessly integrating indoor and outdoor navigation in a wind farm, comprising the following steps: Step S001: deploy GNSS receiving equipment and collect relevant data.

[0037] A GNSS (Global Navigation Satellite System) receiving device is installed on the safety equipment and vehicles of power plant inspection workers. The GNSS receiving device is used to receive GNSS signals from the workers or vehicles.

[0038] The GNSS receiving device in this embodiment must meet the requirements of a device that supports GPS L5 (Global Positioning System L5) and BeiDou B2a (BeiDou Navigation Satellite System B2a) signals.

[0039] It should be noted that when workers work outdoors, the surrounding environment has less interference with the signal, which makes the accuracy of navigation and positioning through GNSS signals higher; when workers work indoors, the surrounding environment has more interference with the signal, which makes the accuracy of navigation and positioning through GNSS signals lower. Therefore, for the navigation and positioning situations of workers indoors or near indoors, other technologies need to be combined to improve the accuracy of navigation and positioning.

[0040] It's important to note that RFID electronic fencing is a virtual perimeter control solution based on radio frequency identification (RFID) technology. By deploying RFID readers and tags, it monitors and automatically manages the entry and exit of targets (people, equipment, and assets) within a specific area. Its core principle is to define a virtual perimeter using the coverage of RFID signals. Therefore, to mitigate environmental interference with GNSS signals, RFID tags are installed in areas with numerous obstructions to enable navigation and positioning of personnel in these areas.

[0041] Specifically, active RFID (Radio Frequency Identification) electronic tags (active RFID tags with integrated IMU) with IMU (Inertial Measurement Unit) are installed on tools, spare parts, and worker safety equipment (such as hard hats and safety belts). An independent UHF (Ultra High Frequency) channel (860-960 MHz frequency band segment) is allocated to each device to avoid signal conflicts. Among them, the inertial measurement unit (such as accelerometer, gyroscope) can detect the motion state of the object (such as moving direction and speed), assisting RFID in achieving more accurate dynamic positioning.

[0042] Install and deploy ceramic-encapsulated tags (rather than plastic or metal) at indoor and outdoor connection areas such as tower ladder corners, cabin entrances, and cable tray nodes (where signals are susceptible to interference or require critical positioning). Ceramic-encapsulated tags have low reflection interference on RF signals and are suitable for environments with high metal density (such as the many metal structures in wind turbine towers).

[0043] RFID readers are installed and deployed at key locations such as each floor of the wind turbine and the warehouse entrance to achieve regional positioning (such as "tower bottom exit" and "cabin internal exit"); logical areas are divided according to the reader coverage area (such as "tower bottom exit" and "cabin internal exit"). When a tag enters the RFID reader range, it is determined that the staff is located in that area; the tag ID is bound to the preset coordinate database to trigger position correction (for example, when the IMU cumulative error is large, the position is reset through the RFID signal); combined with multi-reader signal strength (RSSI) or arrival time difference (TDOA) to achieve meter-level or even sub-meter-level positioning in small areas (such as the cabin).

[0044] Specifically, the distance between the reader and the staff is obtained through the RFID electronic tag and the reader, and then the time difference between the RFID electronic tag reaching different readers is obtained; the acceleration and angular velocity of the staff at each moment are continuously measured through the inertial measurement unit (IMU).

[0045] Step S002: Acquire three different types of location data.

[0046] The first type is GNSS signal location data; It should be noted that because the signals of low-elevation-angle satellites are more easily reflected by the ground, buildings or other obstacles, the receiver receives a mixed waveform of direct signals and reflected signals; and the mixed waveform easily leads to measurement errors, which reduces the accuracy of satellite navigation; in order to reduce the errors caused by low-elevation-angle satellites, some satellites are eliminated by analyzing the elevation angle of the satellite.

[0047] Specifically, the RTKLIB (Real-Time Kinematic Library) open-source library is used to directly obtain the satellite's position vector in the geocentric coordinate system and the receiver's position vector in the geocentric coordinate system. The receiver is mounted on the object to be positioned, such as a worker or vehicle.

[0048] The elevation angle of each satellite is obtained according to the position vector of each satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system. The elevation angle of each satellite is specifically expressed by the formula:

[0049] Where, represents the position vector of each satellite in the geocentric coordinate system, represents the position vector of the receiver in the geocentric coordinate system, represents the modulus of the vector, represents the inverse sine function, Indicates the elevation angle of each satellite.

[0050] The satellites with elevation angles less than the preset elevation angle threshold are eliminated, and the remaining satellites after elimination are recorded as reference satellites. In this embodiment, there is no specific limitation on the preset elevation angle threshold, and the implementer may determine it according to the specific situation.

[0051] By referring to satellites and GNSS receiving devices, the GNSS signal position data of the staff or vehicle at each moment in outdoor wide-area positioning is obtained; among them, the process of obtaining GNSS signal position data through satellites and GNSS receiving devices is a well-known technology and will not be described in detail here.

[0052] It should be noted that since the position data obtained through GNSS signals has certain errors, and this error comes from the influence of frequency band pseudorange, the GNSS signal position data is adjusted by the frequency and pseudorange of different frequency bands.

[0053] Specifically, the ionospheric-free pseudorange is obtained according to the frequency and pseudorange of different frequency bands; the ionospheric-free pseudorange is specifically expressed by the formula:

[0054] Where, Indicates frequency band frequency, Indicates frequency band frequency, Indicates frequency band The pseudorange observation value of Indicates frequency band The pseudorange observation value of represents the ionospheric-free pseudorange.

[0055] Ionospheric-free pseudoranges are used to eliminate ionospheric delay errors in GNSS pseudorange observations, thereby improving position solution accuracy. It should be noted that the error elimination process is completed directly at the GNSS signal acquisition and data processing front end, rather than first acquiring an erroneous position and then correcting it.

[0056] The second method is to obtain the RFID tag location data through the RFID tag and reader; Through active RFID electronic tags and RFID readers, the signal strength (RSSI, Received Signal Strength Indicator) or arrival time difference (TDoA, Time Difference of Arrival) of multiple readers is obtained; Meter-level positioning can be achieved through the signal strength (RSSI) or time difference of arrival (TDoA) of multiple readers, obtaining the RFID location data of workers or vehicles with local precision. The specific process of obtaining RFID location data of workers or vehicles is as follows: (1) Signal strength positioning method; Signal strength attenuation model:

[0057] Where, Indicates the The distance between the reader and the staff, Indicates the reference distance, usually 1 meter; Indicates the The signal strength reflected by the active RFID tag of the staff member received by each reader; Indicates the signal strength reflected at the reference distance; Indicates the path loss index (empirical value, 2 in outdoor free space, 3 to 5 in indoor complex environment), represents random noise that obeys Gaussian distribution. The signal strength reflected by the staff's active RFID electronic tag received by a reader can be directly obtained.

[0058] The signal strength attenuation model is used to infer the The distance between the reader and the staff:

[0059] The coordinates of the staff member are obtained by triangulation based on the distances between the three readers and the staff member and the coordinates of the readers; Among them, The distance between the reader and the worker and the The relationship between the coordinates of a reader and the coordinates of a staff member is as follows:

[0060] Where, Indicates the The coordinates of the reader, Indicates the location coordinates of the staff member's RFID electronic tag; By combining the distances between the three readers and the staff and the relationship between the coordinates of the readers and the coordinates of the staff, the position coordinates of the staff's RFID electronic tags are obtained. .

[0061] (2) Time difference of arrival positioning method; The signal arrival time difference ranging is specifically expressed by the formula:

[0062] Where, Indicates that the staff's active RFID electronic tag has reached the The time of arrival at the first reader The time difference between the reader times, represents the speed of light, Indicates that the staff has arrived The reader and The distance difference between the readers.

[0063]

[0064]

[0065]

[0066] Where, Indicates the The distance between the reader and the staff, Indicates the The coordinates of the reader, Indicates the location coordinates of the staff member's RFID electronic tag; Perform pairwise matching among the three readers, construct a set of equations, and jointly obtain the position coordinates of the staff's RFID electronic tags .

[0067] It should be noted that after the location data is obtained by the RFID electronic tag, the local coordinates of the electronic tag are converted into coordinates in the same global coordinates as the GNSS signal location data through the coordinate conversion formula; wherein the coordinate conversion formula is specifically expressed as:

[0068] Where, Indicates the location coordinates obtained by the RFID electronic tag. The rotation matrix representing the reader installation posture, Represents the global position translation vector of the reader, Represents the position coordinates in the global coordinate system.

[0069] The rotation matrix of the reader installation posture is determined by the RFID reader installation posture; the reader global position translation vector is the position of the reader in the global coordinate system.

[0070] Obtain the RFID electronic tag location data at each moment through the location coordinates in the global coordinate system The third type is position data obtained through the inertial measurement unit IMU; The IMU position data of the staff at the current moment is obtained through the pre-integration model based on the staff's acceleration and angular velocity at several moments before the current moment.

[0071] The displacement increment and velocity increment of the worker are analyzed by the acceleration measured by the IMU; the displacement increment and velocity increment are specifically expressed by the formula:

[0072]

[0073] Where, Indicates the time The acceleration of the staff at that moment, Indicates the A moment, Indicates the A moment, Represents the zero bias estimate of the accelerometer in the inertial measurement unit IMU; Represents the rotation matrix from the IMU body coordinate system to the global coordinate system, represents small increments in time, Indicates the From moment to moment The displacement increment between moments, Indicates the From moment to moment The speed increment between moments.

[0074] Among them, the process of obtaining the rotation matrix from the IMU body coordinate system to the global coordinate system is a well-known technology and will not be described in detail here.

[0075] The attitude increment is obtained by measuring the angular velocity of the IMU; the specific formula is:

[0076] Where, Indicates the time The angular velocity of the staff member at a moment, Represents the zero bias estimate of the gyroscope in the inertial measurement unit IMU, represents an exponential function with a natural constant as the base, Indicates the The time corresponding to the moment, Indicates the The time corresponding to the moment, Indicates the From moment to moment The attitude increment between moments.

[0077] Based on the above displacement increment, velocity increment and posture increment, the IMU position data of the staff at the current moment is obtained through the pre-integration model; wherein, the pre-integration model is a well-known technology and will not be described in detail here.

[0078] Among them, the increment formula above is and It is obtained by calculating the zero-bias estimation equation, specifically:

[0079] Where, Indicates the GNSS signal position coordinates, represents the norm, Indicates the The position at a moment, Represents the predicted position coordinates; It means finding the parameters that minimize the objective function. Represents the bias estimate and ; Represents the number of all moments in the preset time window; wherein, the width of the preset time window is 10 moments before the current moment, wherein in this embodiment, the width of the preset time window is not specifically limited, and the implementer can determine it according to the specific situation.

[0080] Step S003: Switching between indoor and outdoor positioning modes based on location data and GNSS signal strength.

[0081] It should be noted that when staff or vehicles approach buildings, their GNSS signals will be interfered with by the surrounding buildings, causing GNSS signal attenuation. That is, the closer to the interfering building, the more serious the GNSS signal attenuation; that is, when staff walk from outdoors to indoors, their GNSS signal gradually attenuates. Therefore, by setting a threshold during the signal attenuation process to monitor, when certain conditions are met, it is necessary to switch the positioning mode to complete seamless integrated navigation.

[0082] Specifically, the weight of each satellite is obtained according to the signal-to-noise ratio of each satellite; the weight of each satellite is specifically expressed by the formula:

[0083] Where, Indicates the The signal-to-noise ratio of the satellites, Indicates the The signal-to-noise ratio of the satellites, Indicates the number of all satellites, Indicates the The weight of the signal-to-noise ratio of each satellite.

[0084] The signal-to-noise ratios of all satellites are adjusted by the weight of each satellite's signal-to-noise ratio to obtain the adjusted signal-to-noise ratio of the GNSS signal at each moment. The adjusted signal-to-noise ratio of the GNSS signal at each moment is specifically expressed by the formula:

[0085] Where, Indicates the The signal-to-noise ratio of the satellites, Indicates the The weight of the satellite signal-to-noise ratio, Indicates the number of all satellites, Indicates the adjusted signal-to-noise ratio of the GNSS signal at each moment.

[0086] Based on the number of all reference satellites, the position accuracy spread factor at each moment, and the adjusted signal-to-noise ratio of the GNSS signal, the indoor and outdoor positioning modes are switched. The specific process of positioning mode switching is as follows: When the staff is outdoors, they first use the first positioning mode to locate and obtain the GNSS signal every second; when the continuous When the GNSS signal of 10 seconds meets the preset first signal quality reference range of medium and low quality, the positioning mode is switched from the first positioning mode to the second positioning mode. Otherwise, the positioning mode is not switched and the first positioning mode is maintained. No GNSS signal is detected for seconds or continuously When the RFID reader detects an active RFID electronic tag, it switches the positioning mode from the second positioning mode to the third positioning mode. Otherwise, it does not switch the positioning mode and maintains the second positioning mode. When the GNSS signal of 100 seconds meets the preset second signal quality reference range of medium to low quality, the positioning mode is automatically switched back to the first positioning mode from the third positioning mode; otherwise, the positioning mode is not switched and the third positioning mode is maintained; in, Indicates the preset reference number; Among them, the preset first signal quality reference range is: C / N <38 dB-Hz, number of satellites <4, PDOP >5; the preset second signal quality reference range is: C / N >40 dB-Hz, number of satellites ≥6, PDOP <2; among them, C / N represents signal-to-noise ratio, dB-Hz represents decibel-hertz; PDOP represents position precision spread factor.

[0087] Step S004: Obtain the navigation position of the staff member at the current moment based on the GNSS signal position data, RFID electronic tag position data, IMU position data and the positioning mode corresponding to the current moment.

[0088] It should be noted that when different types of position data are fused through extended Kalman filtering, if the sensor times are not aligned, there will be errors in the time corresponding to the collected data. Therefore, after fusing different types of position data, the position of the person may be misjudged. Therefore, it is necessary to align the times of all sensors.

[0089] It should be further explained that, since different types of location data corresponding to different positioning modes have different reliabilities, different location data are assigned different weights in different positioning modes.

[0090] Specifically, the weights corresponding to different position data in each positioning mode are obtained. The weights corresponding to different position data in each positioning mode are all preset values; in the first positioning mode, the weight of GNSS signal position data is 0.9, the weight of RFID electronic tag position data is 0, and the weight of IMU position data is 0.1; in the second positioning mode, the weight of GNSS signal position data is 0.5, the weight of RFID electronic tag position data is 0.3, and the weight of IMU position data is 0.2; in the third positioning mode, the weight of GNSS signal position data is 0, the weight of RFID electronic tag position data is 0.8, and the weight of IMU position data is 0.2.

[0091] The extended Kalman filter algorithm is used to fuse the weights corresponding to the different location data in each positioning mode, the current GNSS signal location data, the RFID tag location data, and the IMU location data to obtain the current navigation location of the worker. The extended Kalman filter algorithm is a well-known technology and will not be described in detail here.

[0092] like Figure 2 As shown, the second aspect of the present invention is to provide a wind farm indoor and outdoor seamless integration navigation system, comprising the following steps: Data acquisition module 101: used to obtain the distance between the reader and the worker through the RFID electronic tag and the reader, and then obtain the time difference between the RFID electronic tag reaching different readers; and continuously measure the acceleration and angular velocity of the worker at each moment through the inertial measurement unit (IMU); Position analysis module 102: used to obtain the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system; based on the relationship between the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system, some satellites are eliminated and the remaining satellites are recorded as reference satellites; GNSS signal position data at each moment is obtained through the reference satellite and the GNSS receiving device; RFID electronic tag position data at each moment is obtained based on the distance between the reader and the staff member and the time difference between the RFID electronic tag reaching different readers; based on the acceleration and angular velocity of the staff member at several moments before the current moment, the IMU position data of the staff member at the current moment is obtained through a pre-integration model; Positioning switching module 103: used to obtain the position accuracy spread factor and the signal-to-noise ratio of each reference satellite at each moment, obtain the weight of each reference satellite based on the signal-to-noise ratio of each reference satellite; obtain the adjusted signal-to-noise ratio of the GNSS signal at each moment through the weight of each reference satellite and the signal-to-noise ratio of all reference satellites; and switch the indoor and outdoor positioning modes based on the number of all reference satellites, the position accuracy spread factor at each moment, and the adjusted signal-to-noise ratio of the GNSS signal; The fusion navigation module 104 is used to obtain the navigation position of the staff at the current moment based on the GNSS signal position data, RFID electronic tag position data, IMU position data and the positioning mode corresponding to the current moment.

[0093] A third aspect of the present invention is to provide an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a method for seamlessly integrating indoor and outdoor navigation of a wind farm is implemented.

[0094] A fourth aspect of the present invention is to provide a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, a method for seamlessly integrating indoor and outdoor navigation of a wind farm is implemented.

[0095] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, optical storage, etc.) containing computer-usable program code.

[0096] The present invention is described with reference to flowcharts and / or block diagrams of methods, systems, and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the present invention.

Claims

1. A wind farm indoor and outdoor seamless fusion navigation method, characterized in that: include: The distance between the reader and the worker is obtained through the RFID electronic tag and the reader, and then the time difference between the RFID electronic tag reaching different readers is obtained; The acceleration and angular velocity of the worker at each moment are continuously measured through the inertial measurement unit (IMU); Obtaining the position vectors of the satellites and the receiver in the geocentric coordinate system; eliminating some satellites based on the relationship between the position vectors of the satellites and the receiver in the geocentric coordinate system, and recording the remaining satellites as reference satellites. Obtain GNSS signal position data at each moment through reference satellites and GNSS receiving equipment; The RFID tag location data at each moment is obtained based on the distance between the reader and the worker and the time difference between the RFID tag reaching different readers. The IMU location data of the worker at the current moment is obtained through a pre-integration model based on the worker's acceleration and angular velocity at several moments before the current moment. Obtain the position accuracy spread factor and the signal-to-noise ratio of each reference satellite at each moment, and obtain the weight of each reference satellite based on the signal-to-noise ratio of each reference satellite; obtain the adjusted signal-to-noise ratio of the GNSS signal at each moment through the weight of each reference satellite and the signal-to-noise ratio of all reference satellites; switch between indoor and outdoor positioning modes based on the number of all reference satellites, the position accuracy spread factor at each moment, and the adjusted signal-to-noise ratio of the GNSS signal; The navigation position of the staff at the current moment is obtained based on the current GNSS signal position data, RFID electronic tag position data, IMU position data and the positioning mode corresponding to the current moment.

2. A wind farm indoor and outdoor seamless fusion navigation method according to claim 1, characterized in that: Eliminating some satellites based on the relationship between the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system includes: Where, represents the position vector of each satellite in the geocentric coordinate system, represents the position vector of the receiver in the geocentric coordinate system, represents the modulus of the vector, represents the inverse sine function, Indicates the elevation angle of each satellite; The satellites whose elevation angle is less than the preset elevation angle threshold are eliminated.

3. A wind farm indoor and outdoor seamless fusion navigation method according to claim 1, characterized in that: The method of obtaining the RFID electronic tag location data at each moment based on the distance between the reader and the worker and the time difference between the RFID electronic tag reaching different readers includes: The RFID tag location data at each moment is obtained through signal strength positioning method or arrival time difference positioning method; (1) The specific process of obtaining the RFID electronic tag location data at each moment through the signal strength positioning method is as follows: Signal strength attenuation model: Where, Indicates the The distance between the reader and the staff, Indicates the reference distance; Indicates the The signal strength reflected by the active RFID tag of the staff member received by each reader; Indicates the signal strength reflected at the reference distance; represents the path loss exponent, represents random noise that follows a Gaussian distribution; The signal strength attenuation model is used to infer the The distance between the reader and the staff: Among them, The distance between the reader and the worker and the The relationship between the coordinates of a reader and the coordinates of a staff member is as follows: Where, Indicates the The coordinates of the reader, Indicates the location coordinates of the staff member's RFID electronic tag; By combining the distances between the three readers and the staff and the relationship between the coordinates of the readers and the coordinates of the staff, the position coordinates of the staff's RFID electronic tags are obtained. ; (2) The specific process of obtaining the RFID electronic tag location data at each moment through the arrival time difference positioning method is as follows: The signal arrival time difference ranging is specifically expressed by the formula: Where, Indicates that the staff's active RFID electronic tag has reached the The time of arrival at the first reader The time difference between the reader times, represents the speed of light, Indicates that the staff has arrived The reader and The distance difference between the readers; Where, Indicates the The distance between the reader and the staff, Indicates the The coordinates of the reader, Indicates the location coordinates of the staff member's RFID electronic tag; Perform pairwise matching among the three readers, construct a set of equations, and jointly obtain the position coordinates of the staff's RFID electronic tags ; The obtained RFID tag location coordinates The coordinate conversion formula is used to convert the position coordinates in the global coordinate system. The coordinate conversion formula is specifically expressed as: Where, Indicates the location coordinates obtained by the RFID electronic tag. The rotation matrix representing the reader installation posture, Represents the global position translation vector of the reader, Represents the position coordinates in the global coordinate system; The position data of the RFID electronic tag at each moment is obtained through the position coordinates in the global coordinate system.

4. A wind farm indoor and outdoor seamless fusion navigation method according to claim 1, characterized in that: The method of obtaining the IMU position data of the staff member at the current moment through a pre-integration model based on the acceleration and angular velocity of the staff member at several moments before the current moment includes: The displacement increment and velocity increment of the worker are obtained by the acceleration measured by the IMU; the displacement increment and velocity increment are specifically expressed by the formula: Where, Indicates the time The acceleration of the staff at that moment, Indicates the A moment, Indicates the A moment, Represents the zero bias estimate of the accelerometer in the inertial measurement unit IMU; Represents the rotation matrix from the IMU body coordinate system to the global coordinate system, represents small increments in time, Indicates the From moment to moment The displacement increment between moments, Indicates the From moment to moment The speed increment between moments; The attitude increment is obtained by measuring the angular velocity of the IMU. The attitude increment is specifically expressed by the formula: Where, Indicates the time The angular velocity of the staff member at a moment, Represents the zero bias estimate of the gyroscope in the inertial measurement unit IMU, represents an exponential function with a natural constant as the base, Indicates the The time corresponding to the moment, Indicates the The time corresponding to the moment, Indicates the From moment to moment The increment of posture between moments; According to the displacement increment, the velocity increment and the attitude increment, the IMU position data of the staff member at the current moment is obtained through a pre-integration model; Among them, the displacement increment, the velocity increment and the posture increment formula are and It is obtained by calculating the zero-bias estimation equation, which is specifically expressed as: Where, Indicates the GNSS signal position coordinates, represents the norm, Indicates the The position at a moment, Represents the predicted position coordinates; It means finding the parameters that minimize the objective function. Represents the bias estimate and ; Indicates the number of all moments in the preset time window.

5. A wind farm indoor and outdoor seamless fusion navigation method according to claim 1, characterized in that: The weight of each reference satellite is obtained according to the signal-to-noise ratio of each reference satellite; The adjusted signal-to-noise ratio of the GNSS signal at each moment is obtained by using the weight of each reference satellite and the signal-to-noise ratio of all reference satellites, including: Where, Indicates the The signal-to-noise ratio of the reference satellites, Indicates the The signal-to-noise ratio of the reference satellites, represents the number of all reference satellites, Indicates the The weight of the signal-to-noise ratio of each reference satellite; Where, Indicates the adjusted signal-to-noise ratio of the GNSS signal at each moment.

6. A wind farm indoor and outdoor seamless fusion navigation method according to claim 1, characterized in that: The switching of indoor and outdoor positioning modes according to the number of all reference satellites, the position accuracy spread factor at each moment, and the adjusted signal-to-noise ratio of the GNSS signal includes: When the staff is outdoors, they first use the first positioning mode to locate and obtain the GNSS signal every second; when the continuous When the GNSS signal of 10 seconds meets the preset first signal quality reference range of medium and low quality, the positioning mode is switched from the first positioning mode to the second positioning mode. Otherwise, the positioning mode is not switched and the first positioning mode is maintained. No GNSS signal is detected for seconds or continuously When the RFID reader detects an active RFID electronic tag, it switches the positioning mode from the second positioning mode to the third positioning mode. Otherwise, it does not switch the positioning mode and maintains the second positioning mode. When the GNSS signal of 100 seconds meets the preset second signal quality reference range of medium to low quality, the positioning mode is automatically switched back to the first positioning mode from the third positioning mode; otherwise, the positioning mode is not switched and the third positioning mode is maintained; in, Indicates the preset reference number; Among them, the preset first signal quality reference range is: C / N <38 dB-Hz, number of satellites <4, PDOP >5; the preset second signal quality reference range is: C / N >40 dB-Hz, number of satellites ≥6, PDOP <2; among them, C / N represents signal-to-noise ratio, dB-Hz represents decibel-hertz; PDOP represents position precision spread factor.

7. A wind farm indoor and outdoor seamless fusion navigation method according to claim 6, characterized in that: The method of obtaining the navigation position of the staff member at the current moment according to the current GNSS signal position data, the RFID electronic tag position data, the IMU position data and the positioning mode corresponding to the current moment includes: Get the weights corresponding to different location data in each positioning mode; The navigation position of the staff at the current moment is obtained by fusing the position data using the weights corresponding to different position data in each positioning mode, the current GNSS signal position data, the RFID electronic tag position data, and the IMU position data through the extended Kalman filter algorithm.

8. A wind farm indoor and outdoor seamless integration navigation system, characterized by: include: Data acquisition module: used to obtain the distance between the reader and the staff through the RFID electronic tag and the reader, and then obtain the time difference between the RFID electronic tag reaching different readers; The acceleration and angular velocity of the worker at each moment are continuously measured through the inertial measurement unit (IMU); Position analysis module: used to obtain the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system; based on the relationship between the position vector of the satellite in the geocentric coordinate system and the position vector of the receiver in the geocentric coordinate system, some satellites are eliminated and the remaining satellites are recorded as reference satellites; Obtain GNSS signal position data at each moment through reference satellites and GNSS receiving equipment; The RFID tag location data at each moment is obtained based on the distance between the reader and the worker and the time difference between the RFID tag reaching different readers. The IMU location data of the worker at the current moment is obtained through a pre-integration model based on the worker's acceleration and angular velocity at several moments before the current moment. Positioning switching module: used to obtain the position accuracy spread factor and the signal-to-noise ratio of each reference satellite at each moment, and obtain the weight of each reference satellite based on the signal-to-noise ratio of each reference satellite; obtain the adjusted signal-to-noise ratio of the GNSS signal at each moment through the weight of each reference satellite and the signal-to-noise ratio of all reference satellites; switch between indoor and outdoor positioning modes based on the number of all reference satellites, the position accuracy spread factor at each moment, and the adjusted signal-to-noise ratio of the GNSS signal; Fusion navigation module: used to obtain the navigation position of the staff at the current moment based on the current GNSS signal position data, RFID electronic tag position data, IMU position data and the positioning mode corresponding to the current moment.

9. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for seamlessly integrating indoor and outdoor navigation of a wind farm as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for seamlessly integrating indoor and outdoor navigation of a wind farm according to any one of claims 1 to 7 is implemented.

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