A method and system for calculating positioning accuracy based on position information

Abstract

The present invention provides a positioning accuracy calculation method and system based on position information, which sets a position information positioning accuracy random array of multi-point positioning reference and positioning distribution error at each point on the edge of the reference distribution standard point position, collects and detects the multi-point positioning reference and positioning distribution error information; wirelessly transmits and receives the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits them to a position positioning calculation cloud processing center; uses the position information and positioning distribution error neural network to perform intelligent neural network deep learning recognition on the multi-point positioning reference and positioning distribution error information, identifies the feature information of the randomly distributed points and the feature information of the distribution point errors, and performs weight calculation of the multi-point positioning reference and positioning distribution error information; performs weight sorting and smoothing processing on the randomly distributed positioning points, and performs precise intelligent error elimination positioning accuracy calculation based on the random distribution cross reference of the position information.

Description

Technical Field

[0001] The present invention relates to the technical field of complex positioning high-precision intelligent computing, and in particular to a positioning accuracy computing method and system based on position information. Background Art

[0002] At this stage, as the requirements for positioning accuracy continue to increase, it is becoming increasingly important to ensure the accuracy of positioning accuracy calculation and reduce errors. Current problems include: how to set the location information of multi-point positioning references and positioning distribution errors and obtain initial information, how to perform signal coverage and fast and efficient transmission within the positioning signal area, how to identify point information and point error information for positioning distribution error information processing, how to perform fast and accurate calculation of positioning accuracy based on position information and eliminate interference errors, etc. Therefore, it is necessary to propose a positioning accuracy calculation method and system based on position information to at least partially solve the problems existing in the existing technology. Summary of the Invention

[0003] A series of simplified concepts are introduced in the summary of the invention, which will be further explained in detail in the specific implementation method. The summary of the invention does not mean to attempt to limit the key features and necessary technical features of the technical solution for protection, nor does it mean to attempt to determine the scope of protection of the technical solution for protection.

[0004] To at least partially solve the above problems, the present invention provides a method for calculating positioning accuracy based on position information, comprising:

[0005] S100, setting a multi-point positioning reference and positioning distribution error position information positioning accuracy random array at each point on the edge of the reference distribution standard point position, and collecting and detecting multi-point positioning reference and positioning distribution error information;

[0006] S200, wirelessly transmitting and receiving the multi-point positioning reference, positioning distribution error information, and parameter data in the positioning signal area, and transmitting them to the position positioning computing cloud processing center;

[0007] S300, performing intelligent neural network deep learning recognition on multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network, identifying randomly distributed point feature information and distributed point error feature information, and performing weight calculation on the multi-point positioning reference and positioning distribution error information;

[0008] S400, based on the multi-point positioning reference and positioning distribution error information weight calculation data, the weight sorting and smoothing processing of the randomly distributed positioning points are performed, and the precise intelligent error elimination positioning accuracy calculation based on the random distribution cross reference of the position information is performed.

[0009] Preferably, S100 includes:

[0010] S101, setting wireless positioning signal transceivers at each point on the edge of the reference distribution standard point position, and each three wireless positioning signal transceivers have a wireless positioning signal receiving and transmitting range covering the center of the three wireless positioning signal transceivers;

[0011] S102, setting a millimeter wave radar at the center of the reference distribution standard point position, scanning in real time to see if there are randomly distributed points on the detection point position, and obtaining radar detection information of the randomly distributed points.

[0012] Preferably, S200 includes:

[0013] S201, setting a wireless positioning signal converter at each point near the center area of ​​the reference distribution standard point position to convert any wireless positioning signal into position coordinate parameters;

[0014] S202, transmitting the location coordinate parameters to the location positioning computing cloud processing center via a wireless transmission network;

[0015] S203, through the Bluetooth and WIFI wireless transmission network, the multi-point positioning reference and positioning distribution error information and parameter data are wirelessly transmitted and received in the positioning signal area, and transmitted to the position positioning computing cloud processing center.

[0016] Preferably, S300 includes:

[0017] S301, setting up an AI deep learning interference recognition and analysis module and integrating it into the position information and positioning distribution error neural network;

[0018] S302, performing intelligent neural network deep learning recognition on multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network, and performing processing and analysis; determining whether there are random distribution point features and distribution point error features at the points; and identifying random distribution point feature information or distribution point error feature information;

[0019] S303: Perform multi-point positioning reference and positioning distribution error information weight calculation.

[0020] Preferably, S400 includes:

[0021] S401, performing data processing and integration on multi-point positioning reference and positioning distribution error information weight calculation data;

[0022] S402, based on data processing integration, weight sorting of randomly distributed positioning points is performed through the location positioning computing cloud processing center;

[0023] S403, based on the weight sorting results of the randomly distributed positioning points, the weight data of the randomly distributed positioning points are smoothed by data smoothing, and a precise intelligent error elimination positioning accuracy calculation based on the random distribution cross reference of the position information is performed.

[0024] The present invention provides a positioning accuracy calculation system based on position information, comprising:

[0025] The random array module of the distribution edge position information sets a random array of the position information of the multi-point positioning reference and the positioning distribution error at each point on the edge of the reference distribution standard point position, and collects and detects the multi-point positioning reference and positioning distribution error information;

[0026] The regional positioning signal transmitting and receiving module wirelessly transmits and receives the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits them to the position positioning computing cloud processing center;

[0027] The position positioning neural network deep learning module uses the position information and positioning distribution error neural network to perform intelligent neural network deep learning recognition on multi-point positioning reference and positioning distribution error information, identify the feature information of randomly distributed points and the feature information of distributed point errors, and calculate the weights of multi-point positioning reference and positioning distribution error information;

[0028] The intelligent error elimination positioning accuracy calculation module calculates data based on the weight of multi-point positioning reference and positioning distribution error information, sorts the weights of randomly distributed positioning points and performs smoothing processing, and performs precise intelligent error elimination positioning accuracy calculation based on random distribution cross-reference of position information.

[0029] Preferably, the random array module for distributing edge position information includes:

[0030] The positioning signal transceiver coverage submodule sets wireless positioning signal transceivers at each point on the edge of the reference distribution standard point position. Every three wireless positioning signal transceivers have a wireless positioning signal transceiver range covering the center of the three wireless positioning signal transceivers.

[0031] The meter-wave radar scanning detection submodule sets a millimeter-wave radar at the center of the reference distribution standard point position, and scans the detection points in real time to see if there are randomly distributed points, and obtains radar detection information of the randomly distributed points.

[0032] Preferably, the regional positioning signal transmitting and receiving module includes:

[0033] The positioning signal position parameter conversion submodule sets a wireless positioning signal converter at each point near the center area of ​​the reference distribution standard point position to convert any wireless positioning signal into position coordinate parameters;

[0034] The wireless transmission network cloud transmission submodule transmits the location coordinate parameters to the location positioning computing cloud processing center through the wireless transmission network;

[0035] The Bluetooth and WIFI wireless transmission network submodule uses the Bluetooth and WIFI wireless transmission network to wirelessly transmit and receive the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits them to the position positioning computing cloud processing center.

[0036] Preferably, the location positioning neural network deep learning module includes:

[0037] Interference identification and analysis AI integrated submodule, setting up an AI deep learning interference identification and analysis module and integrating it into the location information and positioning distribution error neural network;

[0038] The processing and analysis feature determination submodule uses the position information and positioning distribution error neural network to perform intelligent neural network deep learning recognition on the multi-point positioning reference and positioning distribution error information, and performs processing and analysis; determines whether there are random distribution point features and whether there are distribution point error features on the points; and identifies random distribution point feature information or distribution point error feature information;

[0039] The error information weight calculation submodule performs multi-point positioning reference and positioning distribution error information weight calculation.

[0040] Preferably, the intelligent error elimination positioning accuracy calculation module includes:

[0041] The data processing and integration submodule processes and integrates the multi-point positioning reference and positioning distribution error information weight calculation data;

[0042] The random distribution point weight sorting submodule performs weight sorting of the randomly distributed points through the location positioning computing cloud processing center based on data processing integration;

[0043] The cross-reference intelligent precision calculation submodule performs data smoothing on the weighted data of the randomly distributed positioning points according to the weight sorting results of the randomly distributed positioning points, and performs precise intelligent error elimination positioning precision calculation based on the random distribution cross-reference based on the position information.

[0044] Compared with the prior art, the present invention has at least the following beneficial effects:

[0045] The present invention provides a positioning accuracy calculation method and system based on position information. The present invention provides a positioning accuracy calculation method based on position information. The method comprises the following steps: setting a multi-point positioning reference and positioning distribution error positioning accuracy random array at each point on the edge of a reference distribution standard point position, collecting and detecting the multi-point positioning reference and positioning distribution error information; wirelessly transmitting and receiving the multi-point positioning reference and positioning distribution error information and parameter data in a positioning signal area, and transmitting the multi-point positioning reference and positioning distribution error information to a position positioning calculation cloud processing center; performing intelligent neural network deep learning recognition on the multi-point positioning reference and positioning distribution error information through a position information and positioning distribution error neural network, identifying randomly distributed point feature information and distributed point error feature information, and performing weight calculation of the multi-point positioning reference and positioning distribution error information; performing weight sorting and smoothing processing on the randomly distributed positioning points based on the multi-point positioning reference and positioning distribution error information weight calculation data, and performing precise intelligent difference elimination positioning accuracy calculation based on the random distribution cross reference of the position information; further eliminating interference errors, and greatly improving the positioning accuracy and calculation speed of the positioning information; and being capable of performing high-precision calculation of multi-point complex positioning, and greatly improving the positioning error elimination processing capability for a variety of randomly distributed points.

[0046] The present invention describes a method and system for calculating positioning accuracy based on location information. Other advantages, objectives, and features of the present invention will be partially reflected in the following description, and will also be understood by those skilled in the art through research and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0048] Figure 1 This is a step diagram of a positioning accuracy calculation method based on position information described in the present invention.

[0049] Figure 2 This is a diagram of an embodiment of a method for calculating positioning accuracy based on position information described in the present invention.

[0050] Figure 3 This is a block diagram of a positioning accuracy calculation system based on position information described in the present invention. DETAILED DESCRIPTION

[0051] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments so that those skilled in the art can implement the invention with reference to the description. Figure 1-3 As shown, the present invention provides a method for calculating positioning accuracy based on position information, comprising:

[0052] S100, setting a multi-point positioning reference and positioning distribution error position information positioning accuracy random array at each point on the edge of the reference distribution standard point position, and collecting and detecting multi-point positioning reference and positioning distribution error information;

[0053] S200, wirelessly transmitting and receiving the multi-point positioning reference, positioning distribution error information, and parameter data in the positioning signal area, and transmitting them to the position positioning computing cloud processing center;

[0054] S300, performing intelligent neural network deep learning recognition on multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network, identifying randomly distributed point feature information and distributed point error feature information, and performing weight calculation on the multi-point positioning reference and positioning distribution error information;

[0055] S400, based on the multi-point positioning reference and positioning distribution error information weight calculation data, the weight sorting and smoothing processing of the randomly distributed positioning points are performed, and the precise intelligent error elimination positioning accuracy calculation based on the random distribution cross reference of the position information is performed.

[0056] The working principle of the above technical solution is: a positioning accuracy calculation method based on position information, including: setting a random array of position information positioning accuracy of multi-point positioning references and positioning distribution errors at each point on the edge of the reference distribution standard point position, collecting and detecting multi-point positioning reference and positioning distribution error information; wirelessly transmitting and receiving the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmitting them to the position positioning calculation cloud processing center; performing intelligent neural network deep learning recognition on the multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network, identifying the randomly distributed point feature information and the distribution point error feature information, and performing multi-point positioning reference and positioning distribution error information weight calculation; according to the multi-point positioning reference and positioning distribution error information weight calculation data, performing weight sorting and smoothing processing on the randomly distributed positioning points, and performing precise intelligent error elimination positioning accuracy calculation based on random distribution cross reference of position information.

[0057] The beneficial effects of the above technical solution are as follows: a positioning accuracy calculation method based on position information of the present invention sets a random array of position information positioning accuracy of multi-point positioning references and positioning distribution errors at each point on the edge of the reference distribution standard point position, collects and detects multi-point positioning reference and positioning distribution error information; wirelessly transmits and receives the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits them to the position positioning calculation cloud processing center; through the position information and positioning distribution error neural network, the multi-point positioning reference and positioning distribution error information are subjected to intelligent neural network deep learning recognition, the randomly distributed point feature information and the distribution point error feature information are identified, and the multi-point positioning reference and positioning distribution error information weight calculation is performed; according to the multi-point positioning reference and positioning distribution error information weight calculation data, the randomly distributed point weights are sorted and smoothed, and the random distribution cross-reference based on the position information is accurately and intelligently eliminated. Positioning accuracy calculation can be performed; high-precision calculation of multi-point complex positioning can be performed, greatly improving the positioning error elimination processing capability for a variety of randomly distributed points.

[0058] In one embodiment, S100 includes:

[0059] S101, setting wireless positioning signal transceivers at each point on the edge of the reference distribution standard point position, and each three wireless positioning signal transceivers have a wireless positioning signal receiving and transmitting range covering the center of the three wireless positioning signal transceivers;

[0060] S102, setting a millimeter wave radar at the center of the reference distribution standard point position, scanning in real time to see if there are randomly distributed points on the detection point position, and obtaining radar detection information of the randomly distributed points.

[0061] The working principle of the above technical solution is as follows: wireless positioning signal transceivers are set at each point on the edge of the reference distribution standard point position, and every three wireless positioning signal transceivers have a wireless positioning signal receiving and transmitting range covering the center of the three wireless positioning signal transceivers; a millimeter wave radar is set at the center of the reference distribution standard point position to scan in real time whether there are randomly distributed points on the detection point, and obtain radar detection information of the randomly distributed points; the wireless positioning signal transceiver includes: a three-dimensional positioning detection wave trigger unit, a spherical detection wave transmitting unit, a detection reflection wave receiving unit, a femtosecond clock pulse unit and a signal time difference correction unit. Unit; the positioning detection wave trigger unit triggers the positioning detection wave pulse generator to generate a stereo positioning detection wave pulse and triggers the femtosecond clock pulse unit to start timing. The stereo positioning detection wave pulse is transmitted to the spherical detection wave transmitting unit to transmit the spherical detection wave to the positioning detection space with the wireless positioning signal transceiver as the sphere center; when the spherical detection wave encounters the object to be positioned, it is reflected to form a positioning reflection detection wave; the detection reflection wave receiving unit receives the positioning reflection detection wave, and the femtosecond clock pulse unit completes a detection timing segment; the signal time difference correction unit performs detection signal time difference correction on the detection timing segment to compensate The signal transmission conversion operation error between the device units is used to obtain the detection correction timing section; the precise distance of the object to be positioned is calculated based on the detection correction timing section and the stereo positioning detection wave speed; the positioning azimuth angle of the object to be positioned is calculated based on the azimuth of the reflected wave of the spherical detection wave of the object to be positioned; stereo precision positioning and stereo precision calculation of stereo positioning based on the stereo precision positioning position information are performed; when the positioning detection space reaches the farthest detection distance of the wireless positioning signal transceiver, the first wireless positioning signal transceiver position is used as the reference position, and the double farthest detection distance of the wireless positioning signal transceiver is used as the path edge, and the equilateral triangle is used to calculate the positioning azimuth angle of the object to be positioned based on the reflected wave azimuth of the spherical detection wave of the object to be positioned. The second wireless positioning signal transceiver and the third wireless positioning signal transceiver are arranged in a shape of a circle, so that every three wireless positioning signal transceivers have a wireless positioning signal receiving and transmitting range covering the centers of the three wireless positioning signal transceivers; the three-dimensional positioning detection waves include: multi-band electromagnetic waves and multi-wavelength light waves; preliminary detection is carried out through millimeter wave radar, and real-time scanning is performed to see whether there are randomly distributed points on the detection points. When the object to be detected is located at the randomly distributed points, the wireless positioning signal transceivers near the randomly distributed points are started to perform three-dimensional precise positioning and three-dimensional positioning precise calculation based on the three-dimensional precise positioning position information.

[0062] The beneficial effects of the above technical solution are as follows: wireless positioning signal transceivers are set at each point on the edge of the reference distribution standard point position, and every three wireless positioning signal transceivers have a wireless positioning signal receiving and transmitting range covering the center of the three wireless positioning signal transceivers; a millimeter wave radar is set at the center of the reference distribution standard point position to scan in real time whether there are randomly distributed points on the detection point, and obtain radar detection information of the randomly distributed points; the wireless positioning signal transceiver includes: a three-dimensional positioning detection wave trigger unit, a spherical detection wave transmitting unit, a detection reflection wave receiving unit, a femtosecond clock pulse unit and a signal time difference correction unit. Unit; the positioning detection wave trigger unit triggers the positioning detection wave pulse generator to generate a stereo positioning detection wave pulse and triggers the femtosecond clock pulse unit to start timing. The stereo positioning detection wave pulse is transmitted to the spherical detection wave transmitting unit to transmit the spherical detection wave to the positioning detection space with the wireless positioning signal transceiver as the sphere center; when the spherical detection wave encounters the object to be positioned, it is reflected to form a positioning reflection detection wave; the detection reflection wave receiving unit receives the positioning reflection detection wave, and the femtosecond clock pulse unit completes a detection timing segment; the signal time difference correction unit performs detection signal time difference correction on the detection timing segment to compensate The signal transmission conversion operation error between the device units is used to obtain the detection correction timing section; the precise distance of the object to be positioned is calculated based on the detection correction timing section and the stereo positioning detection wave speed; the positioning azimuth angle of the object to be positioned is calculated based on the azimuth of the reflected wave of the spherical detection wave of the object to be positioned; stereo precision positioning and stereo precision calculation of stereo positioning based on the stereo precision positioning position information are performed; when the positioning detection space reaches the farthest detection distance of the wireless positioning signal transceiver, the first wireless positioning signal transceiver position is used as the reference position, and the double farthest detection distance of the wireless positioning signal transceiver is used as the path edge, and the equilateral triangle is used to calculate the positioning azimuth angle of the object to be positioned based on the reflected wave azimuth of the spherical detection wave of the object to be positioned. The second wireless positioning signal transceiver and the third wireless positioning signal transceiver are arranged in a shape of a circle, so that every three wireless positioning signal transceivers have a wireless positioning signal receiving and transmitting range covering the centers of the three wireless positioning signal transceivers; the three-dimensional positioning detection waves include: multi-band electromagnetic waves and multi-wavelength light waves; preliminary detection is carried out through millimeter wave radar, and real-time scanning is performed to see whether there are randomly distributed points on the detection points. When the object to be detected is located at the randomly distributed points, the wireless positioning signal transceivers near the randomly distributed points are started to perform three-dimensional precise positioning and three-dimensional positioning precise calculation based on the three-dimensional precise positioning position information.

[0063] In one embodiment, S200 includes:

[0064] S201, setting a wireless positioning signal converter at each point near the center area of ​​the reference distribution standard point position to convert any wireless positioning signal into position coordinate parameters;

[0065] S202, transmitting the location coordinate parameters to the location positioning computing cloud processing center via a wireless transmission network;

[0066] S203, through the Bluetooth and WIFI wireless transmission network, the multi-point positioning reference and positioning distribution error information and parameter data are wirelessly transmitted and received in the positioning signal area, and transmitted to the position positioning computing cloud processing center.

[0067] The working principle of the above technical solution is: by setting up wireless positioning signal converters at each point near the center area of ​​the reference distribution standard point position, any wireless positioning signal is converted into position coordinate parameters; the position coordinate parameters are transmitted to the position positioning computing cloud processing center through the wireless transmission network; through the Bluetooth and WIFI wireless transmission network, the multi-point positioning reference and positioning distribution error information and parameter data are wirelessly transmitted and received in the positioning signal area, and transmitted to the position positioning computing cloud processing center.

[0068] The beneficial effects of the above technical solution are: setting a wireless positioning signal converter at each point near the center area of ​​the reference distribution standard point position to convert any wireless positioning signal into position coordinate parameters; transmitting the position coordinate parameters to the position positioning computing cloud processing center through the wireless transmission network; through the Bluetooth and WIFI wireless transmission network, the multi-point positioning reference and positioning distribution error information and parameter data are wirelessly transmitted and received in the positioning signal area, and transmitted to the position positioning computing cloud processing center.

[0069] In one embodiment, S300 includes:

[0070] S301, setting up an AI deep learning interference recognition and analysis module and integrating it into the position information and positioning distribution error neural network;

[0071] S302, performing intelligent neural network deep learning recognition on multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network, and performing processing and analysis; determining whether there are random distribution point features and distribution point error features at the points; and identifying random distribution point feature information or distribution point error feature information;

[0072] S303: Perform multi-point positioning reference and positioning distribution error information weight calculation.

[0073] The working principle of the above technical solution is as follows: by setting up an AI deep learning interference recognition and analysis module and integrating it into the position information and positioning distribution error neural network; performing intelligent neural network deep learning recognition and processing analysis on multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network; judging whether there are randomly distributed point features and whether there are distributed point error features at the point; identifying random distribution point feature information or distributed point error feature information; performing weight calculation of multi-point positioning reference and positioning distribution error information; calculating the weight of multi-point positioning reference and positioning distribution error information:

[0074]

[0075] Among them, TDWk represents the weight of multi-point positioning reference and positioning distribution error information, SDK represents the total number of reference distribution standard points, i represents the i-th reference distribution standard point, j represents the next adjacent reference distribution standard point of the i-th reference distribution standard point, Li represents the detection distance between the i-th reference distribution standard point and the randomly distributed point, and Lj represents the detection distance between the j-th adjacent reference distribution standard point and the randomly distributed point.

[0076] The beneficial effects of the above technical solution are as follows: setting up an AI deep learning interference identification and analysis module and integrating it into the position information and positioning distribution error neural network; performing intelligent neural network deep learning identification and processing analysis on multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network; judging whether there are random distribution point features and whether there are distribution point error features on the points; identifying random distribution point feature information or distribution point error feature information; and performing weight calculation of multi-point positioning reference and positioning distribution error information;

[0077] Calculate the weights of multi-point positioning reference and positioning distribution error information: where TDWk represents the weights of multi-point positioning reference and positioning distribution error information, SDK represents the total number of reference distribution standard points, i represents the i-th reference distribution standard point, j represents the next adjacent reference distribution standard point of the i-th reference distribution standard point, Li represents the detection distance between the i-th reference distribution standard point and the randomly distributed point, and Lj represents the detection distance between the j-th adjacent reference distribution standard point and the randomly distributed point; by calculating the weights of multi-point positioning reference and positioning distribution error information, the multi-point positioning reference selection is made more accurate and the positioning distribution error range is smaller.

[0078] In one embodiment, S400 includes:

[0079] S401, performing data processing and integration on multi-point positioning reference and positioning distribution error information weight calculation data;

[0080] S402, based on data processing integration, weight sorting of randomly distributed positioning points is performed through the location positioning computing cloud processing center;

[0081] S403, based on the weight sorting results of the randomly distributed positioning points, the weight data of the randomly distributed positioning points are smoothed by data smoothing, and a precise intelligent error elimination positioning accuracy calculation based on the random distribution cross reference of the position information is performed.

[0082] The working principle of the above technical solution is: S401, data processing and integration of multi-point positioning reference and positioning distribution error information weight calculation data; S402, based on the data processing and integration, the weights of the randomly distributed positioning points are sorted through the position positioning calculation cloud processing center; S403, based on the results of the weight sorting of the randomly distributed positioning points, the weight data of the randomly distributed positioning points are smoothed through data smoothing processing, and the random distribution cross-reference based on the position information is used to calculate the precise intelligent error elimination positioning accuracy.

[0083] The beneficial effects of the above technical solution are: through data processing and integration of multi-point positioning reference and positioning distribution error information weight calculation data; based on the data processing integration, the weights of the randomly distributed positioning points are sorted by the position positioning calculation cloud processing center; based on the results of the weight sorting of the randomly distributed positioning points, the weight data of the randomly distributed positioning points are smoothed by data smoothing processing, and the precise intelligent error elimination positioning accuracy calculation of the random distribution cross reference based on the position information is performed; it can perform high-precision calculation of complex multi-point positioning, and greatly improve the positioning error elimination processing capability of a variety of randomly distributed points.

[0084] The present invention provides a positioning accuracy calculation system based on position information, comprising:

[0085] The random array module of the distribution edge position information sets a random array of the position information of the multi-point positioning reference and the positioning distribution error at each point on the edge of the reference distribution standard point position, and collects and detects the multi-point positioning reference and positioning distribution error information;

[0086] The regional positioning signal transmitting and receiving module wirelessly transmits and receives the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits them to the position positioning computing cloud processing center;

[0087] The position positioning neural network deep learning module uses the position information and positioning distribution error neural network to perform intelligent neural network deep learning recognition on multi-point positioning reference and positioning distribution error information, identify the feature information of randomly distributed points and the feature information of distributed point errors, and calculate the weights of multi-point positioning reference and positioning distribution error information;

[0088] The intelligent error elimination positioning accuracy calculation module calculates data based on the weight of multi-point positioning reference and positioning distribution error information, sorts the weights of randomly distributed positioning points and performs smoothing processing, and performs precise intelligent error elimination positioning accuracy calculation based on random distribution cross-reference of position information.

[0089] The working principle of the above technical solution is: the present invention provides a positioning accuracy calculation system based on position information, including: a distribution edge position information random array module, which sets a multi-point positioning reference and positioning distribution error position information positioning accuracy random array at each point on the edge of the reference distribution standard point position, and collects and detects multi-point positioning reference and positioning distribution error information; a regional positioning signal transmitting and receiving module, which wirelessly transmits and receives the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits it to the position positioning calculation cloud processing center; a position positioning neural network deep learning module, which performs intelligent neural network deep learning recognition on the multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network, identifies the randomly distributed point feature information and the distribution point error feature information, and performs multi-point positioning reference and positioning distribution error information weight calculation; an intelligent difference elimination positioning accuracy calculation module, which performs weight sorting and smoothing processing on the randomly distributed positioning points according to the multi-point positioning reference and positioning distribution error information weight calculation data, and performs precise intelligent difference elimination positioning accuracy calculation based on random distribution cross reference of position information.

[0090] The beneficial effects of the above technical solution are as follows: the present invention provides a positioning accuracy calculation system based on position information, including: a distribution edge position information random array module, which sets a multi-point positioning reference and positioning distribution error position information positioning accuracy random array at each point on the edge of the reference distribution standard point position, and collects and detects multi-point positioning reference and positioning distribution error information; a regional positioning signal transmitting and receiving module, which wirelessly transmits and receives the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits them to the position positioning calculation cloud processing center; a position positioning neural network deep learning module, which performs intelligent neural network deep learning recognition on the multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network, identifies the feature information of the randomly distributed points and the feature information of the distributed point errors, and performs weight calculation of the multi-point positioning reference and positioning distribution error information; an intelligent error elimination positioning accuracy calculation module, which performs weight sorting and smoothing processing on the randomly distributed positioning points according to the weight calculation data of the multi-point positioning reference and positioning distribution error information, and performs precise intelligent error elimination positioning accuracy calculation based on the random distribution cross reference of the position information; it can perform high-precision calculation of multi-point complex positioning, and greatly improve the positioning error elimination processing capability of various randomly distributed points.

[0091] In one embodiment, the random array module for distributing edge position information includes:

[0092] The positioning signal transceiver coverage submodule sets wireless positioning signal transceivers at each point on the edge of the reference distribution standard point position. Every three wireless positioning signal transceivers have a wireless positioning signal transceiver range covering the center of the three wireless positioning signal transceivers.

[0093] The meter-wave radar scanning detection submodule sets a millimeter-wave radar at the center of the reference distribution standard point position, and scans the detection points in real time to see if there are randomly distributed points, and obtains radar detection information of the randomly distributed points.

[0094] The working principle of the above technical solution is as follows: the random array module of the distribution edge position information includes: a positioning signal transceiver coverage submodule, which sets a wireless positioning signal transceiver at each point on the edge of the reference distribution standard point position, and every three wireless positioning signal transceivers have a wireless positioning signal transceiver range covering the center of the three wireless positioning signal transceivers; a meter wave radar scanning detection submodule, which sets a millimeter wave radar at the center of the reference distribution standard point position, and scans the detection point in real time to see if there are randomly distributed points, and obtains radar detection information of the randomly distributed points; the wireless positioning signal transceiver includes: a three-dimensional positioning detection wave trigger unit, a spherical detection Wave transmitting unit, detection reflection wave receiving unit, femtosecond clock pulse unit and signal time difference correction unit; the positioning detection wave triggering unit triggers the positioning detection wave pulse generator to generate a stereo positioning detection wave pulse and triggers the femtosecond clock pulse unit to start timing, and the stereo positioning detection wave pulse is transmitted to the spherical detection wave transmitting unit to transmit the spherical detection wave to the positioning detection space with the wireless positioning signal transceiver as the sphere center; when the spherical detection wave encounters the object to be positioned, it is reflected to form a positioning reflection detection wave; the detection reflection wave receiving unit receives the positioning reflection detection wave, and the femtosecond clock pulse unit completes a detection timing segment; the signal time difference correction unit The detection timing section is corrected for the detection signal time difference, and the signal transmission conversion operation error between the device units is compensated to obtain the detection correction timing section; the precise distance of the object to be positioned is calculated according to the detection correction timing section and the stereo positioning detection wave speed; the positioning azimuth angle of the object to be positioned is calculated according to the azimuth angle of the reflected wave of the spherical detection wave of the object to be positioned; stereo precision positioning and stereo precision calculation of stereo positioning based on the stereo precision positioning position information are performed; when the positioning detection space reaches the farthest detection distance of the wireless positioning signal transceiver, the first wireless positioning signal transceiver position is used as the reference position, and the wireless positioning signal transceiver detects double the farthest distance. With distance as the path edge, the second wireless positioning signal transceiver and the third wireless positioning signal transceiver are arranged in an equilateral triangle, so that every three wireless positioning signal transceivers have a wireless positioning signal receiving and transmitting range covering the centers of the three wireless positioning signal transceivers; the three-dimensional positioning detection wave includes: multi-band electromagnetic waves and multi-wavelength light waves; preliminary detection is carried out through millimeter wave radar, and real-time scanning is performed to see whether there are randomly distributed points on the detection point. When the object to be detected is located at the randomly distributed point, the wireless positioning signal transceiver near the randomly distributed point is started to perform three-dimensional precise positioning and three-dimensional positioning precise calculation based on the three-dimensional precise positioning position information.

[0095] The beneficial effects of the above technical solution are as follows: through the positioning signal transceiver coverage submodule, wireless positioning signal transceivers are set at each point on the edge of the reference distribution standard point position, and every three wireless positioning signal transceivers have a wireless positioning signal transceiver range covering the center of the three wireless positioning signal transceivers; the meter wave radar scanning detection submodule sets a millimeter wave radar at the center of the reference distribution standard point position, and scans the detection point in real time to see if there are randomly distributed points, and obtains radar detection information of the randomly distributed points; the wireless positioning signal transceiver includes: a three-dimensional positioning detection wave trigger unit, a spherical detection wave transmitting unit, and a detection reflection wave. The receiving unit, the femtosecond clock pulse unit and the signal time difference correction unit; the stereo positioning detection wave triggering unit triggers the positioning detection wave pulse generator to generate a stereo positioning detection wave pulse and triggers the femtosecond clock pulse unit to start timing, and the stereo positioning detection wave pulse is transmitted to the spherical detection wave transmitting unit to transmit the spherical detection wave to the positioning detection space with the wireless positioning signal transceiver as the sphere center; when the spherical detection wave encounters the object to be positioned, it is reflected to form a positioning reflection detection wave; the detection reflection wave receiving unit receives the positioning reflection detection wave, and the femtosecond clock pulse unit completes a detection timing segment; the signal time difference correction unit corrects the detection timing segment Perform detection signal time difference correction, compensate for signal transmission conversion operation errors between device units, and obtain detection correction timing segment; calculate the precise distance of the object to be located based on the detection correction timing segment and the stereo positioning detection wave velocity; calculate the positioning azimuth angle of the object to be located based on the azimuth angle of the reflected wave of the spherical detection wave of the object to be located; perform stereo precision positioning and stereo precision calculation based on stereo precision positioning position information; when the positioning detection space reaches the farthest detection distance of the wireless positioning signal transceiver, take the first wireless positioning signal transceiver position as the reference position, and take the double farthest detection distance of the wireless positioning signal transceiver as the path The second wireless positioning signal transceiver and the third wireless positioning signal transceiver are arranged in an equilateral triangle, so that every three wireless positioning signal transceivers have a wireless positioning signal receiving and transmitting range covering the centers of the three wireless positioning signal transceivers; the three-dimensional positioning detection wave includes: multi-band electromagnetic waves and multi-wavelength light waves; preliminary detection is carried out through millimeter wave radar, and real-time scanning is performed to see whether there are randomly distributed points on the detection point. When the object to be detected is located at the randomly distributed point, the wireless positioning signal transceiver near the randomly distributed point is started to perform three-dimensional precise positioning and three-dimensional positioning precise calculation based on the three-dimensional precise positioning position information.

[0096] In one embodiment, the regional positioning signal transmitting and receiving module includes:

[0097] The positioning signal position parameter conversion submodule sets a wireless positioning signal converter at each point near the center area of ​​the reference distribution standard point position to convert any wireless positioning signal into position coordinate parameters;

[0098] The wireless transmission network cloud transmission submodule transmits the location coordinate parameters to the location positioning computing cloud processing center through the wireless transmission network;

[0099] The Bluetooth and WIFI wireless transmission network submodule uses the Bluetooth and WIFI wireless transmission network to wirelessly transmit and receive the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits them to the position positioning computing cloud processing center.

[0100] The working principle of the above technical solution is: the regional positioning signal transmitting and receiving module includes: a positioning signal position parameter conversion submodule, which sets a wireless positioning signal converter at each point near the center area of ​​the reference distribution standard point position to convert any wireless positioning signal into position coordinate parameters; a wireless transmission network cloud transmission submodule, which transmits the position coordinate parameters to the position positioning computing cloud processing center through the wireless transmission network; a Bluetooth and WIFI wireless transmission network submodule, which wirelessly transmits and receives the multi-point positioning reference and positioning distribution error information and parameter data through the Bluetooth and WIFI wireless transmission network, and transmits it to the position positioning computing cloud processing center.

[0101] The beneficial effects of the above technical solution are: through the positioning signal position parameter conversion sub-module, a wireless positioning signal converter is set at each point near the center area of ​​the reference distribution standard point position to convert any wireless positioning signal into position coordinate parameters; the wireless transmission network cloud transmission sub-module transmits the position coordinate parameters to the position positioning computing cloud processing center through the wireless transmission network; the Bluetooth and WIFI wireless transmission network sub-module wirelessly transmits and receives the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area through the Bluetooth and WIFI wireless transmission network, and transmits them to the position positioning computing cloud processing center.

[0102] In one embodiment, the location positioning neural network deep learning module includes:

[0103] Interference identification and analysis AI integrated submodule, setting up an AI deep learning interference identification and analysis module and integrating it into the location information and positioning distribution error neural network;

[0104] The processing and analysis feature determination submodule uses the position information and positioning distribution error neural network to perform intelligent neural network deep learning recognition on the multi-point positioning reference and positioning distribution error information, and performs processing and analysis; determines whether there are random distribution point features and whether there are distribution point error features on the points; and identifies random distribution point feature information or distribution point error feature information;

[0105] The error information weight calculation submodule performs multi-point positioning reference and positioning distribution error information weight calculation.

[0106] The working principle of the above technical solution is: the location positioning neural network deep learning module includes:

[0107] Interference identification and analysis AI integrated submodule, setting up an AI deep learning interference identification and analysis module and integrating it into the location information and positioning distribution error neural network;

[0108] The processing and analysis feature determination submodule uses the position information and positioning distribution error neural network to perform intelligent neural network deep learning recognition on the multi-point positioning reference and positioning distribution error information, and performs processing and analysis; determines whether there are random distribution point features and whether there are distribution point error features on the points; and identifies random distribution point feature information or distribution point error feature information;

[0109] The error information weight calculation submodule calculates the weights of multi-point positioning reference and positioning distribution error information; calculates the weights of multi-point positioning reference and positioning distribution error information:

[0110]

[0111] Among them, TDWk represents the weight of multi-point positioning reference and positioning distribution error information, SDK represents the total number of reference distribution standard points, i represents the i-th reference distribution standard point, j represents the next adjacent reference distribution standard point of the i-th reference distribution standard point, Li represents the detection distance between the i-th reference distribution standard point and the randomly distributed point, and Lj represents the detection distance between the j-th adjacent reference distribution standard point and the randomly distributed point.

[0112] The beneficial effects of the above technical solution are as follows: through the interference identification and analysis AI integration submodule, an AI deep learning interference identification and analysis module is set up and integrated into the position information and positioning distribution error neural network; the processing and analysis feature determination submodule performs intelligent neural network deep learning identification and processing analysis on multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network; determines whether there are randomly distributed point features and whether there are distributed point error features on the point; identifies randomly distributed point feature information or distributed point error feature information; the error information weight calculation submodule performs multi-point positioning reference and positioning distribution error information weight calculation;

[0113] Calculate the weights of multi-point positioning reference and positioning distribution error information: where TDWk represents the weights of multi-point positioning reference and positioning distribution error information, SDK represents the total number of reference distribution standard points, i represents the i-th reference distribution standard point, j represents the next adjacent reference distribution standard point of the i-th reference distribution standard point, Li represents the detection distance between the i-th reference distribution standard point and the randomly distributed point, and Lj represents the detection distance between the j-th adjacent reference distribution standard point and the randomly distributed point; by calculating the weights of multi-point positioning reference and positioning distribution error information, the multi-point positioning reference selection is made more accurate and the positioning distribution error range is smaller.

[0114] In one embodiment, the intelligent error elimination positioning accuracy calculation module includes:

[0115] The data processing and integration submodule processes and integrates the multi-point positioning reference and positioning distribution error information weight calculation data;

[0116] The random distribution point weight sorting submodule performs weight sorting of the randomly distributed points through the location positioning computing cloud processing center based on data processing integration;

[0117] The cross-reference intelligent precision calculation submodule performs data smoothing on the weighted data of the randomly distributed positioning points according to the weight sorting results of the randomly distributed positioning points, and performs precise intelligent error elimination positioning precision calculation based on the random distribution cross-reference based on the position information.

[0118] The working principle of the above technical solution is: the intelligent error elimination positioning accuracy calculation module includes: a data processing integration sub-module, which performs data processing and integration on the multi-point positioning reference and positioning distribution error information weight calculation data; a random distribution point weight sorting sub-module, which performs positioning random distribution point weight sorting through the position positioning calculation cloud processing center according to the data processing integration; a cross-reference intelligent accuracy calculation sub-module, which performs positioning random distribution point weight data smoothing through data smoothing processing according to the positioning random distribution point weight sorting result, and performs random distribution cross-reference based on position information precise intelligent error elimination positioning accuracy calculation.

[0119] The beneficial effects of the above technical solution are: through the data processing integration sub-module, data processing and integration are carried out on the multi-point positioning reference and positioning distribution error information weight calculation data; the random distribution point weight sorting sub-module, based on the data processing integration, performs positioning random distribution point weight sorting through the position positioning calculation cloud processing center; the cross-reference intelligent precision calculation sub-module, based on the positioning random distribution point weight sorting result, performs positioning random distribution point weight data smoothing through data smoothing processing, and performs random distribution cross-reference precise intelligent error elimination positioning precision calculation based on position information; it can perform high-precision calculation of multi-point complex positioning, and greatly improve the positioning error elimination processing capability of various randomly distributed points.

[0120] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and implementation methods. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. A method for calculating positioning accuracy based on position information, characterized in that: include: S100, setting a multi-point positioning reference and positioning distribution error position information positioning accuracy random array at each point on the edge of the reference distribution standard point position, and collecting and detecting multi-point positioning reference and positioning distribution error information; S200, wirelessly transmitting and receiving the multi-point positioning reference, positioning distribution error information, and parameter data in the positioning signal area, and transmitting them to the position positioning computing cloud processing center; S300, performing intelligent neural network deep learning recognition on multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network, identifying randomly distributed point feature information and distributed point error feature information, and performing weight calculation on the multi-point positioning reference and positioning distribution error information; S400: Based on the multi-point positioning reference and positioning distribution error information weight calculation data, the weight sorting and smoothing processing of the randomly distributed positioning points are performed, and the precise intelligent error elimination positioning accuracy calculation based on the random distribution cross reference of the position information is performed; S400 includes: S401, performing data processing and integration on multi-point positioning reference and positioning distribution error information weight calculation data; S402, based on data processing integration, weight sorting of randomly distributed positioning points is performed through the location positioning computing cloud processing center; S403, based on the weight sorting results of the randomly distributed positioning points, the weight data of the randomly distributed positioning points are smoothed by data smoothing, and a precise intelligent error elimination positioning accuracy calculation based on the random distribution cross reference of the position information is performed.

2. The method for calculating positioning accuracy based on position information according to claim 1, characterized in that: S100 includes: S101, setting wireless positioning signal transceivers at each point on the edge of the reference distribution standard point position, and each three wireless positioning signal transceivers have a wireless positioning signal receiving and transmitting range covering the center of the three wireless positioning signal transceivers; S102, setting a millimeter wave radar at the center of the reference distribution standard point position, scanning in real time to see if there are randomly distributed points on the detection point position, and obtaining radar detection information of the randomly distributed points.

3. The method for calculating positioning accuracy based on position information according to claim 1, wherein: S200 includes: S201, setting a wireless positioning signal converter at each point near the center area of ​​the reference distribution standard point position to convert any wireless positioning signal into position coordinate parameters; S202, transmitting the location coordinate parameters to the location positioning computing cloud processing center via a wireless transmission network; S203, through the Bluetooth and WIFI wireless transmission network, the multi-point positioning reference and positioning distribution error information and parameter data are wirelessly transmitted and received in the positioning signal area, and transmitted to the position positioning computing cloud processing center.

4. The method for calculating positioning accuracy based on position information according to claim 1, wherein: S300 includes: S301, setting up an AI deep learning interference recognition and analysis module and integrating it into the position information and positioning distribution error neural network; S302, performing intelligent neural network deep learning recognition on multi-point positioning reference and positioning distribution error information through the position information and positioning distribution error neural network, and performing processing and analysis; determining whether there are random distribution point features and distribution point error features at the points; and identifying random distribution point feature information or distribution point error feature information; S303: Perform multi-point positioning reference and positioning distribution error information weight calculation.

5. A positioning accuracy calculation system based on position information, characterized in that: include: The random array module of the distribution edge position information sets a random array of the position information of the multi-point positioning reference and the positioning distribution error at each point on the edge of the reference distribution standard point position, and collects and detects the multi-point positioning reference and positioning distribution error information; The regional positioning signal transmitting and receiving module wirelessly transmits and receives the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits them to the position positioning computing cloud processing center; The position positioning neural network deep learning module uses the position information and positioning distribution error neural network to perform intelligent neural network deep learning recognition on multi-point positioning reference and positioning distribution error information, identify the feature information of randomly distributed points and the feature information of distributed point errors, and calculate the weights of multi-point positioning reference and positioning distribution error information; The intelligent error elimination positioning accuracy calculation module calculates data based on the weight of multi-point positioning reference and positioning distribution error information, performs weight sorting and smoothing of randomly distributed positioning points, and performs precise intelligent error elimination positioning accuracy calculation based on random distribution cross-reference of position information; The intelligent error elimination positioning accuracy calculation module includes: The data processing and integration submodule processes and integrates the multi-point positioning reference and positioning distribution error information weight calculation data; The random distribution point weight sorting submodule performs weight sorting of the randomly distributed points through the location positioning computing cloud processing center based on data processing integration; The cross-reference intelligent precision calculation submodule performs data smoothing on the weighted data of the randomly distributed positioning points according to the weight sorting results of the randomly distributed positioning points, and performs precise intelligent error elimination positioning precision calculation based on the random distribution cross-reference based on the position information.

6. A positioning accuracy calculation system based on position information according to claim 5, characterized in that: The random array module for distributing edge position information includes: The positioning signal transceiver coverage submodule sets wireless positioning signal transceivers at each point on the edge of the reference distribution standard point position. Every three wireless positioning signal transceivers have a wireless positioning signal transceiver range covering the center of the three wireless positioning signal transceivers. The meter-wave radar scanning detection submodule sets a millimeter-wave radar at the center of the reference distribution standard point position, and scans the detection points in real time to see if there are randomly distributed points, and obtains radar detection information of the randomly distributed points.

7. The positioning accuracy calculation system based on position information according to claim 5, characterized in that: The regional positioning signal transmitting and receiving module includes: The positioning signal position parameter conversion submodule sets a wireless positioning signal converter at each point near the center area of ​​the reference distribution standard point position to convert any wireless positioning signal into position coordinate parameters; The wireless transmission network cloud transmission submodule transmits the location coordinate parameters to the location positioning computing cloud processing center through the wireless transmission network; The Bluetooth and WIFI wireless transmission network submodule uses the Bluetooth and WIFI wireless transmission network to wirelessly transmit and receive the multi-point positioning reference and positioning distribution error information and parameter data in the positioning signal area, and transmits them to the position positioning computing cloud processing center.

8. The positioning accuracy calculation system based on position information according to claim 5, characterized in that: The location positioning neural network deep learning module includes: Interference identification and analysis AI integrated submodule, setting up an AI deep learning interference identification and analysis module and integrating it into the location information and positioning distribution error neural network; The processing and analysis feature determination submodule uses the position information and positioning distribution error neural network to perform intelligent neural network deep learning recognition on the multi-point positioning reference and positioning distribution error information, and performs processing and analysis; determines whether there are random distribution point features and whether there are distribution point error features on the points; and identifies random distribution point feature information or distribution point error feature information; The error information weight calculation submodule performs multi-point positioning reference and positioning distribution error information weight calculation.

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