CN113271537A - Indoor positioning system of mixing chamber - Google Patents
Indoor positioning system of mixing chamber Download PDFInfo
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- CN113271537A CN113271537A CN202110548832.7A CN202110548832A CN113271537A CN 113271537 A CN113271537 A CN 113271537A CN 202110548832 A CN202110548832 A CN 202110548832A CN 113271537 A CN113271537 A CN 113271537A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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Abstract
A hybrid indoor positioning system, comprising: a basic positioning frame: the positioning system comprises a base station positioning module, a GPS positioning module, a Wi-Fi positioning module and a Beacon positioning module; basic positioning fusion module: selecting positioning results obtained by each positioning module in the basic positioning frame, and selecting an optimal positioning result; a PDR fusion module: different types of sensor data uploaded by the smart phone are processed by different sensor algorithms to obtain pedestrian motion state information, and the pedestrian motion state information, the positioning result output by the basic positioning fusion module and the last positioning result are fused to obtain the positioning result according with the pedestrian motion state: and a map matching module. The invention integrates GPS positioning, WiFi positioning, Beacon positioning and base station positioning, supports the expansion of positioning submodules, corrects the pedestrian track by PDR after integrating the positioning results, combines an indoor actual scene by map matching, and finally obtains stable and high-precision positioning.
Description
Technical Field
The invention relates to the technical field of indoor positioning, in particular to a hybrid indoor positioning system.
Background
With the rapid development of the mobile internet and the popularization of the smart phone, people have an increasing demand for location services of the smart phone in daily life. There are representative positioning systems such as GPS, beidou, etc. to provide location services outdoors, and these systems cannot provide accurate location services indoors due to signal blockage, etc. In the field of indoor positioning, WiFi (Wireless-Fidelity) and Beacon (bluetooth low energy Beacon) positioning are generally adopted, and for reasons of cost and precision, it is difficult to provide general high-precision location service by using one positioning technology for indoor positioning. In the case of good WiFi coverage, the single WiFi positioning accuracy is in the range of 5 meters to 10 meters; the single Beacon fixed precision can reach 3 meters to 5 meters, but the cost of laying Beacon is high, and the Beacon fixed precision needs to be supported by a user smart phone. The existing technology is basically the fusion of one or more positioning technologies, is not comprehensive enough, and does not fully utilize the advantages of each positioning technology.
Disclosure of Invention
Objects of the invention
In order to solve the technical problems in the background art, the invention provides a hybrid indoor positioning system which integrates GPS positioning, WiFi positioning, Beacon positioning and base station positioning, supports expansion of positioning submodules, corrects the track of a pedestrian by using PDR after integrating positioning results, combines an indoor actual scene by using map matching, and finally obtains stable and high-precision positioning.
(II) technical scheme
The invention provides a mixed indoor positioning system, comprising:
a basic positioning frame: the positioning system comprises four positioning modules which are independently operated, namely A1-A4:
a1, base station positioning module: in the base building stage, a base station base built in a big data crowdsourcing mode is used for roughly knowing the rough position of each base station, during positioning, the rough position of the smart phone is obtained by combining the built base station base and a trilateral positioning method according to base station information reported by the smart phone, and an output result comprises a positioning coordinate and a real-time positioning confidence coefficient;
a2, GPS positioning module: directly obtaining a GPS position result through the smart phone to obtain longitude and latitude coordinates, directly using the longitude and latitude coordinates as an output result, and obtaining a real-time positioning confidence coefficient according to the real-time positioning precision and the average positioning precision;
a3, Wi-Fi positioning module: obtaining an indoor positioning result by adopting a conventional fingerprint positioning technology, and obtaining a real-time positioning confidence coefficient according to the real-time positioning precision and the average positioning precision;
a4, Beacon positioning module: using geometric positioning based on RSSI ranging, under the condition that the positions of Beacon nodes are known, estimating the distance from a terminal to the nodes through the strength of Beacon node signals received by the terminal, estimating the position of the terminal according to the distances from the terminal to a plurality of nodes, and obtaining real-time positioning confidence according to real-time positioning accuracy and average positioning accuracy;
basic positioning fusion module: selecting positioning results obtained by each positioning module in the basic positioning frame, and selecting an optimal positioning result;
a PDR fusion module: processing the data by using different sensor algorithms to obtain pedestrian motion state information, and fusing the pedestrian motion state information, the positioning result output by the basic positioning fusion module and the last positioning result to obtain a positioning result according with the pedestrian motion state;
a map matching module: and further adjusting the position of the user to obtain the final position according with the indoor real scene.
Preferably, when the basic positioning fusion module selects the optimal positioning result, the selection method is to select the positioning result with the highest confidence coefficient according to the last positioning result and the position confidence of each positioning module at this time, and if the deviation between the positioning result with the highest confidence coefficient and the last positioning result is large and the deviation between the positioning results with the next highest confidence coefficient is within a certain range, the positioning result with the next highest confidence coefficient is selected.
Preferably, the positioning result output by the basic positioning fusion module is recorded as a result N, the last positioning result is recorded as a result B, and the fusion strategy of the PDR fusion module is as follows:
when the deviation between the result N and the result B exceeds a certain threshold value and the position reliability of the result N is greater than that of the result B, the result N is considered to be a credible positioning result and is directly output without utilizing the PDR fusion module for fusion, the data in the PDR fusion module is reset under the condition, and the result N is used as a new starting point;
when the dynamic and static states are judged to be static, the result B is taken as the final output;
and when the dynamic and static states are judged to be motion, calculating on the basis of the result B, obtaining a calculation result by combining the moving step number, the motion direction and the key steering angle, recording the calculation result as a result P, comparing the result P with the result N to obtain the forward direction deviation and the position point deviation data, correcting the parameters of the PDR fusion module, and taking the obtained result P as an output result.
Preferably, the map matching module uses a method comprising:
deviation rectification of an unreachable area: in an actual environment, a lot of places are inaccessible to pedestrians, and when the positioning result is in the areas, the positioning result is pulled to the nearest accessible area;
and (3) road correction: when the user deviates from the road within a certain range, the position of the user is corrected and pulled to the road.
Preferably, the positioning system further comprises a positioning result feed-forward module: and feeding back the positioning output result to the basic positioning frame, the basic positioning fusion module and the PDR fusion module.
Compared with the prior art, the technical scheme of the invention has the following beneficial technical effects:
the invention integrates GPS positioning, WiFi positioning, Beacon positioning and base station positioning, supports the expansion of positioning submodules, corrects the pedestrian track by PDR after integrating the positioning results, combines an indoor actual scene by map matching, and finally obtains stable and high-precision positioning. Each base location technique may operate independently or multiple location techniques may be used together. Together, the various techniques form a stable system that ultimately forms a stable closed loop through feed-forward.
Drawings
Fig. 1 is a flowchart illustrating an operation of a hybrid indoor positioning system according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
As shown in fig. 1, the present invention provides a hybrid indoor positioning system, which includes:
a basic positioning frame: the positioning system comprises four positioning modules which are independently operated, namely A1-A4:
a1, base station positioning module: in the base building stage, a base station base built in a big data crowdsourcing mode is used, the approximate position of each base station is approximately known, when in positioning, the position where the smart phone is approximately located is obtained by combining the built base station base and a trilateral positioning method according to base station information reported by the smart phone, the average positioning accuracy of a base station positioning module is about 250 meters, approximate longitude and latitude coordinates can be obtained, an output result comprises a positioning coordinate and a real-time positioning confidence coefficient, and an index of the real-time positioning confidence coefficient is obtained by evaluating the average positioning accuracy of the base station positioning module and the quality of a received base station signal;
a2, GPS positioning module: the method comprises the steps that a GPS position result is directly obtained through a smart phone, longitude and latitude coordinates are obtained and are directly used as an output result, the average positioning precision of a GPS positioning module is about 10m, the real-time positioning precision is obtained according to the data quality of a GPS, and the real-time positioning confidence coefficient is obtained according to the real-time positioning precision and the average positioning precision;
a3, Wi-Fi positioning module: obtaining an indoor positioning result by adopting a conventional fingerprint positioning technology, wherein in the case of unknown node positions, fingerprint positioning can be carried out by acquiring and storing characteristic values of signals at a plurality of known positions, matching a characteristic library with a real-time received signal and estimating a current position, the establishment of the characteristic library can use a crowdsourcing mode or a manual acquisition mode, the average positioning precision of a Wi-Fi positioning module is about 10m, the real-time positioning precision is that a real-time positioning confidence coefficient is obtained according to the obtained WiFi data quality and the average positioning precision;
a4, Beacon positioning module: using geometric positioning based on RSSI ranging, under the condition that the positions of Beacon nodes are known, estimating the distance from a terminal to the nodes through the strength of Beacon node signals received by the terminal, estimating the positions of the terminal according to the distances from the terminal to a plurality of nodes, wherein the positions of the nodes are accurate, the deployment is planned manually, the average positioning precision is about 5 meters higher, the real-time positioning precision is obtained according to the data quality of the Beacon, and the real-time positioning confidence is obtained according to the real-time positioning precision and the average positioning precision; rssi (received Signal Strength indicator) is an indication of the Strength of the received Signal, which is implemented after the backchannel baseband receive filter;
a basic positioning fusion module; selecting positioning results obtained by each positioning module in a basic positioning frame, and selecting an optimal positioning result, wherein the selection method comprises the steps of selecting according to the last positioning result and the position confidence of each positioning module at this time, selecting the positioning result with the highest confidence, and selecting the positioning result with the second highest confidence if the deviation of the positioning result with the highest confidence and the last positioning result is larger, and the deviation of the positioning result with the second highest confidence is within a certain range;
PDR (pedestrian dead reckoning) fusion module: different types of sensor data uploaded by the smart phone are processed by different sensor algorithms to obtain pedestrian motion state information, the positioning result output by the basic positioning fusion module and the last positioning result are fused to obtain the positioning result according with the pedestrian motion state, the positioning result output by the basic positioning fusion module is recorded as a result N, the last positioning result is recorded as a result B, and the fusion strategy of the PDR fusion module is as follows:
when the deviation between the result N and the result B exceeds a certain threshold value and the position reliability of the result N is greater than that of the result B, the result N is considered to be a credible positioning result and is directly output, the PDR fusion module is not utilized for fusion, in this case, the data in the PDR fusion module is reset, and the result N is used as a new starting point:
when the dynamic and static states are judged to be static, the result B is taken as the final output;
when the dynamic and static states are judged to be motion, calculating on the basis of a result B, obtaining a calculation result by combining the moving step number, the motion direction and the key steering angle, recording the calculation result as a result P, comparing the result P with a result N to obtain the deviation data of the advancing direction and the position point, correcting the parameters of the PDR fusion module, and taking the obtained result P as an output result;
a map matching module: the position of the user is further adjusted to obtain the final position according with the indoor real scene, and the method used by the map matching module comprises the following steps:
deviation rectification of an unreachable area: in an actual environment, a lot of places are inaccessible to pedestrians, and when the positioning result is in the areas, the positioning result is pulled to the nearest accessible area;
and (3) road correction: when the user deviates from the road within a certain range, the position of the user is corrected and pulled to the road.
A positioning result forward feedback module: and the positioning output result is fed back to the basic positioning frame, the basic positioning fusion module and the PDR fusion module, so that higher positioning precision is brought to the next positioning of the modules, and a system outputs a more accurate positioning result.
The invention integrates GPS positioning, WiFi positioning, Beacon positioning and base station positioning, supports the expansion of positioning submodules, corrects the pedestrian track by PDR after integrating the positioning results, combines an indoor actual scene by map matching, and finally obtains stable and high-precision positioning. Each base location technique may operate independently or multiple location techniques may be used together. Together, the various techniques form a stable system that ultimately forms a stable closed loop through feed-forward.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (5)
1. A hybrid indoor positioning system, comprising:
a basic positioning frame: the positioning system comprises four positioning modules which are independently operated, namely A1-A4:
a1, base station positioning module: in the base building stage, a base station base built in a big data crowdsourcing mode is used for roughly knowing the rough position of each base station, during positioning, the rough position of the smart phone is obtained by combining the built base station base and a trilateral positioning method according to base station information reported by the smart phone, and an output result comprises a positioning coordinate and a real-time positioning confidence coefficient;
a2, GPS positioning module: directly obtaining a GPS position result through the smart phone to obtain longitude and latitude coordinates, directly using the longitude and latitude coordinates as an output result, and obtaining a real-time positioning confidence coefficient according to the real-time positioning precision and the average positioning precision;
a3, Wi-Fi positioning module: obtaining an indoor positioning result by adopting a conventional fingerprint positioning technology, and obtaining a real-time positioning confidence coefficient according to the real-time positioning precision and the average positioning precision;
a4, Beacon positioning module: using geometric positioning based on RSSI ranging, under the condition that the positions of Beacon nodes are known, estimating the distance from a terminal to the nodes through the strength of Beacon node signals received by the terminal, estimating the position of the terminal according to the distances from the terminal to a plurality of nodes, and obtaining real-time positioning confidence according to real-time positioning accuracy and average positioning accuracy;
basic positioning fusion module: selecting positioning results obtained by each positioning module in the basic positioning frame, and selecting an optimal positioning result;
a PDR fusion module: processing the data by using different sensor algorithms to obtain pedestrian motion state information, and fusing the pedestrian motion state information, the positioning result output by the basic positioning fusion module and the last positioning result to obtain a positioning result according with the pedestrian motion state;
a map matching module: and further adjusting the position of the user to obtain the final position according with the indoor real scene.
2. The hybrid indoor positioning system of claim 1, wherein when the basic positioning fusion module selects the optimal positioning result, the selection method is to select the positioning result with the highest confidence according to the last positioning result and the position confidence of each positioning module this time, and if the positioning result with the highest confidence has a larger deviation from the last positioning result and the positioning result with the next highest confidence has a deviation within a certain range, the positioning result with the next highest confidence is selected.
3. The system of claim 2, wherein the positioning result output by the base positioning fusion module is recorded as result N, the last positioning result is recorded as result B, and the fusion strategy of the PDR fusion module is:
when the deviation between the result N and the result B exceeds a certain threshold value and the position reliability of the result N is greater than that of the result B, the result N is considered to be a credible positioning result and is directly output without utilizing the PDR fusion module for fusion, the data in the PDR fusion module is reset under the condition, and the result N is used as a new starting point;
when the dynamic and static states are judged to be static, the result B is taken as the final output;
and when the dynamic and static states are judged to be motion, calculating on the basis of the result B, obtaining a calculation result by combining the moving step number, the motion direction and the key steering angle, recording the calculation result as a result P, comparing the result P with the result N to obtain the forward direction deviation and the position point deviation data, correcting the parameters of the PDR fusion module, and taking the obtained result P as an output result.
4. A hybrid indoor location system as claimed in claim 3 wherein the map matching module uses a method comprising:
deviation rectification of an unreachable area: in an actual environment, a lot of places are inaccessible to pedestrians, and when the positioning result is in the areas, the positioning result is pulled to the nearest accessible area;
and (3) road correction: when the user deviates from the road within a certain range, the position of the user is corrected and pulled to the road.
5. The hybrid indoor positioning system of claim 4, further comprising a positioning result feed-forward module: and feeding back the positioning output result to the basic positioning frame, the basic positioning fusion module and the PDR fusion module.
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| US20230319742A1 (en) * | 2022-04-05 | 2023-10-05 | Meta Platforms, Inc. | Peripheral time server device |
| CN117560629A (en) * | 2024-01-11 | 2024-02-13 | 北京中关村实验室 | Safe and robust indoor pedestrian track tracking method and system |
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