CN109085536B - Indoor self-positioning method, device, system and equipment based on LED lamp - Google Patents
Indoor self-positioning method, device, system and equipment based on LED lamp Download PDFInfo
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- CN109085536B CN109085536B CN201810770534.0A CN201810770534A CN109085536B CN 109085536 B CN109085536 B CN 109085536B CN 201810770534 A CN201810770534 A CN 201810770534A CN 109085536 B CN109085536 B CN 109085536B
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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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/16—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using electromagnetic waves other than radio waves
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
- Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection
Abstract
The application discloses an indoor self-positioning method, device, system and equipment based on LED lamps, wherein the method comprises the following steps: s1, selecting a first preset number of light intensity data from all the light intensity data received at a to-be-positioned point in a descending manner from a maximum light intensity value, and combining to obtain a light intensity data group to be analyzed, wherein the light intensity data comprises: light intensity value and LED lamp ID; s2, determining a matching light intensity data set with the highest similarity to the light intensity data set to be analyzed in a preset light intensity database according to a preset matching rule, wherein coordinates corresponding to the matching light intensity data set with the highest similarity serve as positioning coordinates of the point to be positioned, and the preset light intensity database comprises: all coordinates of the indoor area and all light intensity data received at each location coordinate. The technical problem that the existing indoor self-positioning technology cannot accurately position in an electromagnetic sensitive environment is solved.
Description
Technical Field
The application relates to the technical field of indoor positioning, in particular to an indoor self-positioning method, device, system and equipment based on an LED lamp.
Background
With the continuous development of intelligent products, the demand of people for location-based services is continuously increasing. For example, when a person is located at a certain indoor location and wants to go to another indoor location (set as a destination location), the person first needs to obtain the current location information of the person, then obtains the destination location information, and finally obtains a path from the current location to the destination location after path planning. The most fundamental in the whole process is the acquisition of the current position of the user (hereinafter referred to as self-positioning), and at this time, if the self-positioning position information is wrong, the planning of the whole path is affected.
However, although the existing indoor self-positioning technologies, such as infrared technology, radio Frequency Identification (RFID) technology, wireless Local Area Network (WLAN) technology, etc., can achieve a good self-positioning effect in an indoor environment, for an electromagnetic sensitive environment (e.g., a hospital, etc.), the existing indoor self-positioning technologies cannot accurately position in the electromagnetic sensitive environment because electromagnetic waves used in self-positioning are easily interfered by other types of electromagnetic waves.
Disclosure of Invention
The embodiment of the application provides an indoor self-positioning method, device, system and equipment based on an LED lamp, which are used for indoor self-positioning and solving the technical problem that the existing indoor self-positioning technology cannot accurately position in an electromagnetic sensitive environment.
In view of the above, a first aspect of the present application provides an indoor self-positioning method based on LED lamps, including:
s1, selecting a first preset number of light intensity data from all the light intensity data received at a to-be-positioned point in a descending manner from a maximum light intensity value, and combining to obtain a light intensity data group to be analyzed, wherein the light intensity data comprises: light intensity value and LED lamp ID;
s2, determining a matching light intensity data set with the highest similarity to the light intensity data set to be analyzed in a preset light intensity database according to a preset matching rule, wherein coordinates corresponding to the matching light intensity data set with the highest similarity serve as positioning coordinates of the point to be positioned, and the preset light intensity database comprises: all coordinates of the indoor area and all light intensity data received at each position coordinate.
Preferably, step S1 is preceded by S0;
s0, collecting coordinates of each grid point obtained after the preset grid division is carried out on the indoor area and all light intensity data received at each grid point to obtain the preset light intensity database.
Preferably, step S2 specifically includes:
s21, determining a second preset number of matched light intensity data sets matched with the light intensity data sets to be analyzed and coordinates corresponding to each matched light intensity data set in a preset light intensity database;
s22, determining the matched light intensity data group with the highest similarity to the light intensity data group to be analyzed from all the matched light intensity data groups, wherein the coordinate corresponding to the matched light intensity data group with the highest similarity is used as the positioning coordinate of the point to be positioned.
Preferably, step S21 specifically includes:
s211, randomly selecting one light intensity data to be analyzed from the light intensity data group to be analyzed;
s212, inquiring all light intensity data to be matched, which are the same as the ID of the selected LED lamp of the light intensity data to be analyzed, in a preset light intensity database;
s213, calculating the absolute error of the light intensity value of each light intensity data to be matched and the selected light intensity data to be analyzed, and selecting a second preset number of light intensity data to be matched from the minimum value in an increasing mode from all the absolute errors to obtain a second preset number of matched light intensity data;
and S214, inquiring the preset light intensity database, and obtaining a second preset number of matched light intensity data sets and coordinates corresponding to each matched light intensity data set, wherein the matched light intensity data sets correspond to each matched light intensity data set, and the coordinates corresponding to each matched light intensity data set.
Preferably, step S22 specifically includes:
and calculating the sum of squares of errors of each matched light intensity data set and the light intensity data set to be analyzed, and determining the matched light intensity data set with the minimum sum of squares of errors of the matched light intensity data sets to be analyzed, wherein the coordinate corresponding to the matched light intensity data set with the minimum sum of squares of errors is used as the positioning coordinate of the to-be-positioned point.
This application second aspect provides a from positioner in room based on LED lamp, includes: a first unit and a second unit;
the first unit is used for selecting a first preset number of light intensity data from all the light intensity data received at the to-be-positioned point in a descending manner from the maximum light intensity value, and combining the light intensity data to obtain a light intensity data group to be analyzed, wherein the light intensity data comprises: light intensity value and LED lamp ID;
the second unit is configured to determine, according to a preset matching rule, a matching light intensity data set with the highest similarity to the light intensity data set to be analyzed in a preset light intensity database, where coordinates corresponding to the matching light intensity data set with the highest similarity serve as positioning coordinates of the point to be positioned, where the preset light intensity database includes: all coordinates of the indoor area and all light intensity data received at each position coordinate.
Preferably, the method further comprises the following steps: a third unit;
and the third unit is used for acquiring the coordinates of each grid point obtained by performing preset grid division on the indoor area and all the received light intensity data at each grid point to obtain the preset light intensity database.
The third aspect of the present application provides an indoor self-positioning system based on LED lamps, comprising: the controller, the photoelectric detector and the self-positioning device are arranged on the base;
the controller is used for controlling each LED lamp to generate light intensity data one by one in a time division multiplexing mode;
the photoelectric detector is used for receiving the light intensity data one by one at the position to be positioned, identifying the light intensity data and then sending the identified light intensity data to the self-positioning device.
The fourth aspect of the application provides an indoor self-positioning device based on an LED lamp, the device comprises a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the self-positioning method described above according to instructions in the program code.
A fifth aspect of the present application provides a computer-readable storage medium for storing program code for performing the self-positioning method described above.
According to the technical scheme, the embodiment of the application has the following advantages:
the application provides an indoor self-positioning method, device, system and equipment based on LED lamps, wherein the method comprises the following steps: firstly, in all light intensity data received at a to-be-positioned point, selecting a first preset number of light intensity data from maximum light intensity values in a descending manner, combining to obtain a light intensity data group to be analyzed, and then determining a matching light intensity data group with the highest similarity to the light intensity data group to be analyzed in a preset light intensity database.
Drawings
Fig. 1 is a schematic flowchart of a first embodiment of an indoor self-positioning method based on an LED lamp in an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a second embodiment of an indoor self-positioning method based on LED lamps in the embodiment of the present application;
FIG. 3 is a schematic flow chart illustrating a third embodiment of an indoor self-positioning method based on LED lamps in the embodiment of the present application;
FIG. 4 is a schematic structural diagram of an indoor self-positioning device based on an LED lamp according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an indoor self-positioning system based on an LED lamp in an embodiment of the present application.
Detailed Description
The embodiment of the application provides an indoor self-positioning method, device, system and equipment based on an LED lamp, which are used for indoor self-positioning and solving the technical problem that the existing indoor self-positioning technology cannot accurately position in an electromagnetic sensitive environment.
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
Referring to fig. 1, a schematic flow chart of a first embodiment of an indoor self-positioning method based on an LED lamp in the embodiment of the present application includes:
101, selecting a first preset number of light intensity data from all the light intensity data received at a to-be-positioned point in a descending manner from a maximum light intensity value, and combining to obtain a light intensity data group to be analyzed, wherein the light intensity data comprises: light intensity value and LED lamp ID.
It should be noted that, in all the light intensity data received at the point to be located, the first preset number of light intensity data is selected from the light intensity data with the maximum light intensity value decreasing progressively, so that the light intensity value in the light intensity data group to be analyzed is larger, and the subsequent analysis is facilitated. It will be appreciated that the light intensity values produced by different LED lamps are the same, except that the light intensity values received at different locations for the same LED lamp may be different.
The light intensity data includes a light intensity value and an LED lamp ID, for example, when the light intensity data is 100A, where letters indicate the LED lamp ID and numbers indicate the light intensity value of the lamp received at the point to be positioned. It is to be understood that the light intensity data is not limited to the form of the number + letter described in the present embodiment, but may be in the form of the number + number, and is not particularly limited herein.
102, in a preset light intensity database, according to a preset matching rule, determining a matching light intensity data set with the highest similarity to a light intensity data set to be analyzed, wherein coordinates corresponding to the matching light intensity data set with the highest similarity are used as positioning coordinates of a point to be positioned, wherein the preset light intensity database comprises: all coordinates of the indoor area and all light intensity data received at each location coordinate.
It should be noted that, after the light intensity data set to be analyzed is determined, according to the preset matching rule, the matching light intensity data set with the highest similarity to the light intensity data set to be analyzed is determined in the preset light intensity database, and the coordinate corresponding to the matching light intensity data set with the highest similarity is used as the positioning coordinate of the point to be positioned.
In the embodiment, firstly, a first preset number of light intensity data are selected from all light intensity data received at a to-be-positioned point in a descending manner from a maximum light intensity value, a light intensity data group to be analyzed is obtained through combination, and then a matching light intensity data group with the highest similarity to the light intensity data group to be analyzed is determined in a preset light intensity database.
The foregoing is a first embodiment of an indoor self-positioning method based on an LED lamp provided in the embodiments of the present application, and the following is a second embodiment of the indoor self-positioning method based on an LED lamp provided in the embodiments of the present application.
Referring to fig. 2, a schematic flowchart of a second embodiment of an indoor self-positioning method based on LED lamps in the embodiment of the present application includes:
It should be noted that the size of the preset grid can be adjusted according to actual needs, and if a high-precision self-positioning effect is desired, a preset grid with a dense grid can be set. If the requirement on the accuracy of self-positioning is not particularly high, a preset grid with a sparse grid can be set.
It should be noted that the first preset number may be set according to actual needs, and in this embodiment, the first preset number is 3. For example, if all the light intensity data received at the point to be positioned are (100A, 101B, 90C, 80D, 95E), the light intensity data group to be analyzed is (100A, 101B, 95E).
It should be noted that, after the light intensity data sets to be analyzed are determined, in order to reduce the amount of calculation for processing and avoid the time delay, first, in the preset light intensity database, a second preset number of matching light intensity data sets matched with the light intensity data sets to be analyzed and the coordinates corresponding to each matching light intensity data set are determined.
And 203, determining a matched light intensity data set with the highest similarity to the light intensity data set to be analyzed from all the matched light intensity data sets, wherein the coordinate corresponding to the matched light intensity data set with the highest similarity is used as the positioning coordinate of the point to be positioned.
In the embodiment, a first preset number of light intensity data are selected from all light intensity data received at a position to be positioned in a descending manner, and are combined to obtain a light intensity data group to be analyzed, because the light intensity data and indoor coordinates have a corresponding relationship in a preset light intensity database, in order to reduce calculation amount and avoid time delay, a second preset number of matching light intensity data groups matched with the light intensity data group to be analyzed and coordinates corresponding to each matching light intensity data group are determined in the preset light intensity database, and then a matching light intensity data group with the highest similarity to the light intensity data group to be analyzed is determined from all the matching light intensity data groups, and at the moment, the coordinates corresponding to the matching light intensity data group with the highest similarity are determined as the positioning coordinates of the position to be positioned.
The foregoing is a second embodiment of an indoor self-positioning method based on an LED lamp provided in this application, and the following is a third embodiment of the indoor self-positioning method based on an LED lamp provided in this application.
Referring to fig. 3, a schematic flowchart of a second embodiment of an indoor self-positioning method based on LED lamps in the embodiment of the present application includes:
and step 300, collecting coordinates of each grid point obtained after the preset grid segmentation is carried out on the indoor area and all light intensity data received at each grid point to obtain a preset light intensity database.
Step 300 is the same as step 200 in the second embodiment of the present application, and for the specific description, reference may be made to the content of step 200 in the second embodiment, which is not described herein again.
301, in all the light intensity data received at the point to be positioned, selecting a first preset number of light intensity data from the maximum light intensity values in a descending manner, and combining to obtain a light intensity data group to be analyzed, wherein the light intensity data comprises: light intensity value and LED lamp ID.
Step 301 is the same as step 201 in the second embodiment of the present application, and for specific description, reference may be made to the content of step 201 in the second embodiment, which is not described herein again.
It should be noted that, one of the light intensity data sets to be analyzed is randomly selected, for example, the light intensity data set to be analyzed is (100A, 101B, 95E), and the selected light intensity data to be analyzed is 100A.
And step 303, inquiring all the light intensity data to be matched, which are the same as the ID of the selected LED lamp of the light intensity data to be analyzed, in a preset light intensity database.
It should be noted that, in the preset light intensity database, all the light intensity data to be matched that are the same as the ID of the LED lamp of the selected light intensity data to be analyzed are searched. For example, the light intensity data 100A is queried to obtain all the light intensity data to be matched: 101A, 100A, 80A, 85A, 93A.
And 304, calculating absolute errors of the light intensity values of each light intensity data to be matched and the selected light intensity data to be analyzed, and selecting a second preset number of light intensity data to be matched from all the absolute errors in an increasing mode from the minimum value to obtain a second preset number of matched light intensity data.
It should be noted that the second preset number may also be set as needed, and in this embodiment, the second preset number is 4, that is, the matching light intensity data at this time is 101A, 100A, 85A, and 93A.
And 305, inquiring in a preset light intensity database, and obtaining a matching light intensity data group corresponding to each matching light intensity data and a coordinate corresponding to each matching light intensity data to obtain a second preset number of matching light intensity data groups and a coordinate corresponding to each matching light intensity data group.
It should be noted that, after the second preset number of matched light intensity data are determined, the matched light intensity data group corresponding to each matched light intensity data and the coordinate corresponding to each matched light intensity data are searched in the preset light intensity database, so as to obtain the second preset number of matched light intensity data groups and the coordinate corresponding to each matched light intensity data group. The matched light intensity data set in this embodiment is: (101A, 99B, 96E), (100A, 102B, 96E), (85A, 90B, 102E), (90A, 96B, 101E), and the coordinates corresponding to each matched light-intensity data group are (3,3), (3,4), (5,3), (4,3), respectively.
In the present embodiment, the sum of squares of errors between the 4 matched light intensity data sets (101A, 99B, 96E), (100A, 102B, 96E), (85A, 90B, 102E), (90A, 96B, 101E) and the light intensity data set to be analyzed (100A, 101B, 95E) is calculated, respectively. It should be noted that, here, the sum of absolute errors between the 4 matched light intensity data sets and the light intensity data set to be analyzed may be calculated.
And 307, determining a matched light intensity data set with the minimum error square sum with the light intensity data set to be analyzed, wherein the coordinate corresponding to the matched light intensity data set with the minimum error square sum is used as the positioning coordinate of the point to be positioned.
In this embodiment, the sum of squares of errors between the light intensity data sets (100A, 102B, 96E) and the light intensity data to be analyzed is matched according to the calculation result of step 306, and at this time, the coordinate corresponding to the light intensity data sets (100A, 102B, 96E) is considered to be the positioning coordinate of the point to be positioned. If the preset light intensity database is set, the coordinate corresponding to the matched light intensity data set (100A, 102B, 96E) is (3,4), at this time, the positioning coordinate of the point to be positioned is (3,4), the position of the coordinate (3,4) and the position of the point to be positioned are considered, for example, the (3,4) point is in a medical department of a hospital, and at this time, the position of the point to be positioned can be identified as being in the medical department. Here, the coordinate corresponding to the matching light intensity data set with the minimum absolute error may be selected as the positioning coordinate of the point to be positioned.
It should be noted that, the second preset number of matching light intensity data sets that match the light intensity data set to be analyzed is determined, which is not limited to the manner described in this embodiment, and may also be the LED lamp IDs of the light intensity data in the light intensity data set to be analyzed, that is, all the light intensity data sets of the LED lamp IDs that contain the light intensity data in the light intensity data set to be analyzed in the preset light intensity database, as the second preset number of matching light intensity data sets. Or selecting two light intensity data to be analyzed, calculating the sum of absolute errors of the two light intensity data, selecting matched light intensity data from the sum of absolute errors in the smallest incremental mode, and determining a second preset number of matched light intensity data sets.
In the embodiment, a first preset number of light intensity data are selected from all light intensity data received at a position to be positioned in a descending manner, and are combined to obtain a light intensity data group to be analyzed, because the light intensity data and indoor coordinates have a corresponding relationship in a preset light intensity database, in order to reduce calculation amount and avoid time delay, a second preset number of matching light intensity data groups matched with the light intensity data group to be analyzed and coordinates corresponding to each matching light intensity data group are determined in the preset light intensity database, and then a matching light intensity data group with the highest similarity to the light intensity data group to be analyzed is determined from all the matching light intensity data groups, and at the moment, the coordinates corresponding to the matching light intensity data group with the highest similarity are determined as the positioning coordinates of the position to be positioned.
The foregoing is a third embodiment of the indoor self-positioning method based on the LED lamp provided in this embodiment of the present application, and the following is an embodiment of the indoor self-positioning device based on the LED lamp provided in this embodiment of the present application.
Referring to fig. 4, a schematic structural diagram of an indoor self-positioning device based on an LED lamp in an embodiment of the present application includes:
the method comprises the following steps: a first unit 401 and a second unit 402;
the first unit 401 is configured to select a first preset number of light intensity data from all light intensity data received at a to-be-located point in a descending manner from a maximum light intensity value, and combine the light intensity data to obtain a light intensity data group to be analyzed, where the light intensity data includes: light intensity value and LED lamp ID;
a second unit 402, configured to determine, according to a preset matching rule, a matching light intensity data set with the highest similarity to a light intensity data set to be analyzed in a preset light intensity database, where a coordinate corresponding to the matching light intensity data set with the highest similarity is used as a positioning coordinate of a point to be located, where the preset light intensity database includes: all coordinates of the indoor area and all light intensity data received at each location coordinate.
Further, a third unit 403 is also included;
the third unit 403 is configured to acquire coordinates of each grid point obtained by performing preset grid segmentation on the indoor area and all light intensity data received at each grid point, so as to obtain a preset light intensity database.
In the embodiment, firstly, a first preset number of light intensity data are selected from all light intensity data received at a to-be-positioned point in a descending manner from a maximum light intensity value, a light intensity data group to be analyzed is obtained through combination, and then a matching light intensity data group with the highest similarity to the light intensity data group to be analyzed is determined in a preset light intensity database.
The foregoing is an embodiment of an indoor self-positioning device based on an LED lamp provided in this application, and the following is an embodiment of an indoor self-positioning system based on an LED lamp provided in this application.
Referring to fig. 5, in an embodiment of the present application, a schematic structural diagram of an indoor self-positioning system based on an LED lamp includes: a controller 501, a photodetector 502 and the self-positioning device 503 of the above embodiment; the controller 501 is configured to control each LED lamp to generate light intensity data one by one in a time division multiplexing manner; the photodetector 502 is configured to receive the light intensity data one by one at the point to be positioned, identify the light intensity data, and send the identified light intensity data to the self-positioning device 503.
It should be noted that, the time division multiplexing control mode takes account of both indoor lighting and ID coding of the LED lamp, and the CMOS switch is controlled by the main controller to enable each LED to generate light intensity data carrying the ID of the LED lamp. The photodetector 502 recognizes the light intensity data carrying the LED lamp ID as a corresponding light intensity value and LED lamp ID.
The embodiment of the application also provides an indoor self-positioning device based on the LED lamp, and the device comprises a processor and a memory: the memory is used for storing the program codes and transmitting the program codes to the processor, and the processor is used for executing the self-positioning method in the first embodiment and the second embodiment according to the instructions in the program codes, thereby executing various functional applications and data processing.
The embodiment of the present application further provides a computer-readable storage medium, which is used for storing a program code, where the program code is used for executing the self-positioning method in the foregoing first embodiment and second embodiment.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The terms "first," "second," "third," "fourth," and the like (if any) in the description of the present application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that, in this application, "at least one" means one or more, "a plurality" means two or more. "and/or" is used to describe the association relationship of the associated object, indicating that there may be three relationships, for example, "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b and c may be single or plural.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (7)
1. An indoor self-positioning method based on an LED lamp is characterized by comprising the following steps:
s1, selecting a first preset number of light intensity data from all the light intensity data received at a to-be-positioned point in a descending manner from a maximum light intensity value, and combining to obtain a light intensity data group to be analyzed, wherein the light intensity data comprises: light intensity value and LED lamp ID;
s2, determining a matching light intensity data set with the highest similarity to the light intensity data set to be analyzed in a preset light intensity database according to a preset matching rule, wherein coordinates corresponding to the matching light intensity data set with the highest similarity serve as positioning coordinates of the point to be positioned, and the preset light intensity database comprises: all coordinates of the indoor area and all light intensity data received at each position coordinate;
determining the matched light intensity data group with the highest similarity to the light intensity data group to be analyzed specifically, calculating the sum of squares of errors of each matched light intensity data group and the light intensity data group to be analyzed, and determining the matched light intensity data group with the smallest sum of squares of errors of the matched light intensity data groups and the light intensity data group to be analyzed;
the step S2 specifically includes:
s21, in a preset light intensity database, determining a second preset number of matched light intensity data sets matched with the light intensity data sets to be analyzed and coordinates corresponding to each matched light intensity data set;
s22, determining a matched light intensity data set with the highest similarity with the light intensity data set to be analyzed from all the matched light intensity data sets, wherein the coordinate corresponding to the matched light intensity data set with the highest similarity is used as the positioning coordinate of the point to be positioned;
step S21 specifically includes:
s211, randomly selecting one light intensity data to be analyzed from the light intensity data group to be analyzed;
s212, inquiring all light intensity data to be matched, which are the same as the ID of the selected LED lamp of the light intensity data to be analyzed, in a preset light intensity database;
s213, calculating the absolute error of the light intensity value of each light intensity data to be matched and the selected light intensity data to be analyzed, and selecting a second preset number of light intensity data to be matched from the minimum value in an increasing mode from all the absolute errors to obtain a second preset number of matched light intensity data;
s214, inquiring in the preset light intensity database, and obtaining a second preset number of matched light intensity data sets and coordinates corresponding to each matched light intensity data set according to the matched light intensity data set corresponding to each matched light intensity data set and the coordinates corresponding to each matched light intensity data set.
2. The method of claim 1, further comprising, prior to step S1, S0;
s0, collecting coordinates of each grid point obtained after the preset grid division is carried out on the indoor area and all light intensity data received at each grid point to obtain the preset light intensity database.
3. An indoor self-positioning device based on LED lamps, characterized by comprising: a first unit and a second unit;
the first unit is used for selecting a first preset number of light intensity data from all the light intensity data received at the to-be-positioned point in a descending manner from the maximum light intensity value, and combining the light intensity data to obtain a light intensity data group to be analyzed, wherein the light intensity data comprises: light intensity value and LED lamp ID;
the second unit is configured to determine, according to a preset matching rule, a matching light intensity data set with the highest similarity to the light intensity data set to be analyzed in a preset light intensity database, where coordinates corresponding to the matching light intensity data set with the highest similarity serve as positioning coordinates of the point to be positioned, where the preset light intensity database includes: all coordinates of the indoor area and all light intensity data received at each position coordinate;
determining the matched light intensity data group with the highest similarity to the light intensity data group to be analyzed specifically, calculating the sum of squares of errors of each matched light intensity data group and the light intensity data group to be analyzed, and determining the matched light intensity data group with the smallest sum of squares of errors of the matched light intensity data groups and the light intensity data group to be analyzed;
the second unit specifically includes:
the matching light intensity data set determining subunit is used for determining a second preset number of matching light intensity data sets matched with the light intensity data set to be analyzed and the corresponding coordinates of each matching light intensity data set in a preset light intensity database;
the target determining subunit is used for determining a matching light intensity data set with the highest similarity to the light intensity data set to be analyzed from all the matching light intensity data sets, and the coordinate corresponding to the matching light intensity data set with the highest similarity is used as the positioning coordinate of the point to be positioned;
the target determination subunit is specifically configured to:
randomly selecting one light intensity data to be analyzed from the light intensity data group to be analyzed;
inquiring all the light intensity data to be matched which are the same as the ID of the selected LED lamp of the light intensity data to be analyzed in a preset light intensity database;
calculating the absolute error of the light intensity value of each light intensity data to be matched and the selected light intensity data to be analyzed, and selecting a second preset number of light intensity data to be matched from the minimum value in an increasing mode from all the absolute errors to obtain a second preset number of matched light intensity data;
and inquiring in the preset light intensity database, and obtaining a second preset number of matched light intensity data sets and coordinates corresponding to each matched light intensity data set by using the matched light intensity data set corresponding to each matched light intensity data and the coordinates corresponding to each matched light intensity data set.
4. The apparatus of claim 3, further comprising: a third unit;
and the third unit is used for acquiring the coordinates of each grid point obtained by performing preset grid division on the indoor area and all the received light intensity data at each grid point to obtain the preset light intensity database.
5. An indoor self-positioning system based on LED lamps, comprising: a controller, a photodetector and a self-positioning device as claimed in claim 3 or 4 above;
the controller is used for controlling each LED lamp to generate light intensity data one by one in a time division multiplexing mode;
the photoelectric detector is used for receiving the light intensity data one by one at the position to be positioned, identifying the light intensity data and then sending the identified light intensity data to the self-positioning device.
6. An indoor self-positioning device based on LED lamps, characterized in that the device comprises a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the self-localization method of any of claims 1-2 according to instructions in the program code.
7. A computer-readable storage medium for storing program code for performing the self-localization method of any of claims 1 to 2.
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