CN108632740B - Positioning method and device of user equipment - Google Patents
Positioning method and device of user equipment Download PDFInfo
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- CN108632740B CN108632740B CN201710168721.7A CN201710168721A CN108632740B CN 108632740 B CN108632740 B CN 108632740B CN 201710168721 A CN201710168721 A CN 201710168721A CN 108632740 B CN108632740 B CN 108632740B
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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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
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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
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
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Abstract
The invention discloses a positioning method and device of user equipment, and relates to the technical field of communication. The positioning method of the user equipment comprises the following steps: constructing a fingerprint database of the signal coverage area, wherein the fingerprint database comprises fingerprint records of sub-areas of the signal coverage area, and the signal coverage area is provided with M base stations; acquiring a fingerprint record corresponding to the position information as a corrected fingerprint record according to the position information and the measurement report data in the network signaling; replacing the fingerprint record of the sub-area corresponding to the position information in the fingerprint database by using the corrected fingerprint record to obtain a corrected fingerprint database; obtaining a fingerprint record of the user equipment according to the intensity of a received signal of the user equipment; acquiring a fingerprint record with the highest similarity to the fingerprint record of the user equipment in the corrected fingerprint database as a target fingerprint record; and taking the sub-area corresponding to the target fingerprint record as the position of the user equipment. The accuracy of the positioning of the user equipment can be improved.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method and an apparatus for positioning a user equipment.
Background
With the rapid development and wide application of the wireless local area network technology, the location positioning technology based on the coverage of the wireless local area network becomes a hotspot of location service research in indoor environment. The fingerprint positioning method can utilize the existing wireless local area network environment, does not need to change hardware equipment for time synchronization and angle measurement, and thus can realize positioning. Due to the characteristics of strong environmental adaptability, low cost and the like, the fingerprint positioning method becomes a commonly used positioning method.
During the propagation of the wireless signal in the space, the strength of the wireless signal decreases with the increase of the propagation distance. The closer the receiving device is to the wireless signal source, the stronger the received signal strength; the further the receiving device is from the wireless signal source, the weaker the received signal strength. The fingerprint positioning method at the present stage comprises two stages of off-line sampling and on-line positioning. In the off-line sampling stage, the received signal strength obtained by the base station through multiple sampling in each divided sub-area is obtained. And taking the average value of the received signal strength obtained by multiple times of sampling in a sub-area as the fingerprint record of the sub-area. And stores the fingerprint record in a fingerprint database. In the line positioning stage, the user equipment matches the base station identification obtained by actual measurement and the corresponding received signal strength with the received signal strength in the fingerprint database, selects K optimal fingerprint records closest to the received signal strength obtained by actual measurement, takes the similarity between each optimal fingerprint record and the received signal strength obtained by actual measurement as the weight, and takes the weighted average processing result of the positions of the K optimal fingerprint records as the position of the user equipment.
At present, the fingerprint records in the fingerprint database are generated by means of single data, and the accuracy of the fingerprint records in the fingerprint database is poor due to the poor accuracy of the single data, so that the accuracy of the positioning of the user equipment is reduced.
Disclosure of Invention
The embodiment of the invention provides a method and a device for positioning user equipment, which can improve the accuracy of positioning the user equipment.
In a first aspect, an embodiment of the present invention provides a method for positioning user equipment, including: constructing a fingerprint database of a signal coverage area, wherein the fingerprint database comprises fingerprint records of sub-areas of the signal coverage area, M base stations are arranged in the signal coverage area, and M is an integer greater than or equal to 1; acquiring a fingerprint record corresponding to the position information as a corrected fingerprint record according to the position information and the measurement report data in the network signaling; replacing the fingerprint record of the sub-area corresponding to the position information in the fingerprint database by using the corrected fingerprint record to obtain a corrected fingerprint database; obtaining a fingerprint record of the user equipment according to the intensity of a received signal of the user equipment; acquiring a fingerprint record with the highest similarity to the fingerprint record of the user equipment in the corrected fingerprint database as a target fingerprint record; and taking the sub-area corresponding to the target fingerprint record as the position of the user equipment.
In some embodiments of the first aspect, constructing a fingerprint database of signal coverage areas comprises: dividing a signal coverage area into at least two sub-areas; carrying out received signal strength test on the divided sub-areas to obtain a received signal strength vector of each divided sub-area, wherein the received signal strength vector comprises received signal strength intervals of M base stations received by the sub-areas; obtaining the probability density of the received signal intensity of the divided sub-regions by utilizing an approximate M-moment algorithm and Fourier transform according to the received signal intensity vector of the divided sub-regions and the characteristic function of the received signal intensity vector; the probability density is recorded as a fingerprint in a fingerprint database.
In some embodiments of the first aspect, acquiring, as a corrected fingerprint record, a fingerprint record corresponding to the location information according to the location information and the measurement report data in the network signaling includes: obtaining a received signal strength vector corresponding to the position information according to the position information and the measurement report data; according to the received signal intensity vector corresponding to the position information and an updated characteristic function, obtaining the probability density of the received signal intensity corresponding to the position information by using an approximate M-order moment algorithm and Fourier transform, and updating the characteristic function into the characteristic function of the received signal intensity vector corresponding to the position information; the probability density of the received signal strength corresponding to the location information is recorded as a corrected fingerprint.
In some embodiments of the first aspect, acquiring, as the target fingerprint record, the fingerprint record in the corrected fingerprint database having the highest similarity to the fingerprint record of the user equipment includes: respectively calculating KL distances between each probability density in the fingerprint database after correction and the probability density of the received signal strength of the user equipment; acquiring the probability density with the minimum distance from the probability density KL of the received signal strength of the user equipment in the fingerprint database after correction; and taking the probability density with the minimum distance from the probability density KL of the received signal strength of the user equipment in the fingerprint database after correction as a target fingerprint record.
In some embodiments of the first aspect, obtaining the probability density of the received signal strength of the partitioned sub-region using an approximate M-moment algorithm and fourier transform based on the received signal strength vector of the partitioned sub-region and a feature function of the received signal strength vector comprises: calculating each order moment of the received signal strength of the sub-region by using an approximate M order moment algorithm according to the received signal strength vector of the sub-region; and substituting each order moment into a characteristic function of the received signal intensity vector, and performing Fourier transform on the characteristic function to obtain the probability density of the received signal intensity of the sub-region.
In some embodiments of the first aspect, the location information comprises longitude information and latitude information.
In a second aspect, an embodiment of the present invention provides a positioning apparatus for a user equipment, including: the system comprises a construction module, a transmission module and a signal processing module, wherein the construction module is configured to construct a fingerprint database of a signal coverage area, the fingerprint database comprises fingerprint records of sub-areas of the signal coverage area, M base stations are arranged in the signal coverage area, and M is an integer greater than or equal to 1; the correction module is configured to acquire a fingerprint record corresponding to the position information as a corrected fingerprint record according to the position information and the measurement report data in the network signaling; the updating module is configured to replace the fingerprint record of the sub-area corresponding to the position information in the fingerprint database by using the corrected fingerprint record to obtain a corrected fingerprint database; the acquisition module is configured to obtain a fingerprint record of the user equipment according to the received signal strength of the user equipment; a target acquisition module configured to acquire a fingerprint record with the highest similarity to the fingerprint record of the user equipment in the corrected fingerprint database as a target fingerprint record; and the positioning module is configured to take the sub-area corresponding to the target fingerprint record as the position of the user equipment.
In some embodiments of the second aspect, the building block comprises: a dividing unit configured to divide a signal coverage area into at least two sub-areas; the first vector acquisition unit is configured to perform received signal strength test on the divided sub-areas to obtain received signal strength vectors of each divided sub-area, wherein the received signal strength vectors comprise received signal strength intervals of M base stations received by the sub-areas; a first calculation unit configured to obtain probability density of the received signal strength of the divided sub-regions by using an approximate M-order moment algorithm and fourier transform according to the received signal strength vector of the divided sub-regions and a feature function of the received signal strength vector; a first acquisition unit configured to record the probability density as a fingerprint in a fingerprint database.
In some embodiments of the second aspect, the correction module comprises: the second vector acquisition module is configured to obtain a received signal strength vector corresponding to the position information according to the position information and the measurement report data; the second calculation unit is configured to obtain the probability density of the received signal strength corresponding to the position information by using an approximate M-order moment algorithm and Fourier transform according to the received signal strength vector corresponding to the position information and an updated characteristic function, and the updated characteristic function is the characteristic function of the received signal strength vector corresponding to the position information; and a correction unit configured to record the probability density of the received signal strength corresponding to the position information as a corrected fingerprint.
In some embodiments of the second aspect, the target acquisition module comprises: a third calculation unit configured to calculate KL distances of respective probability densities in the corrected fingerprint database and a probability density of a received signal strength of the user equipment, respectively; a second obtaining unit configured to obtain a probability density with a smallest distance from a probability density KL of the received signal strength of the user equipment in the corrected fingerprint database; and the target acquisition unit is configured to take the probability density with the minimum distance from the probability density KL of the received signal strength of the user equipment in the corrected fingerprint database as the target fingerprint record.
In some embodiments of the second aspect, the first computing unit is specifically configured to: calculating each order moment of the received signal strength of the sub-region by using an approximate M order moment algorithm according to the received signal strength vector of the sub-region; and substituting each order moment into a characteristic function of the received signal intensity vector, and performing Fourier transform on the characteristic function to obtain the probability density of the received signal intensity of the sub-region.
In some embodiments of the second aspect, the location information comprises longitude information and latitude information.
The embodiment of the invention provides a positioning method and a positioning device of user equipment, which are used for constructing a fingerprint database of a signal coverage area. And acquiring a fingerprint record corresponding to the position information as a corrected fingerprint record according to the position information and the measurement report data in the network signaling. And replacing the fingerprint record of the sub-area corresponding to the position information in the fingerprint database by using the corrected fingerprint record to obtain the corrected fingerprint database. And taking the fingerprint record with the highest similarity with the fingerprint record of the user equipment in the corrected fingerprint database as a target fingerprint record, and taking the sub-area corresponding to the target fingerprint record as the position of the user equipment. The position information indicates an accurate position, and the parameters for calculating the fingerprint record at the more accurate position are obtained, so that the parameters for calculating the fingerprint record obtained by combining the position information can be ensured to be more accurate. Thus, according to the more accurate parameters for calculating the fingerprint record, the corrected fingerprint record is obtained, the accuracy of the fingerprint database for comparing with the fingerprint record of the user equipment is improved, and the accuracy of the positioning of the user equipment is further improved.
Drawings
The present invention will be better understood from the following description of specific embodiments thereof taken in conjunction with the accompanying drawings, in which like or similar reference characters designate like or similar features.
Fig. 1 is a flowchart of a positioning method of a ue according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating distribution of base stations in a signal coverage area according to an example of the embodiment of the present invention;
fig. 3 is a flowchart of a positioning method of a ue according to another embodiment of the present invention;
fig. 4 is a schematic structural diagram of a positioning apparatus of a ue according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a positioning apparatus of a ue according to another embodiment of the present invention.
Detailed Description
Features and exemplary embodiments of various aspects of the present invention will be described in detail below. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the present invention. The present invention is in no way limited to any specific configuration and algorithm set forth below, but rather covers any modification, replacement or improvement of elements, components or algorithms without departing from the spirit of the invention. In the drawings and the following description, well-known structures and techniques are not shown in order to avoid unnecessarily obscuring the present invention.
The positioning method and device of the user equipment in the embodiment of the invention are applied to a scene of positioning the user equipment by utilizing a fingerprint positioning technology. The fingerprint positioning technology is a technology for determining the position of user equipment according to the sum of the received signal strengths received by the user equipment under a wireless signal fading model by utilizing the principle that the signal strength of a wireless signal is weakened along with the increase of a propagation distance in the process of space propagation.
Fig. 1 is a flowchart of a positioning method of a user equipment according to an embodiment of the present invention. As shown in fig. 1, the positioning method of the user equipment includes steps 101 to 106.
In step 101, a fingerprint database of signal coverage areas is constructed.
Wherein the fingerprint database comprises fingerprint records of sub-areas of a signal coverage area, the signal coverage area has M base stations, and M is an integer greater than or equal to 1. For example, fig. 2 is a schematic distribution diagram of base stations in a signal coverage area according to an example of the embodiment of the present invention. Assuming that there are 3 base stations in the signal coverage area, the distribution of the base stations is shown in fig. 2. Wherein the signal coverage area is divided into k sub-areas, respectively P1、P2、……、PkEach sub-region having a fingerprint record. The fingerprint record may be the Received Signal Strength (RSS) of the sub-region, or may be the probability density of the Received Signal Strength of the sub-region.
It should be noted that, because parameters of the base station itself may change, for example, the transmission angle of the base station antenna changes, the received signal strength of the sub-area also changes. The number of base stations in the signal coverage area may also change, for example, if a base station is newly established or cancelled, the received signal strength of the sub-area may also change. Thus, the fingerprint records in the constructed fingerprint database may be updated periodically or aperiodically.
In step 102, according to the location information and the measurement report data in the network signaling, a fingerprint record corresponding to the location information is obtained as a corrected fingerprint record.
Wherein location information and Measurement Report (MR) data can be extracted from the network signaling. In one example, the network signaling may be LTE (Long Term Evolution) signaling. The LTE signaling contains S1-U data. The S1-U data is data of the S1 interface for the user plane. The S1 interface is a communication interface between the LTE base station and the packet core network. When a user sends data to the outside through an APP (Application), the user carries some location information having a positioning function. For example, the APP-URL (Application-Uniform Resource Locator) in the S1-U data may include longitude information and latitude information of the ue or the test device.
Since the network signaling may come from the user equipment or the test equipment, the location information in the data is sent out by using the APPs, but the format of the location information in the data sent out by each APP may be different. Position information in different formats needs to be converted into position information in a uniform format to correct the deviation. For example, the position information of the Baidu map adopts Baidu coordinates BD09, the position information of the Google map, the Gauss map and the Tencent map adopts Mars coordinates GCJ02, and the user equipment or the test equipment measures the adopted GPS coordinates by using a GPS (Global Positioning System). Both the hundredth coordinates BD09 and the mars coordinates GCJ02 may be converted to GPS coordinates.
The measurement report data may include a timestamp, MME UE S1AP ID (Mobility Management Entity User Equipment S1 Application identity, mobile Management node-User terminal-S1 interface Application identity) associated User location information and RSRP (Reference Signal Receiving Power) in MRO (Maintenance Repair Operation) information. The received signal strength can be obtained according to the measurement report data, and the technology for obtaining the received signal strength according to the measurement report data is mature, and the existing method can be referred to, and is not described herein again.
The location information can provide the precise location of the user equipment or the test equipment, so that according to the precise location provided by the location information and the measurement report data, a more precise fingerprint record of the sub-area is obtained, such as the received signal strength or the probability density of the received signal strength.
In step 103, the corrected fingerprint record is used to replace the fingerprint record of the sub-area corresponding to the location information in the fingerprint database, so as to obtain a corrected fingerprint database.
For example, table one is a table of the corrected fingerprint records and the corresponding location information of the fingerprint records. Wherein, the data corresponding to 1, 2 and 3 are the received signal strengths of three base stations received at one position respectively. Table two is the received signal strength recorded in the fingerprint database before correction. Table three is the received signal strength recorded in the fingerprint database after correction.
Watch 1
Watch two
Watch III
From table one, table two and table three, the fingerprint records of sub-regions P2 and P3 in table two are replaced with the fingerprint records of sub-regions P2 and P3 in table one, and a corrected fingerprint database as shown in table three is obtained after the replacement.
The received signal strength in the table may be a probability density of the received signal strength, and is not limited herein.
In order to simplify the operation, if the corrected fingerprint record obtained from the location information in the network signaling and the measurement report data is the same as the fingerprint record before correction, the fingerprint record before correction does not need to be replaced. If the corrected fingerprint record obtained according to the position information and the measurement report data in the network signaling is different from the fingerprint record before correction, the fingerprint record before correction needs to be replaced by the fingerprint record after correction.
In step 104, a fingerprint record of the user equipment is obtained according to the received signal strength of the user equipment.
If the fingerprint record is the received signal strength, the fingerprint record of the user equipment is the received signal strength of the user equipment. If the fingerprint record is the probability density of the received signal strength, the fingerprint record of the user equipment is the probability density of the received signal strength calculated by using the received signal strength. If the fingerprint record is other parameters, the fingerprint record of the user equipment is other parameters calculated by using the strength of the received signal.
In step 105, the fingerprint record with the highest similarity to the fingerprint record of the user equipment in the corrected fingerprint database is acquired as the target fingerprint record.
Wherein a higher similarity indicates that the fingerprint record of the user device is closer to the fingerprint record in the corrected fingerprint database. The closer the fingerprint record of the user device is to the fingerprint record in the corrected fingerprint database, the closer the location of the user device is to the location corresponding to the fingerprint record in the corrected fingerprint database. The target fingerprint record is the fingerprint record with the highest similarity to the fingerprint data of the user device.
In step 106, the sub-area corresponding to the target fingerprint record is used as the location of the user equipment.
That is, the location corresponding to the target fingerprint can be regarded as the location of the user equipment, so as to realize the positioning of the user equipment.
The embodiment of the invention provides a positioning method of user equipment, which is used for constructing a fingerprint database of a signal coverage area. And acquiring a fingerprint record corresponding to the position information as a corrected fingerprint record according to the position information and the measurement report data in the network signaling. And replacing the fingerprint record of the sub-area corresponding to the position information in the fingerprint database by using the corrected fingerprint record to obtain the corrected fingerprint database. And taking the fingerprint record with the highest similarity with the fingerprint record of the user equipment in the corrected fingerprint database as a target fingerprint record, and taking the sub-area corresponding to the target fingerprint record as the position of the user equipment. The position information indicates an accurate position, and the parameters for calculating the fingerprint record at the more accurate position are obtained, so that the parameters for calculating the fingerprint record obtained by combining the position information can be ensured to be more accurate. Thus, according to the more accurate parameters for calculating the fingerprint record, the corrected fingerprint record is obtained, the accuracy of the fingerprint database for comparing with the fingerprint record of the user equipment is improved, and the accuracy of the positioning of the user equipment is further improved.
Fig. 3 is a flowchart of a positioning method of a ue according to another embodiment of the present invention. FIG. 3 differs from FIG. 1 in that step 101 in FIG. 1 can be subdivided into steps 1011-1014 in FIG. 3; step 102 in FIG. 1 can be subdivided into steps 1021-1023 in FIG. 3; step 105 in FIG. 1 may be subdivided into steps 1051-1053 in FIG. 3.
In step 1011, the signal coverage area is divided into at least two sub-areas.
The signal coverage area may be divided into at least two sub-areas with the same shape and size, or the signal coverage area may be transposed into at least two sub-areas with different shapes and sizes. In one example, the partitioned sub-regions may also be determined from drive test or sweep data. The specific division is not limited herein.
In step 1012, the divided sub-regions are subjected to a received signal strength test to obtain a received signal strength vector of each divided sub-region.
The received signal strength test refers to a test that the test equipment is used for receiving signals sent by the base station in different sub-areas, so as to obtain the received signal strength of the signals of different base stations received by different sub-areas. The received signal strength vector comprises received signal strength intervals of M base stations received by a subregion PiCan be written as (RSS)1，RSS2，…， RSSM)i。RSS1Is a sub-region PiReceived signal strength interval, RSS, of received base station 1 signals2Is a sub-region PiReceived signal strength interval, RSS, of the received base station 2 signalMIs a sub-region PiThe received signal strength interval of the received base station M signal. For example, RSS2＝[-120dBm，-90dBm]。
In step 1013, the probability density of the received signal strength of the divided sub-regions is obtained by using an approximate M-order moment algorithm and fourier transform according to the received signal strength vector of the divided sub-regions and the feature function of the received signal strength vector.
According to the received signal strength vectors of the divided sub-areas, the range of the received signal strength of the signals of each base station received by the sub-areas can be obtained. If there are M base stations in the signal coverage area, the M-moment algorithm is used. For example, if there are 4 base stations in the signal coverage area, the 4 th moment algorithm is used.
In one example, the order moments of the received signal strength of the sub-region may be calculated by using an approximate M-order moment algorithm according to the received signal strength vector of the sub-region. And substituting each order moment into a characteristic function of the received signal intensity vector, and performing Fourier transform on the characteristic function to obtain the probability density of the received signal intensity of the sub-region. Specifically, the probability density of the received signal strength of the divided sub-areas may be calculated using the following equations (1) to (5):
fS(ω)＝E{ejωS} (2)
wherein M is the number of base stations in a signal coverage area, M is an integer and is more than or equal to 1 and less than or equal to M; p is the number of test samples in the signal strength test, siA received signal strength vector in the ith test sample for the subregion; e { S }mThe m-order moment of the received signal strength of the subareas; f. ofS(ω) is a feature function of the received signal strength vector; f. fS(x) Is the probability density of the received signal strength.
Equation (3) is the Taylor formula expansion series form of equation (2). Since the infinite order moment of the formula (3) cannot be realized in the engineering, the formula (3) is modified to the formula (4) using the M order moment. The characteristic function of the received signal strength vector can be approximately obtained by substituting each order moment obtained by calculation in the formula (1) into the formula (4). And carrying out Fourier transform according to the definition of the characteristic function of the received signal strength vector to obtain the probability density of the received signal strength.
In step 1014, the probability density is recorded as a fingerprint in a fingerprint database.
In step 1021, a received signal strength vector corresponding to the location information is obtained based on the location information and the measurement report data.
In step 1022, according to the received signal strength vector corresponding to the location information and the updated eigen function, the probability density of the received signal strength corresponding to the location information is obtained by using the approximate M-moment algorithm and fourier transform.
And recording the fingerprint as the probability density of the received signal strength, and obtaining a corresponding received signal strength vector according to the received signal strength corresponding to the position information. The received signal strength obtained from the location information is more accurate, and thus, the received signal strength obtained from the location information may be different from the received signal strength unrelated to the location information. Therefore, the updated feature function may be different from the feature function, and the updated feature function is the feature function of the received signal strength vector corresponding to the location information. . Based on the more accurate received signal strength vector and the updated eigen function, a more accurate fingerprint record, i.e. a corrected fingerprint record, can be obtained.
In step 1023, the probability density of the received signal strength corresponding to the location information is recorded as a corrected fingerprint.
In step 1051, KL distances are calculated for each probability density in the corrected fingerprint database and the probability density of the received signal strength of the user equipment, respectively.
In this embodiment, the similarity between the probability density in the fingerprint database after correction and the probability density of the user equipment is obtained by using a KL Distance (Kullback-Leibler Distance) formula. It should be noted that the probability density of the ue is the probability density of the received signal strength of the ue. The KL distance formula is the following formula (6):
wherein D (f)Sp(x)||fSq(x) KL distance which is the probability density in the fingerprint database after correction and the probability density of the user equipment; f. ofSq(x) Probability density for the user equipment; f. ofSp(x) Is the probability density in the fingerprint database after correction.
In step 1052, the probability density with the smallest distance to the probability density KL of the received signal strength of the user equipment in the corrected fingerprint database is obtained.
Wherein, the smaller the KL distance is, the greater the similarity between the probability density of the user equipment and the probability density in the corrected fingerprint database is. The KL distance formula represents a loss of the number of bits generated when the probability distribution becomes the probability density of the user equipment based on the probability distribution in the fingerprint database after correction. D (f) if the probability density in the corrected fingerprint database is identical to the probability density distribution of the user equipmentSp(x)||fSq(x) 0), that is, the number of lost bits is 0.
In step 1053, the probability density with the smallest distance to the probability density KL of the received signal strength of the user equipment in the corrected fingerprint database is recorded as the target fingerprint.
And calculating KL distance between each probability density in the fingerprint database after correction and the probability density of the user equipment, and taking the probability density with the minimum distance between the probability density KL in the fingerprint database after correction and the probability density of the user equipment as a target fingerprint record. The target fingerprint record is the closest, most similar probability density to that of the user device.
Fig. 4 is a schematic structural diagram of a positioning apparatus 200 of a user equipment according to an embodiment of the present invention. As shown in fig. 4, the positioning apparatus 200 of the user equipment includes a construction module 201, a correction module 202, an update module 203, an acquisition module 204, an object acquisition module 205, and a positioning module 206.
A building module 201 configured to build a fingerprint database of the signal coverage area, the fingerprint database comprising fingerprint records of sub-areas of the signal coverage area, the signal coverage area having M base stations, M being an integer greater than or equal to 1.
And the correcting module 202 is configured to obtain a fingerprint record corresponding to the location information as a corrected fingerprint record according to the location information and the measurement report data in the network signaling.
In one example, the location information may include longitude information and latitude information.
An updating module 203 configured to replace the fingerprint record of the sub-region corresponding to the location information in the fingerprint database with the corrected fingerprint record, resulting in a corrected fingerprint database.
The obtaining module 204 is configured to obtain a fingerprint record of the user equipment according to the received signal strength of the user equipment.
A target obtaining module 205 configured to obtain a fingerprint record with the highest similarity to the fingerprint record of the user equipment in the corrected fingerprint database as a target fingerprint record.
A positioning module 206 configured to take the sub-region corresponding to the target fingerprint record as the location of the user equipment.
The embodiment of the invention provides a positioning device of user equipment, and a construction module constructs a fingerprint database of a signal coverage area. And the correction module acquires the fingerprint record corresponding to the position information as a corrected fingerprint record according to the position information and the measurement report data in the network signaling. And the updating module replaces the fingerprint record of the sub-area corresponding to the position information in the fingerprint database by using the corrected fingerprint record to obtain the corrected fingerprint database. The target acquisition module takes the fingerprint record with the highest similarity with the fingerprint record of the user equipment in the corrected fingerprint database as a target fingerprint record, and the positioning module takes the sub-area corresponding to the target fingerprint record as the position of the user equipment. The position information indicates an accurate position, and the parameters for calculating the fingerprint record at the more accurate position are obtained, so that the parameters for calculating the fingerprint record obtained by combining the position information can be ensured to be more accurate. Thus, according to the more accurate parameters for calculating the fingerprint record, the corrected fingerprint record is obtained, the accuracy of the fingerprint database for comparing with the fingerprint record of the user equipment is improved, and the accuracy of the positioning of the user equipment is further improved.
Fig. 5 is a schematic structural diagram of a positioning apparatus 200 of a ue according to another embodiment of the present invention. Fig. 5 is different from fig. 4 in that the build module 201 in fig. 4 may include the dividing unit 2011, the first vector acquisition unit 2012, the first calculation unit 2013, and the first acquisition unit 2014 in fig. 5; the correction module 202 in fig. 4 may include the second vector acquisition module 2021, the second calculation unit 2022, and the correction unit 2023 in fig. 5; the target acquisition module 205 of fig. 4 may include the third computing unit 2051, the second acquisition unit 2052, and the target acquisition unit 2053 of fig. 5.
Therein, the dividing unit 2011 is configured to divide the signal coverage area into at least two sub-areas.
The first vector obtaining unit 2012 is configured to perform a received signal strength test on the divided sub-areas to obtain a received signal strength vector of each of the divided sub-areas, where the received signal strength vector includes received signal strength intervals of M base stations received by the sub-area.
A first calculating unit 2013 configured to obtain probability density of the received signal strength of the divided sub-regions by using an approximate M-order moment algorithm and fourier transform according to the received signal strength vector of the divided sub-regions and a feature function of the received signal strength vector.
In one example, the first calculating unit 2013 is specifically configured to calculate respective orders of the received signal strengths of the sub-regions by using an approximate M-order algorithm according to the received signal strength vectors of the sub-regions; and substituting each order moment into a characteristic function of the received signal intensity vector, and performing Fourier transform on the characteristic function to obtain the probability density of the received signal intensity of the sub-region.
A first obtaining unit 2014 configured to record the probability density as a fingerprint in a fingerprint database.
The second vector obtaining module 2021 is configured to obtain, according to the location information and the measurement report data, a received signal strength vector corresponding to the location information.
The second calculating unit 2022 is configured to obtain the probability density of the received signal strength corresponding to the position information by using an approximate M-order moment algorithm and fourier transform according to the received signal strength vector corresponding to the position information and an updated feature function, where the updated feature function is the feature function of the received signal strength vector corresponding to the position information.
A correction unit 2023 configured to record the probability density of the received signal strength corresponding to the position information as a corrected fingerprint.
A third calculation unit 2051 configured to calculate KL distances of the respective probability densities in the corrected fingerprint database to the probability density of the received signal strength of the user equipment, respectively.
A second obtaining unit 2052 configured to obtain a probability density in the corrected fingerprint database having a smallest distance to the probability density KL of the received signal strength of the user equipment.
A target acquisition unit 2053 configured to record, as a target fingerprint, a probability density in the corrected fingerprint database that is the smallest distance from the probability density KL of the received signal strength of the user equipment.
It should be clear that the embodiments in this specification are described in a progressive manner, and the same or similar parts in the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. For device embodiments, reference is made to the description of the method embodiments. The present invention is not limited to the specific steps and structures described above and shown in the drawings. Also, a detailed description of known process techniques is omitted herein for the sake of brevity.
The functional blocks and functional units shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information.
Claims (10)
1. A method for positioning a user equipment, comprising:
constructing a fingerprint database of a signal coverage area, wherein the fingerprint database comprises fingerprint records of sub-areas of the signal coverage area, the signal coverage area is provided with M base stations, and M is an integer greater than or equal to 1;
acquiring a fingerprint record corresponding to the position information as a corrected fingerprint record according to the position information and the measurement report data in the network signaling;
replacing the fingerprint record of the sub-area corresponding to the position information in the fingerprint database by using the corrected fingerprint record to obtain a corrected fingerprint database;
obtaining a fingerprint record of user equipment according to the intensity of a received signal of the user equipment;
acquiring a fingerprint record with the highest similarity to the fingerprint record of the user equipment in the corrected fingerprint database as a target fingerprint record;
taking a sub-area corresponding to the target fingerprint record as the position of the user equipment;
the fingerprint database for constructing the signal coverage area comprises the following steps:
dividing the signal coverage area into at least two sub-areas;
performing received signal strength test on the divided sub-areas to obtain a received signal strength vector of each divided sub-area, wherein the received signal strength vector comprises received signal strength intervals of the M base stations received by the sub-areas;
obtaining the probability density of the received signal intensity of the divided sub-regions by utilizing an approximate M-order moment algorithm and Fourier transform according to the received signal intensity vector of the divided sub-regions and the characteristic function of the received signal intensity vector;
taking the probability density as the fingerprint record in the fingerprint database.
2. The method according to claim 1, wherein the obtaining, as the corrected fingerprint record, the fingerprint record corresponding to the location information according to the location information and the measurement report data in the network signaling comprises:
obtaining a received signal strength vector corresponding to the position information according to the position information and the measurement report data;
obtaining the probability density of the received signal intensity corresponding to the position information by using an approximate M-order moment algorithm and Fourier transform according to the received signal intensity vector corresponding to the position information and an updated characteristic function, wherein the updated characteristic function is the characteristic function of the received signal intensity vector corresponding to the position information;
and recording the probability density of the received signal strength corresponding to the position information as a corrected fingerprint.
3. The method according to claim 1, wherein the acquiring, as the target fingerprint record, the fingerprint record with the highest similarity to the fingerprint record of the user equipment in the corrected fingerprint database comprises:
respectively calculating KL distances between each probability density in the fingerprint database after correction and the probability density of the received signal strength of the user equipment;
acquiring the probability density with the minimum distance from the probability density KL of the received signal strength of the user equipment in the fingerprint database after correction;
and taking the probability density with the minimum distance from the probability density KL of the received signal strength of the user equipment in the fingerprint database after correction as a target fingerprint record.
4. The method of claim 1, wherein obtaining the probability density of the received signal strength of the partitioned sub-region by using an approximate M-moment algorithm and Fourier transform according to the received signal strength vector of the partitioned sub-region and the eigenfunction of the received signal strength vector comprises:
calculating each order moment of the received signal strength of the sub-region by using an approximate M order moment algorithm according to the received signal strength vector of the sub-region;
and substituting each order moment into a characteristic function of the received signal intensity vector, and performing Fourier transform on the characteristic function to obtain the probability density of the received signal intensity of the sub-region.
5. The method of claim 1 or 2, wherein the location information comprises longitude information and latitude information.
6. A positioning apparatus of a user equipment, comprising:
a construction module configured to construct a fingerprint database of a signal coverage area, the fingerprint database including fingerprint records of sub-areas of the signal coverage area, the signal coverage area having M base stations therein, M being an integer greater than or equal to 1;
the correction module is configured to acquire a fingerprint record corresponding to the position information as a corrected fingerprint record according to the position information and the measurement report data in the network signaling;
an updating module configured to replace the fingerprint record of the sub-region corresponding to the location information in the fingerprint database with the corrected fingerprint record to obtain a corrected fingerprint database;
the acquisition module is configured to obtain a fingerprint record of the user equipment according to the received signal strength of the user equipment;
a target acquisition module configured to acquire a fingerprint record with the highest similarity to the fingerprint record of the user equipment in the corrected fingerprint database as a target fingerprint record;
a positioning module configured to take a sub-region corresponding to the target fingerprint record as a location of the user equipment;
the building module comprises:
a dividing unit configured to divide the signal coverage area into at least two sub-areas;
a first vector obtaining unit, configured to perform a received signal strength test on the divided sub-areas to obtain a received signal strength vector of each of the divided sub-areas, where the received signal strength vector includes received signal strength intervals of the M base stations received by the sub-area;
a first calculating unit, configured to obtain probability density of the divided received signal strength of the sub-region by using an approximate M-order moment algorithm and fourier transform according to the divided received signal strength vector of the sub-region and a feature function of the received signal strength vector;
a first acquisition unit configured to record the probability density as the fingerprint in the fingerprint database.
7. The apparatus of claim 6, wherein the correction module comprises:
a second vector acquisition module configured to obtain a received signal strength vector corresponding to the location information according to the location information and the measurement report data;
a second calculating unit, configured to obtain, by using an approximate M-order moment algorithm and fourier transform, a probability density of received signal strength corresponding to the location information according to a received signal strength vector corresponding to the location information and an updated feature function, where the updated feature function is a feature function of the received signal strength vector corresponding to the location information;
a correction unit configured to record, as a corrected fingerprint, a probability density of received signal strength corresponding to the position information.
8. The apparatus of claim 6, wherein the target acquisition module comprises:
a third calculation unit configured to calculate KL distances of respective probability densities in the corrected fingerprint database and a probability density of a received signal strength of the user equipment, respectively;
a second obtaining unit configured to obtain a probability density with a smallest distance from a probability density KL of the received signal strength of the user equipment in the corrected fingerprint database;
and the target acquisition unit is configured to take the probability density with the minimum distance from the probability density KL of the received signal strength of the user equipment in the corrected fingerprint database as a target fingerprint record.
9. The apparatus of claim 6, wherein the first computing unit is specifically configured to:
calculating each order moment of the received signal strength of the sub-region by using an approximate M order moment algorithm according to the received signal strength vector of the sub-region;
and substituting each order moment into a characteristic function of the received signal intensity vector, and performing Fourier transform on the characteristic function to obtain the probability density of the received signal intensity of the sub-region.
10. The apparatus of claim 6 or 7, wherein the location information comprises longitude information and latitude information.
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| CN112824831A (en) * | 2019-11-20 | 2021-05-21 | 广东博智林机器人有限公司 | Fingerprint database updating method, device, equipment and storage medium |
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