CN115665668A - Indoor and outdoor seamless positioning method, system, equipment and medium - Google Patents
Indoor and outdoor seamless positioning method, system, equipment and medium Download PDFInfo
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Abstract
The invention discloses an indoor and outdoor seamless positioning method, system, equipment and medium, and relates to the technical field of information systems. The method comprises the following steps: acquiring the wireless signal intensity of a current positioning point; judging the type of the area where the current positioning point is located according to the wireless signal strength; when the current locating point is located in an indoor area, determining the position coordinate of the current locating point by adopting a WiFi position fingerprint locating technology; when the current positioning point is positioned in an outdoor area, determining the position coordinate of the current positioning point by adopting a GPS positioning technology; and when the current positioning point is positioned in the indoor and outdoor junction area, determining the position coordinate of the current positioning point by adopting an indoor and outdoor fusion positioning technology based on the KNN algorithm. The invention can realize smooth transition and seamless connection of indoor and outdoor positioning.
Description
Technical Field
The invention relates to the technical field of information systems, in particular to an indoor and outdoor seamless positioning method, system, equipment and medium.
Background
In the emerging industry of new generation information technology, location Based Services (LBS) has a great position, and in an outdoor environment, a GPS global positioning system can provide relatively accurate Location Services, but is affected by signal shielding and multipath effects in an urban canyon, and positioning signals of satellites are weakened, so that the positioning signals of the satellites lack indoor positioning capability. In order to make up for positioning blind areas of a satellite positioning system, indoor positioning technologies are developed rapidly, and indoor positioning technologies such as ultra wide band, near field communication, wiFi and radio frequency identification are developed, so that indoor high-precision positioning is realized.
With the continuous development of the location-based service field, LBS is no longer limited to a single indoor or outdoor location service, and is also a current research focus for location services in various complex scenes. At present, in an indoor and outdoor mixed scene, a plurality of positioning technologies are generally adopted to realize seamless coverage of positioning, so that seamless positioning in the mixed scene is realized, but a ping-pong effect of repeatedly switching the positioning technologies easily occurs in an indoor and outdoor junction area. In order to avoid operation waste caused by the ping-pong effect, some scholars propose an intelligent switching algorithm based on a threshold mechanism, and fuse indoor and outdoor positioning information in an indoor and outdoor junction area to realize smooth transition of positioning technology and precision under different scenes. When some scholars perform multi-positioning information fusion, although smooth switching of different positioning areas is realized, the scholars perform undifferentiated positioning on the whole area, neglect the precision difference of different positioning technologies and reduce the positioning precision of some areas.
At present, indoor and outdoor seamless positioning still has a lot of problems to be solved and improved, and through the research on the seamless positioning technology, the precision of maintaining and improving combined positioning is very important.
Disclosure of Invention
The invention aims to provide an indoor and outdoor seamless positioning method, a system, equipment and a medium so as to realize smooth transition and seamless connection of indoor and outdoor positioning.
In order to achieve the purpose, the invention provides the following scheme:
a method for seamless indoor and outdoor positioning, the method comprising:
acquiring the wireless signal intensity of a current positioning point;
judging the type of the area where the current positioning point is located according to the wireless signal intensity; the region types include: indoor area, outdoor area and indoor and outdoor boundary area;
when the current positioning point is positioned in an indoor area, determining the position coordinate of the current positioning point by adopting a WiFi position fingerprint positioning technology; when the current positioning point is located in an outdoor area, determining the position coordinate of the current positioning point by adopting a GPS positioning technology; when the current locating point is located in an indoor and outdoor junction area, determining the position coordinate of the current locating point by adopting an indoor and outdoor fusion locating technology based on a KNN algorithm;
the determining the position coordinates of the current positioning point by adopting the KNN algorithm-based indoor and outdoor fusion positioning technology specifically comprises the following steps:
determining online position fingerprint data of the current positioning point by adopting a WiFi position fingerprint positioning technology;
according to the online position fingerprint data and the offline position fingerprint database, determining the position coordinates of the first k reference points with the minimum weighted fingerprint Euclidean distance with the current positioning point as the position coordinates of k adjacent points; wherein k is a positive integer; the off-line position fingerprint database is a data set which is obtained in advance and comprises position coordinates of a plurality of different reference points and corresponding position fingerprint data;
determining the position coordinates of the (k + 1) th adjacent point of the current positioning point by adopting a GPS positioning technology;
determining a weighted fingerprint Euclidean distance between a (k + 1) th neighbor point and the current positioning point according to the online position fingerprint data and the offline position fingerprint database;
calculating the physical position distance between each adjacent point and the last certain point;
and determining the position coordinate of the current positioning point according to the position coordinate of each adjacent point, the weighted fingerprint Euclidean distance and the physical position distance.
Optionally, the determining, according to the online location fingerprint data and the offline location fingerprint database, location coordinates of the first k reference points with the smallest weighted fingerprint euclidean distance with the current location point as location coordinates of k neighboring points specifically includes:
calculating the probability that the signal intensity difference value of the wireless access point of each reference point in the current positioning point and the offline position fingerprint database is smaller than a set value;
calculating fingerprint Euclidean distances between the current positioning point and each reference point according to the online position fingerprint data and the offline position fingerprint database;
calculating the weighted fingerprint Euclidean distance between the current positioning point and each reference point according to the probability and the fingerprint Euclidean distance;
and comparing the Euclidean distance of each weighted fingerprint, and determining the position coordinates of the first k reference points with the minimum Euclidean distance of the weighted fingerprint of the current positioning point as the position coordinates of the k adjacent points.
Optionally, the determining, by using a GPS positioning technology, the position coordinate of the (k + 1) th neighboring point of the current positioning point specifically includes:
acquiring geodetic coordinates of the current positioning point;
converting the geodetic coordinates into Gaussian plane coordinates;
converting the Gaussian plane coordinate into an indoor position coordinate according to a conversion parameter matrix, and determining the indoor position coordinate as the position coordinate of the (k + 1) th adjacent point of the current positioning point; the parameter transformation matrix is determined according to at least two groups of known indoor position coordinates and corresponding Gaussian plane coordinates.
Optionally, the determining the position coordinate of the current positioning point according to the position coordinate of each of the neighboring points, the weighted fingerprint euclidean distance, and the physical position distance specifically includes:
taking the neighboring point with the physical position distance to the upper certain position point within a set range as a target neighboring point;
determining similarity weight coefficients of the current positioning point and each target adjacent point according to the weighted fingerprint Euclidean distance and the physical position distance;
and determining the position coordinates of the current positioning point according to the position coordinates of the target adjacent points and the similarity weight coefficients.
Optionally, the set range is [ R-0.5, R +0.5] meters; wherein, R is the unit moving distance of the positioned object and is determined according to the physical position distance of two adjacent historical positioning points.
Optionally, the weighted fingerprint euclidean distance between the current location point and each reference point is calculated according to the probability and the fingerprint euclidean distance, and a specific formula is as follows:
wherein: d 0,i The weighted fingerprint Euclidean distance between the current positioning point and the ith reference point; p is i The probability that the difference value of the signal strength of the current positioning point and the wireless access point of the ith reference point is smaller than a set value is obtained; e i And the Euclidean distance of the fingerprint between the current positioning point and the ith reference point.
Optionally, the determining, according to the weighted fingerprint euclidean distance and the physical location distance, a similarity weight coefficient between the current location point and each of the target neighboring points is performed according to the following specific formula:
wherein: w i Weighting coefficients of the similarity of the current positioning point and the ith target adjacent point; d 1,i The weighted fingerprint Euclidean distance between the current positioning point and the ith target neighbor point; l. the i The physical position distance between the ith target neighboring point and the last certain position point is obtained; k is a radical of 0 Is the number of target neighbors, and k 0 ≤k+1。
The invention also provides an indoor and outdoor seamless positioning system, which is applied to the method and comprises the following steps:
the signal intensity acquisition module is used for acquiring the wireless signal intensity of the current positioning point;
the area type determining module is used for judging the area type of the current positioning point according to the wireless signal intensity; the region types include: indoor area, outdoor area and indoor and outdoor boundary area;
the indoor area position coordinate determination module is used for determining the position coordinate of the current positioning point by adopting a WiFi position fingerprint positioning technology when the current positioning point is positioned in an indoor area;
the outdoor area position coordinate determination module is used for determining the position coordinate of the current positioning point by adopting a GPS positioning technology when the current positioning point is positioned in an outdoor area;
the indoor and outdoor boundary area position coordinate determination module is used for determining the position coordinate of the current positioning point by adopting an indoor and outdoor fusion positioning technology based on a KNN algorithm when the current positioning point is positioned in the indoor and outdoor boundary area;
the module for determining the position coordinates of the indoor and outdoor boundary areas specifically comprises:
the online position fingerprint data determining unit is used for determining the online position fingerprint data of the current positioning point by adopting a WiFi position fingerprint positioning technology;
the first adjacent point determining unit is used for determining the position coordinates of the first k reference points with the minimum Euclidean distance of the weighted fingerprint of the current positioning point as the position coordinates of the k adjacent points according to the online position fingerprint data and the offline position fingerprint database; wherein k is a positive integer; the off-line position fingerprint database is a data set which is obtained in advance and comprises position coordinates of a plurality of different reference points and corresponding position fingerprint data;
the second adjacent point determining unit is used for determining the position coordinates of the (k + 1) th adjacent point of the current positioning point by adopting a GPS positioning technology;
a weighted fingerprint Euclidean distance determining unit, configured to determine a weighted fingerprint Euclidean distance between the (k + 1) th neighboring point and the current location point according to the online location fingerprint data and the offline location fingerprint database;
a physical position distance calculating unit, configured to calculate a physical position distance between each neighboring point and the last fixed point;
and the current positioning point position coordinate determination unit is used for determining the position coordinate of the current positioning point according to the position coordinate of each adjacent point, the weighted fingerprint Euclidean distance and the physical position distance.
The invention also provides an electronic device, which comprises a memory and a processor, wherein the memory is used for storing the computer program, and the processor runs the computer program to enable the electronic device to execute the indoor and outdoor seamless positioning method.
The invention further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the indoor and outdoor seamless positioning method.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the indoor and outdoor seamless positioning method provided by the invention combines a GPS positioning technology, a WiFi position fingerprint positioning technology and an indoor and outdoor fusion positioning technology based on a KNN algorithm, can realize smooth switching of indoor and outdoor positioning, and ensures smooth transition and seamless connection of positioning technologies, algorithms, precision and coverage ranges in various scenes.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic diagram of an indoor and outdoor seamless positioning method according to an embodiment of the present invention;
FIG. 2 is a flowchart of an indoor and outdoor seamless positioning method according to an embodiment of the present invention;
fig. 3 is a flowchart of an indoor and outdoor fusion positioning technique based on the KNN algorithm according to an embodiment of the present invention;
fig. 4 is a block diagram of an indoor and outdoor seamless positioning system according to an embodiment of the present invention.
Description of the symbols: the system comprises a signal intensity acquisition module-1, an area type determination module-2, an indoor area position coordinate determination module-3, an outdoor area position coordinate determination module-4, an indoor and outdoor boundary area position coordinate determination module-5, an online position fingerprint data determination unit-51, a first adjacent point determination unit-52, a second adjacent point determination unit-53, a weighted fingerprint Euclidean distance determination unit-54, a physical position distance calculation unit-55 and a current positioning point position coordinate determination unit-56.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide an indoor and outdoor seamless positioning method, a system, equipment and a medium so as to realize smooth transition and seamless connection of indoor and outdoor positioning.
Aiming at the defects of low positioning precision, unsmooth positioning technology switching and the like existing in the current indoor and outdoor seamless positioning, the invention provides an indoor and outdoor seamless positioning scheme based on GPS and WiFi position fingerprints through research and improvement on a K-nearest neighbor (KNN) algorithm. The GPS is adopted outdoors, the improved WiFi position fingerprint positioning is adopted indoors, the indoor positioning precision is improved, the improved KNN algorithm is adopted in the indoor and outdoor boundary area to fuse the indoor and outdoor positioning data, and smooth switching of different positioning technologies is achieved.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Example one
The present embodiment provides an indoor and outdoor seamless positioning method, fig. 1 is a schematic diagram of an indoor and outdoor seamless positioning method according to an embodiment of the present invention, and fig. 2 is a flowchart of an indoor and outdoor seamless positioning method according to an embodiment of the present invention. As shown in fig. 1 and 2, the method includes:
step S1: and acquiring the wireless signal intensity of the current positioning point.
Step S2: judging the type of the area where the current positioning point is located according to the wireless signal intensity; the region types include: indoor area, outdoor area and indoor outer boundary area.
Specifically, since no wireless AP (i.e., wireless access point) is deployed outdoors, the WiFi signal gradually weakens, eventually losing location capability. Therefore, the WiFi signal strength is used to set two thresholds, i.e. an upper signal strength limit and a lower signal strength limit (and the upper signal strength limit is higher than the lower signal strength limit), a portion with the strongest signal, i.e. the portion with the wireless signal strength higher than the upper signal strength limit, is regarded as an indoor area, a portion with the weakest signal, i.e. the portion with the wireless signal strength lower than the lower signal strength limit, is regarded as an outdoor area, and a portion between the indoor area and the outdoor area are regarded as an indoor/outdoor border area.
And step S3: and when the current positioning point is positioned in an indoor area, determining the position coordinate of the current positioning point by adopting a WiFi position fingerprint positioning technology.
In practical application, wiFi position fingerprint positioning is adopted for indoor area positioning, and the position matching of online fingerprint data and an offline fingerprint database is mainly relied on. The traditional position fingerprint positioning method measures similarity difference between two points by using fingerprint Euclidean distance, but the simple Euclidean distance has limitation, for example, when the acquisition of a Received Signal Strength Indicator (RSSI) in online fingerprint data of a certain point has a large error, even if the rest RSSIs are close to a reference point of a neighbor, the calculated Euclidean distance is large, so that the reference point is not selected as the neighbor point. In order to reduce the influence caused by simple Euclidean distance, the invention endows a weight coefficient to the Euclidean distance of the current positioning point, calculates the probability that the difference value of the signal strength of each AP between the to-be-positioned point and the reference point is smaller than a set value according to the similarity of fingerprint data, and takes the reciprocal of the probability as the weight coefficient of the Euclidean distance, wherein the set value is preferably 1dBm.
The improved calculation formula of the Euclidean distance is as follows:
in the formula: d i The weighted fingerprint Euclidean distance (namely the improved fingerprint Euclidean distance) between the to-be-determined point and the ith reference point; p is i The probability that the signal strength difference is less than 1 dBm; rsi ij The RSSI value of the jth AP acquired in real time on the current positioning point is obtained; RSSI ij The RSSI value of the jth AP collected on the ith reference point in the off-line position fingerprint data is obtained; n is AP The number of APs; n is i(RSSI-rssi)＜1 The number of signal strength difference values smaller than 1dBm is represented; n is AP Indicating the number of APs. The Euclidean distance of the fingerprints between the two points is measured according to the method, and the front k adjacent points closest to the current positioning point can be selected from the off-line position fingerprint database.
And step S4: and when the current positioning point is positioned in an outdoor area, determining the position coordinate of the current positioning point by adopting a GPS positioning technology.
In practical applications, the outdoor GPS positioning system employs a geodetic coordinate system (H, B, L), i.e., a geodetic longitude L, a geodetic latitude B, and a geodetic altitude H. In the indoor positioning system, a plane coordinate system (x, y) is generally adopted, and in the seamless positioning between the indoor and the outdoor, the coordinate system needs to be unified. The invention adopts the Gaussian projection method to carry out the coordinate conversion of the outdoor positioning system, and the conversion process is as follows:
the geodetic coordinates (L, B) are first converted into gaussian planar coordinates (X, Y):
wherein, t, m, eta, L p All are intermediate parameters in the calculation process, and include: t = sin B; m = L p cos B；η＝e′cos B；L p ＝L-L 0 ；
In the formula: w is the arc length of meridian, N is the meridian radius of prime-unitary circle corresponding to the desired point, e' is the second eccentricity of ellipse (the spheroid shape is close to ellipsoid, also called ellipsoid or oblate spheroid, represents the mathematical curve of the size and shape of the earth, and is expressed by the long radius and oblate rate, because it is very close to ellipsoid, the reference ellipsoid is usually used to express the shape and size of the ellipsoid of the earth), B is the latitude of the desired point, L is the longitude of the desired point, and 0 the longitude is 3 degrees with the central meridian.
Then, the obtained gaussian plane coordinates (X, Y) are converted into rectangular coordinates (X, Y) under an indoor system. At least two sets of corresponding (X, Y) and (X, Y) data are determined, and a conversion parameter matrix U is calculated:
and obtaining the position coordinate in the indoor coordinate system through the coordinate conversion. And in the indoor and outdoor boundary areas, the position coordinate is used as a near neighbor point selected in the KNN positioning algorithm.
Step S5: and when the current positioning point is positioned in an indoor and outdoor boundary area, determining the position coordinate of the current positioning point by adopting an indoor and outdoor fusion positioning technology based on a KNN algorithm.
Specifically, the indoor and outdoor boundary area selects the first k neighbor points from an offline fingerprint database for WiFi location fingerprint positioning by using a KNN algorithm, and uses the positioning result of the GPS as the selectable (k + 1) th neighbor point, and determines the k +1 neighbor points in a range-limited manner, and selects more valuable neighbor points for final positioning estimation. Therefore, the positioning of the indoor and outdoor boundary area comprehensively considers the GPS positioning result and the WiFi position fingerprint positioning result, and the accuracy is higher.
Fig. 3 is a flowchart of an indoor and outdoor fusion positioning technology based on the KNN algorithm according to an embodiment of the present invention. As shown in fig. 3, step S5 specifically includes:
step S51: and determining the online position fingerprint data of the current positioning point by adopting a WiFi position fingerprint positioning technology.
Step S52: according to the online position fingerprint data and the offline position fingerprint database, determining the position coordinates of the first k reference points with the minimum weighted fingerprint Euclidean distance with the current positioning point as the position coordinates of k adjacent points; wherein k is a positive integer; the off-line position fingerprint database is a data set which is obtained in advance and comprises position coordinates of a plurality of different reference points and corresponding position fingerprint data.
The specific flow of step S52 is as follows:
(1) And calculating the probability that the signal intensity difference value of the wireless access point of each reference point in the current positioning point and the offline position fingerprint database is smaller than a set value.
(2) And calculating the Euclidean distance of the fingerprint between the current positioning point and each reference point according to the online position fingerprint data and the offline position fingerprint database.
(3) Calculating the weighted fingerprint Euclidean distance between the current positioning point and each reference point according to the probability and the fingerprint Euclidean distance, wherein the specific formula is as follows:
wherein: d 0,i The weighted fingerprint Euclidean distance between the current positioning point and the ith reference point; p i Signal strength of wireless access point for the current location point and ith reference pointThe probability that the difference is smaller than the set value; e i The calculation method for the euclidean distance between the current location point and the ith reference point is the same as that in step S3, and is not described herein again.
(4) And comparing the Euclidean distance of each weighted fingerprint, and determining the position coordinates of the first k reference points with the minimum Euclidean distance of the weighted fingerprint of the current positioning point as the position coordinates of the k adjacent points.
Step S53: and determining the position coordinates of the (k + 1) th adjacent point of the current positioning point by adopting a GPS positioning technology.
The specific flow of step S53 is as follows:
(1) And acquiring the geodetic coordinates of the current positioning point.
(2) And converting the geodetic coordinates into Gaussian plane coordinates.
(3) Converting the Gaussian plane coordinate into an indoor position coordinate according to a conversion parameter matrix, and determining the indoor position coordinate as the position coordinate of the (k + 1) th adjacent point of the current positioning point; the parameter transformation matrix is determined according to at least two groups of known indoor position coordinates and corresponding Gaussian plane coordinates. The above calculation process is the same as that in step S4, and is not described herein again.
Step S54: and determining the weighted fingerprint Euclidean distance between the (k + 1) th neighbor point and the current positioning point according to the online position fingerprint data and the offline position fingerprint database.
Step S55: calculating the physical position distance between each adjacent point and the last certain point, wherein the specific formula is as follows:
in the formula: l i The physical position distance between the ith adjacent point and the last certain position point is defined; (x) pre ,y pre ) The position coordinates of the upper certain position point are obtained; (x) i ,y i ) Is the position coordinate of the ith neighbor.
Step S56: and determining the position coordinate of the current positioning point according to the position coordinate of each adjacent point, the weighted fingerprint Euclidean distance and the physical position distance.
The specific flow of step S56 is as follows:
(1) And taking the neighboring point with the physical position distance within the set range from the upper certain position point as the target neighboring point. Preferably, the set range is [ R-0.5, R +0.5] meters; wherein, R is the unit moving distance of the positioned object and is determined according to the physical position distance of two adjacent historical positioning points. The invention adopts the range limiting mode to judge k +1 neighbor points: and taking the last certain position point as a judgment reference point, and selecting a neighboring point which is R +/-0.5 m away from the reference point as a target neighboring point. The target neighbor point is used as a more valuable neighbor point near the current positioning point, so that the subsequent position estimation can be more accurate. In this embodiment, R takes a value of 2.
(2) And determining a similarity weight coefficient between the current positioning point and each target adjacent point according to the weighted fingerprint Euclidean distance and the physical position distance.
In practical application, k meeting the condition is selected 0 And after the adjacent points are located, a weight decision mechanism is adopted for location estimation, a weight coefficient based on similarity is introduced, and the adjacent points are weighted and averaged to obtain a final location estimation point. The similarity between the adjacent point and the point to be located is measured by adopting the fingerprint distance and the physical position distance, and the physical position distance between the last certain point and the adjacent point can be used as a calculation basis because the actual position of the current locating point is unknown and the moving distance in the continuous sampling time is limited. The calculation formula of the similarity weight coefficient between the current positioning point and each target neighboring point is specifically as follows:
in the formula: w i Weighting the similarity between the current positioning point and the ith target neighbor point; d 1,i The weighted fingerprint Euclidean distance between the current positioning point and the ith target neighbor point; l i Is the ith orderThe physical position distance between the marking neighboring point and the last certain point; k is a radical of 0 Is the number of target neighbors, and k 0 ≤k+1。
(3) And determining the position coordinates of the current positioning point according to the position coordinates of the target adjacent points and the similarity weight coefficients. The final positioning result is expressed as:
in the formula: and (x, y) is the position coordinate of the current positioning point.
Example two
In order to implement the method corresponding to the above embodiment to achieve the corresponding functions and technical effects, an indoor and outdoor seamless positioning system is provided below, and fig. 4 is a block diagram of the indoor and outdoor seamless positioning system provided in the embodiment of the present invention. As shown in fig. 4, the system includes:
the signal strength obtaining module 1 is configured to obtain a wireless signal strength of a current location point.
The area type determining module 2 is used for judging the area type of the current positioning point according to the wireless signal intensity; the region types include: indoor area, outdoor area and indoor outer boundary area.
And the indoor area position coordinate determination module 3 is configured to determine the position coordinate of the current positioning point by using a WiFi position fingerprint positioning technology when the current positioning point is located in an indoor area.
And the outdoor area position coordinate determination module 4 is used for determining the position coordinate of the current positioning point by adopting a GPS positioning technology when the current positioning point is positioned in an outdoor area.
And the indoor and outdoor boundary area position coordinate determination module 5 is used for determining the position coordinate of the current positioning point by adopting an indoor and outdoor fusion positioning technology based on the KNN algorithm when the current positioning point is positioned in the indoor and outdoor boundary area.
The indoor and outdoor boundary area position coordinate determination module 5 specifically includes:
and an online location fingerprint data determining unit 51, configured to determine online location fingerprint data of the current location point by using a WiFi location fingerprint positioning technology.
A first neighboring point determining unit 52, configured to determine, according to the online location fingerprint data and the offline location fingerprint database, location coordinates of the first k reference points with the smallest weighted fingerprint euclidean distance with the current location point as location coordinates of the k neighboring points; wherein k is a positive integer; the off-line position fingerprint database is a data set which is obtained in advance and comprises position coordinates of a plurality of different reference points and corresponding position fingerprint data.
The second neighboring point determining unit 53 is configured to determine, by using a GPS positioning technology, a position coordinate of a (k + 1) th neighboring point of the current positioning point.
And a weighted fingerprint euclidean distance determining unit 54, configured to determine a weighted fingerprint euclidean distance between the k +1 th neighboring point and the current location point according to the online location fingerprint data and the offline location fingerprint database.
A physical location distance calculating unit 55, configured to calculate a physical location distance between each of the neighboring points and the last location point.
A current positioning point position coordinate determining unit 56, configured to determine a position coordinate of the current positioning point according to the position coordinate of each of the neighboring points, the weighted fingerprint euclidean distance, and the physical position distance.
EXAMPLE III
The embodiment of the present invention further provides an electronic device, which includes a memory and a processor, where the memory is used to store a computer program, and the processor is used to run the computer program so as to make the electronic device execute the indoor and outdoor seamless positioning method in the first embodiment. The electronic device may be a server.
In addition, the present invention further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the method for seamless indoor and outdoor positioning according to the first embodiment of the present invention is implemented.
At present, many problems to be solved and improved still exist in indoor and outdoor seamless positioning, and the maintenance and improvement of the precision of combined positioning are very important through the research on a seamless positioning technology. The invention provides an indoor and outdoor seamless positioning scheme based on a GPS and WiFi, which realizes smooth switching of indoor and outdoor positioning by using a KNN algorithm and ensures smooth transition and seamless connection of positioning technologies, algorithms, precision and coverage ranges in various scenes.
The outdoor GPS positioning is adopted, and longitude and latitude data of the positioning is converted into positioning data under an indoor coordinate system, so that fusion and switching of indoor and outdoor data are realized. WiFi position fingerprint positioning based on a KNN algorithm is adopted indoors, distance measurement and positioning estimation of the WiFi position fingerprint positioning are improved, and indoor positioning accuracy is improved. And selecting front K neighbor points from an offline fingerprint database of WiFi position fingerprint positioning by using a KNN algorithm in the indoor and outdoor boundary area, taking a positioning result of a GPS as selectable neighbor points, judging the K +1 neighbor points in a range limiting manner, and selecting more valuable neighbor points for final positioning estimation. Compared with the prior art, the indoor and outdoor seamless positioning method provided by the invention overcomes the defects of low positioning precision, unsmooth switching of positioning technology and the like existing in indoor and outdoor seamless positioning, and effectively improves the positioning precision and stability.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to assist in understanding the core concepts of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (10)
1. An indoor and outdoor seamless positioning method, which is characterized by comprising the following steps:
acquiring the wireless signal intensity of a current positioning point;
judging the type of the area where the current positioning point is located according to the wireless signal intensity; the region types include: indoor area, outdoor area and indoor and outdoor boundary area;
when the current positioning point is located in an indoor area, determining the position coordinate of the current positioning point by adopting a WiFi position fingerprint positioning technology; when the current positioning point is located in an outdoor area, determining the position coordinate of the current positioning point by adopting a GPS positioning technology; when the current locating point is located in an indoor and outdoor junction area, determining the position coordinate of the current locating point by adopting an indoor and outdoor fusion locating technology based on a KNN algorithm;
the determining the position coordinates of the current positioning point by adopting the KNN algorithm-based indoor and outdoor fusion positioning technology specifically comprises the following steps:
determining online position fingerprint data of the current positioning point by adopting a WiFi position fingerprint positioning technology;
according to the online position fingerprint data and the offline position fingerprint database, determining the position coordinates of the first k reference points with the minimum weighted fingerprint Euclidean distance with the current positioning point as the position coordinates of k adjacent points; wherein k is a positive integer; the off-line position fingerprint database is a data set which is obtained in advance and comprises position coordinates of a plurality of different reference points and corresponding position fingerprint data;
determining the position coordinates of the (k + 1) th adjacent point of the current positioning point by adopting a GPS positioning technology;
determining a weighted fingerprint Euclidean distance between a (k + 1) th neighbor point and the current positioning point according to the online position fingerprint data and the offline position fingerprint database;
calculating the physical position distance between each adjacent point and the last positioning point;
and determining the position coordinate of the current positioning point according to the position coordinate of each adjacent point, the weighted fingerprint Euclidean distance and the physical position distance.
2. The indoor and outdoor seamless positioning method of claim 1, wherein the determining, according to the online location fingerprint data and the offline location fingerprint database, the location coordinates of the first k reference points with the smallest euclidean distance with respect to the weighted fingerprint of the current positioning point as the location coordinates of the k neighboring points specifically comprises:
calculating the probability that the signal intensity difference value of the wireless access point of each reference point in the current positioning point and the offline position fingerprint database is smaller than a set value;
calculating fingerprint Euclidean distances between the current positioning point and each reference point according to the online position fingerprint data and the offline position fingerprint database;
calculating the weighted fingerprint Euclidean distance between the current positioning point and each reference point according to the probability and the fingerprint Euclidean distance;
and comparing the Euclidean distance of each weighted fingerprint, and determining the position coordinates of the first k reference points with the minimum Euclidean distance of the weighted fingerprint of the current positioning point as the position coordinates of the k adjacent points.
3. The indoor and outdoor seamless positioning method according to claim 1, wherein the determining the position coordinates of the (k + 1) th neighboring point of the current positioning point by using a GPS positioning technology specifically comprises:
acquiring geodetic coordinates of the current positioning point;
converting the geodetic coordinates into Gaussian plane coordinates;
converting the Gaussian plane coordinate into an indoor position coordinate according to a conversion parameter matrix, and determining the indoor position coordinate as the position coordinate of the (k + 1) th adjacent point of the current positioning point; the parameter transformation matrix is determined according to at least two groups of known indoor position coordinates and corresponding Gaussian plane coordinates.
4. The indoor and outdoor seamless positioning method of claim 1, wherein the determining the position coordinate of the current positioning point according to the position coordinate of each of the neighboring points, the weighted fingerprint euclidean distance, and the physical position distance specifically includes:
taking the neighboring point with the physical position distance to the upper certain position point within a set range as a target neighboring point;
determining similarity weight coefficients of the current positioning point and each target adjacent point according to the weighted fingerprint Euclidean distance and the physical position distance;
and determining the position coordinates of the current positioning point according to the position coordinates of the target adjacent points and the similarity weight coefficients.
5. The indoor and outdoor seamless positioning method according to claim 4, wherein the setting range is [ R-0.5, R +0.5] m; wherein, R is the unit moving distance of the positioned object and is determined according to the physical position distance of two adjacent historical positioning points.
6. The indoor and outdoor seamless positioning method of claim 2, wherein the weighted fingerprint euclidean distance between the current positioning point and each of the reference points is calculated according to the probability and the fingerprint euclidean distance, and the specific formula is as follows:
wherein: d 0,i The weighted fingerprint Euclidean distance between the current positioning point and the ith reference point; p is i The probability that the signal strength difference value of the current positioning point and the wireless access point of the ith reference point is smaller than a set value is obtained; e i And the Euclidean distance of the fingerprint between the current positioning point and the ith reference point.
7. The indoor and outdoor seamless positioning method of claim 4, wherein the similarity weight coefficient between the current positioning point and each of the target neighboring points is determined according to the weighted fingerprint Euclidean distance and the physical position distance, and the specific formula is as follows:
wherein: w i Weighting coefficients of the similarity of the current positioning point and the ith target adjacent point; d 1,i The weighted fingerprint Euclidean distance between the current positioning point and the ith target neighbor point; l. the i The physical position distance between the ith target neighboring point and the last certain position point is obtained; k is a radical of 0 Is the number of target neighbors, and k 0 ≤k+1。
8. An indoor and outdoor seamless positioning system, comprising:
the signal intensity acquisition module is used for acquiring the wireless signal intensity of the current positioning point;
the area type determining module is used for judging the area type of the current positioning point according to the wireless signal intensity; the region types include: indoor area, outdoor area and indoor and outdoor boundary area;
the indoor area position coordinate determination module is used for determining the position coordinate of the current positioning point by adopting a WiFi position fingerprint positioning technology when the current positioning point is positioned in an indoor area;
the outdoor area position coordinate determination module is used for determining the position coordinate of the current positioning point by adopting a GPS positioning technology when the current positioning point is positioned in an outdoor area;
the indoor and outdoor boundary area position coordinate determination module is used for determining the position coordinate of the current positioning point by adopting an indoor and outdoor fusion positioning technology based on a KNN algorithm when the current positioning point is positioned in the indoor and outdoor boundary area;
the module for determining the position coordinates of the indoor and outdoor boundary areas specifically comprises:
the online position fingerprint data determining unit is used for determining the online position fingerprint data of the current positioning point by adopting a WiFi position fingerprint positioning technology;
a first neighboring point determining unit, configured to determine, according to the online location fingerprint data and the offline location fingerprint database, location coordinates of the first k reference points with a minimum weighted fingerprint euclidean distance with the current location point as location coordinates of the k neighboring points; wherein k is a positive integer; the off-line position fingerprint database is a data set which is obtained in advance and comprises position coordinates of a plurality of different reference points and corresponding position fingerprint data;
the second adjacent point determining unit is used for determining the position coordinates of the (k + 1) th adjacent point of the current positioning point by adopting a GPS positioning technology;
a weighted fingerprint Euclidean distance determining unit, configured to determine a weighted fingerprint Euclidean distance between the (k + 1) th neighboring point and the current location point according to the online location fingerprint data and the offline location fingerprint database;
a physical position distance calculating unit, configured to calculate a physical position distance between each neighboring point and the last fixed point;
and the current positioning point position coordinate determining unit is used for determining the position coordinate of the current positioning point according to the position coordinate of each adjacent point, the weighted fingerprint Euclidean distance and the physical position distance.
9. An electronic device, comprising a memory for storing a computer program and a processor for executing the computer program to cause the electronic device to perform the indoor and outdoor seamless positioning method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that it stores a computer program which, when executed by a processor, implements the indoor-outdoor seamless positioning method according to any one of claims 1 to 7.
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