CN115580825A - Method for acquiring indoor position based on WiFi positioning - Google Patents

Abstract

The invention discloses a method for acquiring indoor position based on WiFi positioning, which comprises the following steps: s1, installing an ap and collecting data; s2, RSSI ranging; s3, acquiring wifi signal intensity distribution data around the terminal; s4, judging a point closest to the real terminal position; interference caused by wifi signal fluctuation is reduced, dependence on accuracy of a single wifi value can be eliminated when the position is calculated by adopting wave floating, filtering smoothing processing is carried out at the later stage of the algorithm, position jitter caused by signal fluctuation can be prevented, and the algorithm is close to a real use scene; the space model of signal intensity and position can be established under the effect of many ap equipment, and signal intensity and ideal value fit in the space model according to, confirm the most reliable coordinate point, and then confirm the terminal position to change according to the coordinate point division multiple can realize the change to positioning accuracy, reduced the error that comes from signal intensity, signal fluctuation, signal source and bring less, improved the positioning accuracy.

Description

Method for acquiring indoor position based on WiFi positioning

Technical Field

The invention relates to the field of indoor signal positioning, in particular to a method for acquiring an indoor position based on WiFi positioning.

Background

In large places such as hospitals, office buildings, large shopping malls, large low parking lots and the like, the indoor environment is relatively complex, a plurality of signal sources are provided, and GPS signals are relatively weak. The indoor position information of the mobile terminal or the holder of the mobile terminal is difficult to determine, and based on the popularization of related hardware equipment of a WiFi chip, researches aiming at WiFi positioning algorithms are mostly carried out at present, such as methods of TOA measurement, triangulation positioning and the like; the existing WiFi-based device position is deduced through an algorithm, for example, a triangulation method draws a circle by taking a WiFi coordinate as a circle center, the radius of the circle is the distance between the device and a hot spot, the position of the device may be at the position where multiple circles overlap, the positioning error is large, and the calculation amount of the adopted two-circle model is large. The fingerprint algorithm means that the mobile phone scans all surrounding WiFi. At this time, all the MAC addresses which can be acquired are compared with the data recorded on the previous equipment, and the fingerprints which are acquired before are matched, so that the coordinates at this time can be regarded as the coordinates pointed by the fingerprints, the acquisition amount is very large, the requirements on the performance of a server and data storage are high, and the positioning result is not ideal. Whereas the TOA time-of-arrival and angle-based approach requires precise measurement instrument and clock synchronization.

For example, a wifi-based indoor positioning and verification system disclosed in chinese patent literature, the publication number of which is: CN110366103B, which discloses at least one RFID reader dispersedly arranged in a positioning area; at least three wireless AP machines which are dispersedly arranged in the positioning area; the mobile equipment is connected with at least three wireless AP machines and acquires wireless signal intensity; the positioning server collects the wireless signal intensity and adopts a differential algorithm to position the mobile equipment, but the scheme has more equipment and larger positioning errors.

Disclosure of Invention

In order to solve the problems of unsatisfactory positioning result, large positioning error and overhigh instrument requirement in the prior art, the invention provides a method for acquiring an indoor position based on WiFi positioning.

In order to achieve the above purpose, the invention provides the following technical scheme:

a method for obtaining indoor position based on WiFi positioning comprises the following steps:

s1, installing an ap and collecting data;

s2, RSSI ranging;

s3, acquiring wifi signal intensity distribution data around the terminal;

and S4, judging the point closest to the real terminal position. RSSI is the strength indication of the received signal; ap is a wireless access point, a wireless switch for a wireless network, and is also the core of the wireless network. The method comprises the steps of installing a plurality of aps to different indoor positions, collecting the distance and the signal intensity of the aps nearby through a terminal, establishing a space model according to the signal intensity, fitting the space model with ideal data, and determining a point closest to the real position of the terminal according to a fitting result. The point closest to the real terminal position can be judged by establishing an intensity signal space model near the terminal and fitting intensity data.

Preferably, the S1 includes grouping and marking data, and collects gps coordinates and corresponding mac addresses of each ap to establish an ap information database. A plurality of ap devices are installed in each floor of the building, one or more ap devices are installed in each floor, and the ap devices in the multi-floor building are grouped into tag data. The ap installation height of each layer is consistent, and errors are further reduced. A spatial area located inside a multi-story building can be established by arranging a plurality of ap devices, and tracking of the terminal range is facilitated by grouping, the strength of each location of the spatial area being determined by the signal strength of the location. The determination of the position can be facilitated.

Preferably, S2 includes ranging according to signal strength; and establishing a relation function of the received signal strength and the signal transmission distance, and introducing a propagation factor and the power of the received signal. RSSI range calculation formula: rssi = txPower + pathloss + rxGain + SystemGain, which can be modeled by the antenna structure, the relationship between the transmitted power and the received power of the radio signal: PR = PT/rn, where PR is the received power of the wireless signal, PT is the transmitted power of the wireless signal, r is the distance between the transceiver units, and n is a propagation factor, the magnitude of which depends on the environment in which the wireless signal propagates. The propagation factor mainly depends on the interference of the wireless signal in the air, such as attenuation, reflection, multipath effect, and the like, if the interference is small, the smaller the value of the propagation factor n, the farther the signal propagation distance is, the closer the propagation curve of the wireless signal is to the theoretical curve, and the more accurate the RSSI-based ranging is. The distance between the terminal and the ap device can be accurately measured.

Preferably, the step S3 includes obtaining S31, and obtaining a spatial coordinate of the ap point with the strongest wifi signal at the periphery; and S32, establishing a virtual area according to the space coordinates. Each terminal can receive wireless signals sent by a plurality of ap devices on the periphery, the space coordinates of a plurality of ap points with the highest signal intensity are selected, a space model is built according to the space coordinates of the ap points, the space model is further divided, the signal intensity is calculated, and fitting is carried out according to an ideal value, so that the point position closest to the real position of the terminal is determined. The device can reduce the use of a high-precision instrument and perform accurate positioning at the same time, and improves the positioning precision through multi-point position judgment, so that the positioning is accurate, and a more detailed spatial position can be obtained.

Preferably, S31 includes scanning all the wifi point signals available around and selecting the strongest multiple signal points to obtain a table of signal strengths and corresponding aps. After scanning all available wifi points around the terminal, selecting the highest intensity, wherein the distance with the highest intensity is usually near the terminal, and establishing a table of signal intensity and corresponding ap, so as to obtain signal intensity data near the terminal.

Preferably, the step S32 includes determining a longitude and latitude variation range according to the spatial coordinates, obtaining a spatial region, and equally dividing the spatial region along the longitude and latitude to obtain a plurality of virtual position points of the array. According to the space coordinates of the ap point, the longitude latitude lattude change ranges (minX, minY) and (maxX, maxY) are taken, a space area can be obtained, the space area is extended by a set distance along the direction facing the terminal, the space area can be established under the condition that the ap devices are gathered on the same side of the terminal, a longitude and latitude coordinate system is established in the space area, the space area is equally divided according to the coordinate system, a plurality of array imaginary position points are obtained after the space area is equally divided, and the imaginary position points are located in the space area and are arranged adjacently. Therefore, possible positions of the terminal are obtained, the positioning accuracy of the terminal can be changed according to the density degree of division of the imaginary position points, and the accuracy and the freedom of the positioning of the terminal are further improved.

Preferably, S4 includes S41, obtaining a hypothetical signal intensity profile; and S42, searching a point closest to the real mobile phone position according to the fitting degree of the virtual point signal diagram and the real RSSI signal diagram. And calculating the signal intensity of each virtual position point, and comparing the calculated signal intensity with the ideal signal intensity to judge and obtain the position of the terminal. The influence of errors can be reduced, and the position can be determined through comparison of signal strength.

Preferably, S41 includes obtaining distances between each of the imaginary location points and a plurality of signal points with strongest signals, and calculating corresponding RSSI values to obtain an imaginary signal strength distribution map. And traversing the coordinate points, taking points (z 1, z2, z3, z4 \8230; 8230; and calculating the corresponding RSSI) to obtain the hypothetical signal intensity distribution graph of each coordinate point. The number of hypothetical signal intensity profiles is the same as the number of coordinate points. A signal intensity profile at each coordinate point can be obtained.

Preferably, S42 includes calculating a fitting degree from the RSSI signal at the ideal virtual position and the virtual signal strength distribution map, traversing a plurality of virtual position points, and taking a position with a minimum fitting value as a point closest to the real mobile phone position. Determining an RSSI signal diagram at a coordinate point under an ideal condition according to the ap equipment information, calculating the fitting degree according to the geometric scaling relation between the RSSI signal diagram at the coordinate point under the ideal condition and the hypothetical signal strength distribution diagram, and summing RSSI data in a double rad = hypothetical position diagram and/or RSSI data in a true signal diagram; the fitting value = (ap 1 mobile phone signal intensity-ap 1 analog signal intensity × rad) absolute value + (ap 2 mobile phone signal intensity-ap 2 analog signal intensity × rad) absolute value + (ap 3 mobile phone signal intensity-ap 3 analog signal intensity × rad) absolute value + (ap 4 mobile phone signal intensity-ap 4 analog signal intensity × rad) absolute value + (ap 5 mobile phone signal intensity-ap 5 analog signal intensity × rad); and traversing the coordinate points, and taking the position with the minimum fitting value as the point closest to the real mobile phone position. Thereby achieving high accuracy positioning.

The invention has the following advantages:

(1) Interference caused by wifi signal fluctuation is reduced, stable wifi signal values are needed for triangular positioning, but in a real scene, signal fluctuation is large, when the position is calculated by adopting wave floating, dependence on accuracy of a single wifi value can be eliminated, filtering smoothing processing is performed at the later stage of an algorithm, position jitter caused by signal fluctuation can be prevented, and the algorithm is close to a real use scene; (2) The space model of signal intensity and position can be established under the effect of many ap equipment, and signal intensity and ideal value fit in the space model according to, confirm the most reliable coordinate point, and then confirm the terminal position to change according to the coordinate point division multiple can realize the change to positioning accuracy, reduced the error that comes from signal intensity, signal fluctuation, signal source and bring less, improved the positioning accuracy.

Drawings

In order to more clearly illustrate the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.

FIG. 1 is a graph of RSSI versus distance with n unchanged and A changed.

Fig. 2 is a graph illustrating RSSI versus distance curves when a is constant and n is varied according to the present invention.

Fig. 3 is a graph of WiFi signal strength around the cell phone.

Fig. 4 is an ap layout and handset position display diagram.

Fig. 5 is a graph of signal intensity distribution for 100 x 100 phantom points.

FIG. 6 is a schematic diagram of the method steps of the present invention.

Detailed Description

Embodiments of the present invention are illustrated below by specific examples, and it should be understood that the examples described are only some examples, and not all examples, of the present invention. 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.

As shown in fig. 6, in a preferred embodiment, the present invention discloses a method for obtaining indoor location based on WiFi positioning, which includes the following steps:

s1, installing an ap and collecting data; grouping and marking data, collecting gps coordinates and corresponding mac addresses of each ap, and establishing an ap information database; the ap equipment adopts a uniform signal, so that a large error caused by mutual conversion of the RSSI value and the space distance due to inconsistent transmission power is prevented; if the ap equipment does not adopt a uniform model, a deviation value is required to be added after RSSI ranging to reduce errors; and if the heights of the aps are different, a second deviation value adjustment needs to be added after RSSI ranging to reduce the error.

When the system is used, after a plurality of aps are arranged in a multi-story building, the gps coordinate and the mac address of each ap are detected and stored respectively, and an ap information database is established.

S2, RSSI ranging; ranging according to the signal strength; establishing a relation function of the received signal strength and the signal transmission distance, and introducing a propagation factor and the power of a received signal; according to the signal strength ranging, the RSSI ranging calculation formula: rssi = txPower + pathloss + rxGain + SystemGain, rxGain can be modeled by the antenna structure. RSSI ranging principle:

the relationship between the transmission power and the reception power of the wireless signal can be expressed by equation (1), PR is the reception power of the wireless signal, PT is the transmission power of the wireless signal, r is the distance between the transceiver units, n is a propagation factor, and the magnitude of the value depends on the environment in which the wireless signal propagates.

PR＝PT/rn(1)；

Taking logarithm on two sides of the formula (1) to obtain a formula (2),

10·nlgr＝10lgPT/PR(2)；

the transmitting power of the node is known, the transmitting power is substituted into an available formula (3) in a formula (2),

10lgPR＝A-10·nlgr (3)；

the left half 10lgPR of equation (3) is an expression for converting the received signal power to dBm, and can be directly written as equation (4), where a can be regarded as the power of the received signal when the signal is transmitted 1m away in equation (4).

PR(dBm)＝A-10·nlgr (4)；

The relation between the received signal strength and the signal transmission distance is determined by the numerical values of constants A and n obtained in the formula (4), and the influence of the two constants on the signal transmission distance is analyzed. Assuming that n is constant and a is changed, the relationship graph shown in fig. 1 is shown. As shown in fig. 1, the signal propagation factor n is a constant value, and the RSSI is related to the propagation distance at different initial transmission signal powers. The short-distance signal attenuation of the wireless signal in the propagation process is quite serious, and the signal is slowly and linearly attenuated in the long distance. When the transmission signal power increases, the increased propagation distance is approximately the ratio of the increase in transmission signal power to the slope of the curve at the plateau. If A is not changed, the relationship between RSSI and signal propagation distance at different n is shown in FIG. 2. When the value of n is smaller, the attenuation of the signal in the propagation process is smaller, and the signal can propagate for a long distance, so that a good propagation factor n characteristic can be seen from fig. 2, and the signal propagation distance can be increased by increasing the power of the transmitted signal. The propagation factor mainly depends on the interference of the wireless signal in the air such as attenuation, reflection, multipath effect and the like, if the interference is small, the smaller the value of the propagation factor n, the farther the signal propagation distance is, the closer the propagation curve of the wireless signal is to the theoretical curve, and the more accurate the ranging based on the RSSI is.

S3, acquiring wifi signal intensity distribution data around the terminal; s31, obtaining the spatial coordinates of ap points with strongest peripheral wifi signals; scanning all peripheral usable wifi point signals and selecting a plurality of strongest signal points to obtain a table of signal intensity and corresponding ap; after all available wifi points around the terminal are scanned, the highest intensity is selected, the distances which are usually the highest in intensity are all near the terminal, and a table of signal intensity and corresponding ap is established, so that signal intensity data near the terminal are obtained.

When the mobile phone is used, the mobile phone scans all peripheral available WiFi point signals, the Android end can acquire the WiFi signal intensity of the mobile phone and a corresponding mac address, and the Android end api: wifimanager. Getscanresults (), wechat applet side api: wx. onggetwifilist (function feedback)), and a table of signal strengths and corresponding aps is obtained by taking the strongest 5 signal points.

S32, establishing a hypothetical area according to the space coordinate; determining longitude and latitude variation ranges according to the space coordinates, obtaining a space area, and equally dividing the space area along the longitude and the latitude to obtain a plurality of array imaginary position points; according to the space coordinates of the ap point, the longitude latitude lattude change ranges (minX, minY) and (maxX, maxY) are taken, a space area can be obtained, the space area is extended by a set distance along the direction facing the terminal, the space area can be established under the condition that the ap devices are gathered on the same side of the terminal, a longitude and latitude coordinate system is established in the space area, the space area is equally divided according to the coordinate system, a plurality of array imaginary position points are obtained after the space area is equally divided, and the imaginary position points are located in the space area and are arranged adjacently. Thereby obtaining the possible positions of the terminal, and the accuracy of the terminal positioning can be changed according to the density degree of the division of the imaginary position points.

When the mobile phone is used, as shown in fig. 3, the spatial coordinates of the 5 ap points are obtained, longitude latitude satellite variation ranges (minX, minY) and (maxX, maxY) are obtained, a rectangular spatial region is obtained, the region is expanded by 80 meters along each direction (considering the situation that ap hot points are gathered at one side of the mobile phone), a coordinate system is established to divide the mobile phone into 100 x and longitude points, and 100 imaginary mobile phone position points are obtained as shown in fig. 4.

S4, judging a point closest to the real terminal position; s41, obtaining a hypothetical signal intensity distribution graph; obtaining the distance between each hypothetical location point and a plurality of signal points with strongest signals, and respectively calculating corresponding RSSI values to obtain a hypothetical signal strength distribution graph; s42, searching a point closest to the position of the real terminal according to the fitting degree of the virtual point signal diagram and the real RSSI signal diagram; and calculating the fitting degree according to the RSSI signal of the ideal imaginary position and the intensity distribution diagram of the imaginary signal, traversing a plurality of imaginary position points, and taking the position with the minimum fitting value as the point closest to the position of the real terminal.

When the mobile phone is used, the coordinate points are traversed, points (z 1, z2, z3, z4 \8230;) are taken, the distances between the coordinate points and the 5 aps are respectively obtained, the corresponding RSSI values are respectively calculated, PR (dBm) = A-10. Nlgr, 100 × 100 imaginary signal intensity distribution graphs are obtained, as shown in FIG. 5, the virtual point signal graph and the real RSSI signal graph are compared in the graph, the fitting degree is more similar, the more the graph fluctuation is, the more accurate the real position of the mobile phone is, and the calculation mode is as follows: the RSSI signal of the ideal imaginary position and a real RSSI signal graph have an equal scaling relation, and the fitting degree is calculated.

double rad = RSSI data summation in hypothetical location map/RSSI data summation in real signal map;

the fitting value = (ap 1 mobile phone signal intensity-ap 1 analog signal intensity ×) absolute value + (ap 2 mobile phone signal intensity-ap 2 analog signal intensity ×) absolute value + (ap 3 mobile phone signal intensity-ap 3 analog signal intensity ×) absolute value + (ap 4 mobile phone signal intensity-ap 4 analog signal intensity ×) rad) absolute value + (ap 5 mobile phone signal intensity-ap 5 analog signal intensity ×) absolute value.

And traversing 100 points by 100 points, and taking the position with the minimum fitting value as the point closest to the real mobile phone position.

Although the invention has been described in detail above with reference to a general description and specific examples, it will be apparent to one skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.

Claims (9)

1. A method for obtaining indoor position based on WiFi positioning is characterized by comprising the following steps:

s1, installing an ap and collecting data;

s2, RSSI ranging;

s3, acquiring wifi signal intensity distribution data around the terminal;

and S4, judging the point closest to the real terminal position.

2. The method of claim 1, wherein S1 includes grouping and marking data, and collects gps coordinates and corresponding mac addresses of each ap to establish an ap information database.

3. The method of claim 1 or 2, wherein S2 comprises ranging according to signal strength; and establishing a relation function of the strength of the received signal and the signal transmission distance, and introducing a propagation factor and the power of the received signal.

4. The method for acquiring the indoor position based on the WiFi positioning as claimed in claim 1 or 2, wherein the step S3 comprises the steps of acquiring S31, and acquiring the spatial coordinates of ap points with strongest peripheral WiFi signals; and S32, establishing a virtual area according to the space coordinates.

5. The method of claim 4, wherein S31 comprises scanning all surrounding WiFi point signals and selecting the strongest multiple signal points to obtain a table of signal strengths and corresponding aps.

6. The method as claimed in claim 4, wherein the step S32 includes determining a latitude and longitude variation range according to the spatial coordinates, obtaining a spatial region, and dividing the spatial region equally along the latitude and longitude to obtain a plurality of virtual location points in an array.

7. The method for acquiring the indoor position based on the WiFi positioning as claimed in any one of claims 1 to 6, wherein S4 comprises S41, obtaining a hypothetical signal strength distribution graph; and S42, searching a point closest to the real terminal position according to the fitting degree of the virtual point signal diagram and the real RSSI signal diagram.

8. The method of claim 7, wherein S41 comprises obtaining the distance between each imaginary location point and the strongest signal points, and calculating the corresponding RSSI values to obtain the imaginary signal strength distribution map.

9. The method of claim 8, wherein S42 comprises calculating a fitting degree according to the RSSI signal of the ideal imaginary location and the intensity distribution diagram of the imaginary signal, traversing a plurality of imaginary location points, and determining the point with the smallest fitting value as the point closest to the real terminal location.

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