CN105682022A - Indoor and outdoor seamless positioning system based on Android device and positioning method thereof - Google Patents
Indoor and outdoor seamless positioning system based on Android device and positioning method thereof Download PDFInfo
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- H—ELECTRICITY
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- H—ELECTRICITY
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- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
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- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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Abstract
The invention discloses an indoor and outdoor seamless positioning system based on an Android device. The indoor and outdoor seamless positioning system comprises an outdoor positioning part, an indoor positioning part, a background detection part and a function configuration part; the outdoor positioning part comprises an outdoor electronic map and a GPS module; the GPS module is used for obtaining a latitude and longitude coordinate of the current position, correcting and converting the latitude and longitude coordinate into encrypted latitude and longitude data and displaying the same on the outdoor electronic map; the background detection part comprises a floor detection module and an environment detection module; the floor detection module obtains an altitude of the current position in real time; the environment detection module is used for detecting the environment of the current position in real time; the indoor positioning part is used for indoor space positioning and displaying a positioning result on an indoor electronic map; and the function configuration part is used for establishing and checking a WIFI fingerprint base. The indoor and outdoor seamless positioning system disclosed by the invention integrates GPS positioning and WIFI fingerprint positioning and combines indoor and outdoor environment detection and floor detection to realize true seamless positioning. The indoor and outdoor seamless positioning system disclosed by the invention is good in universality, low in cost and high in positioning precision.
Description
Technical Field
The invention relates to the technical field of positioning technology and position service, in particular to an indoor and outdoor seamless positioning system and method based on Android equipment and integrating GPS (global positioning system), WIFI (wireless fidelity) positioning technology and multi-sensor fusion.
Background
With the rapid development of information technology, the demand of location services is increasing, and people hope to obtain location information at any time and any place.
At present, global satellite navigation and positioning systems such as GPS, GLONASS, Beidou navigation and the like are becoming mature, and are successfully applied to various fields such as military, industry, commerce and the like. However, due to the limitation of the satellite positioning technology, the global satellite navigation positioning system cannot be directly transplanted to an indoor scene, and is blocked by walls, buildings and the like, and signals of the GPS and the like are so sharply attenuated that positioning cannot be performed indoors, so people begin to search for positioning technologies in the indoor scene, and the positioning technologies of bluetooth, WIFI, ultrasonic, infrared, RFID, Zigbee and the like are exposed at the head and are undergoing a vigorous development period. At this time, the research on indoor and outdoor seamless positioning follows, how to make the user not limited by the environment is a topic of great concern for acquiring the positioning service anytime and anywhere. Meanwhile, due to the popularity and popularity of intelligent mobile equipment, the universality and convenience of application software and various sensors equipped in the intelligent mobile equipment enable indoor and outdoor seamless positioning on Android equipment to have the unique advantage.
Therefore, it is a good solution to develop an indoor and outdoor seamless positioning system and software based on Android devices.
Disclosure of Invention
The invention aims to provide an indoor and outdoor seamless positioning system and a positioning method based on Android equipment.
The positioning range of the invention covers various specific floors of outdoor environment, internal environment of various large buildings and indoor environment, thus truly realizing omnibearing seamless positioning and having the advantages of high universality, low cost, good positioning effect and the like.
The invention provides an indoor and outdoor seamless positioning system based on Android equipment, which comprises the following components: the system comprises an outdoor positioning part, an indoor positioning part, a background detection part and a function configuration part; the outdoor positioning portion includes: an outdoor electronic map and GPS module; the GPS module is used for acquiring longitude and latitude coordinates of the current position, correcting and converting the longitude and latitude coordinates into encrypted longitude and latitude data and displaying the encrypted longitude and latitude data on the outdoor electronic map; the background detection section includes: the system comprises a floor detection module and an environment detection module; the floor detection module acquires the altitude of the current position in real time; the environment detection module is used for detecting the environment of the current position in real time; the indoor positioning part is used for positioning indoor space and displaying a positioning result on an indoor electronic map; the function configuration part is used for establishing and viewing a WIFI fingerprint database.
In the indoor and outdoor seamless positioning system based on the Android equipment, the floor detection module obtains the reference air pressure through Web service, obtains the air pressure of the current position by using the air pressure sensor, calculates the altitude and detects the floor of the current position.
In the indoor and outdoor seamless positioning system based on the Android device, the environment detection module comprises: the system comprises an Android device GPS module, an optical sensor, a proximity sensor, a magnetic field sensor and an Android system internal clock; the Android device GPS module forms a GPS detection submodule and is used for judging the current environment; the proximity sensor, the optical sensor and the internal clock of the Android system form a light intensity detection submodule for judging the current environment; the magnetic field sensor forms a magnetic field detection submodule for judging the current environment. The Android device GPS module is used for calculating indoor confidence and outdoor confidence determined by a GPS; the proximity sensor, the light sensor and the Android system internal clock are used for calculating indoor confidence and outdoor confidence determined by light intensity; the magnetic field sensor is used to calculate an indoor confidence and an outdoor confidence determined by the magnetic field strength.
The invention also provides an indoor and outdoor seamless positioning method based on the Android equipment, and the indoor and outdoor seamless positioning system provided by the invention comprises the following steps:
the method comprises the following steps: the environment detection module detects the environment of the current position in real time;
step two: if the current environment is outdoor, acquiring longitude and latitude coordinates of the current position by using a GPS module, and displaying the position corresponding to the longitude and latitude coordinates on an outdoor electronic map in real time after correction;
step three: if the current environment is indoor, the floor where the current position is located is detected by using a floor detection module;
step four: and scanning the WIFI signal through the indoor positioning part, matching the WIFI signal with the position fingerprint in the function configuration part, calculating the current position coordinate by using a fingerprint positioning algorithm, and displaying the corresponding position on the indoor electronic map.
In the indoor and outdoor seamless positioning method based on the Android device, the first step comprises the following steps:
step 1 a: acquiring the output precision of an Android device GPS module, and calculating the indoor confidence and the outdoor confidence determined by the GPS;
step 1 b: judging whether the current equipment is shielded or not by the Android proximity sensor, if not, acquiring the light intensity of the optical sensor, acquiring the system time of an internal clock of the Android system, and calculating the indoor confidence and the outdoor confidence determined by the light intensity;
step 1 c: acquiring the magnetic field intensity output by the magnetic field sensor, and calculating the indoor confidence and the outdoor confidence determined by the magnetic field intensity;
step 1 d: and integrating the judgment results of the three sub-parts by using an HMM (hidden Markov model), and calculating the current environment by using a Viterbi algorithm.
In the indoor and outdoor seamless positioning method based on the Android device, the third step comprises the following steps:
step 3 a: acquiring an air pressure value of a current position by using an air pressure sensor;
and step 3 b: acquiring a reference air pressure value of the current position through the longitude and latitude coordinates of the current position and Web service;
and step 3 c: and calculating the altitude of the current position according to the air pressure value and the reference air pressure value, thereby obtaining the floor where the current position is located.
In the indoor and outdoor seamless positioning method based on the Android device, the fourth step comprises the following steps:
step 4 a: scanning WIFI signals and matching the WIFI signals with WIFI signals of selected APs in a WIFI fingerprint database;
and 4 b: if the signal strength is larger than-85 dbm, repeating scanning for multiple times, and calculating the average value of the signal strength of each AP;
and 4 c: and calculating the current position coordinate by using a WKNN algorithm, and displaying the current position coordinate on an indoor electronic map.
In the indoor and outdoor seamless positioning method based on the Android equipment, the establishment of the position fingerprint in the WIFI fingerprint library comprises the following steps:
step 5 a: selecting a plurality of APs for positioning;
and step 5 b: marking the current position on an indoor electronic map;
and step 5 c: scanning WIFI signals, if the WIFI signals are matched with the selected AP in the WIFI fingerprint database 41 and the signal intensity is larger than-85 dbm, repeating the scanning for multiple times, and calculating the average value of the signal intensity of each AP;
and step 5 d: the average of the signal strengths of the APs along with the current location coordinates are combined into the location fingerprint.
In the invention, the outdoor positioning part utilizes GPS technology to combine with an electronic map to carry out outdoor positioning; the indoor positioning part performs indoor positioning by combining an improved WIFI fingerprint positioning technology with an indoor electronic map; the background detection part consists of two parts: environment detection module and floor detection module. The environment detection module is composed of three sub-modules: a GPS detection submodule, a light intensity detection submodule and a magnetic field detection submodule; the GPS detection submodule consists of a GPS module and calculates the outdoor confidence coefficient and the indoor confidence coefficient according to the acquired real-time GPS output precision; the light intensity detection submodule consists of a proximity sensor, an optical sensor and an internal clock of an Android system, and calculates outdoor confidence and indoor confidence according to the acquired real-time system time and light intensity; the magnetic field detection submodule is composed of a magnetic field sensor, and calculates outdoor confidence and indoor confidence according to the acquired real-time magnetic field intensity. And integrating the calculation results of the three sub-modules by using an HMM (hidden Markov model), and calculating the current environment by using a Viterbi algorithm. The floor detection module obtains a real-time air pressure value through an air pressure sensor of the Android device, obtains a current average sea level air pressure value through Web service, judges the current altitude of the floor according to the current average sea level air pressure value and the current average sea level air pressure value, and further obtains the current floor, and the function configuration part is used for collecting and checking an indoor WIFI fingerprint library and positioning the indoor positioning part.
In the invention, the outdoor positioning part utilizes the SDK provided by the electronic map official to carry out secondary development to display the map, utilizes the GPS module to obtain the longitude and latitude coordinates of the current position, and then the longitude and latitude coordinates are corrected and converted into encrypted longitude and latitude coordinates (bd0911) to display the position on the electronic map in real time.
According to the method, the indoor positioning part carries out indoor positioning by utilizing a WIFI fingerprint positioning technology, Android equipment scans WIFI signals, the WIFI signals are matched with WIFI signals of selected APs in a WIFI fingerprint library established by the function configuration part, the acquired signals are subjected to relevant preprocessing and judgment, the preset conditions are met, the WIFI signals are acquired five times at each positioning time, the signal intensity average value of each selected AP is calculated, then the current position coordinate is calculated by utilizing a WKNN algorithm and displayed in a self-made indoor electronic map, and the process is circulated periodically to achieve continuous indoor positioning.
In the invention, the environment detection module is composed of three sub-modules: the GPS detection submodule consists of a GPS module and calculates outdoor confidence and indoor confidence according to the acquired real-time GPS output precision; the light intensity detection submodule consists of a proximity sensor, an optical sensor and an Android system internal clock, the proximity sensor judges whether the current equipment is shielded, if not, the system internal clock judges whether the current environment is in the daytime or at night, the system internal clock continuously receives the illumination intensity output by the optical sensor at the background, and the outdoor confidence coefficient and the indoor confidence coefficient determined by the light intensity are calculated; the magnetic field detection submodule is composed of a magnetic field sensor, obtains the magnetic field intensity in real time, and calculates the outdoor confidence coefficient and the indoor confidence coefficient according to the variance in a period of time. And integrating the calculation results of the three sub-modules by using an HMM (hidden Markov model), and calculating the current environment by using a Viterbi algorithm.
In the invention, the floor detection module utilizes the self-contained air pressure sensor of the Android device to judge, continuously receives the current air pressure value output by the air pressure sensor, and calculates the real-time altitude by comparing the local real-time average sea level air pressure value obtained by Web service, thereby judging the floor at present according to a series of set thresholds.
The method can also be used for Android smart phones, can be used for indoor and outdoor seamless positioning, and can realize the following functions: and the function configuration part is used for acquiring WIFI fingerprints of all indoor floors to establish a WIFI fingerprint database which is used for positioning the indoor positioning part. In the outdoor environment, the GPS technology is combined with the electronic map to carry out accurate real-time positioning, a user enters the indoor environment, the background detects that the user enters the indoor environment, the user is inquired whether to switch to the indoor map and position, the user can switch to the indoor electronic map by clicking and determining, meanwhile, the improved WIFI fingerprint positioning technology is used for starting positioning, the indoor positioning is executed circularly and periodically, continuous positioning is realized, when the user enters other floors through stairs or an elevator, the background detects that the user enters corresponding floors, the user is inquired whether to switch to the corresponding floors and position, the user can switch to the electronic map of the corresponding floor by clicking and determining, and simultaneously starts positioning, at the moment, if the user walks out of the building and enters the outdoor environment, the background detects that the user enters the outdoor environment, inquires whether to switch to the outdoor map and position, and the user can switch to the outdoor map by clicking and determining, the whole process is completed as software, and real seamless indoor and outdoor positioning is realized.
The invention can be used for indoor and outdoor seamless positioning in any place, and only needs to be provided with an indoor electronic map of a building to be positioned in the place. The user can complete the entire positioning process using the above description. The method has no objective condition limitation, has very good universality and good positioning effect, and can be popularized and used.
Drawings
Fig. 1 is a schematic structural diagram of an indoor and outdoor seamless positioning system based on Android devices.
Fig. 2 is a flowchart illustrating the operation of the indoor positioning unit according to the present invention.
Fig. 3 is a flowchart illustrating the operation of the function configuration part in establishing the WIFI fingerprint database according to the present invention.
Detailed Description
The invention is further described in detail with reference to the following specific examples and the accompanying drawings. The procedures, conditions, experimental methods and the like for carrying out the present invention are general knowledge and common general knowledge in the art except for the contents specifically mentioned below, and the present invention is not particularly limited.
As shown in fig. 1, the present invention provides an indoor and outdoor seamless positioning system based on Android devices, including: outdoor positioning portion 1, indoor positioning portion 3, background detection portion 2, and function configuration portion 4. Wherein, outdoor location portion 1 includes: an outdoor electronic map 11 and a GPS module 12. The GPS module 12 is used to acquire longitude and latitude coordinates of the current location, and convert the coordinates into encrypted longitude and latitude data after correction and display the encrypted longitude and latitude data on the outdoor electronic map 11. The background detection unit 2 includes: a floor detection module 21 and an environment detection module 22. The floor detection module 21 acquires the altitude of the current position in real time. The environment detection module 22 is used for detecting the environment of the current location in real time. The indoor positioning section 3 is used for indoor space positioning, and displays the positioning result on an indoor electronic map. The function configuration part 4 is used for establishing and viewing the WIFI fingerprint library 41.
In the indoor and outdoor seamless positioning system based on the Android device, the floor detection module 21 obtains the reference air pressure through Web service, obtains the air pressure of the current position by using the air pressure sensor 212, calculates the altitude and detects the floor of the current position.
In the indoor and outdoor seamless positioning system based on the Android device, the environment detection module 22 comprises: an Android device GPS module 221, a light sensor 222, an Android system internal clock 223, a magnetic field sensor 224, and a proximity sensor 225. The environment detection module is composed of three sub-modules: a GPS detection sub-module (GPS detector), a light intensity detection sub-module (LightDetector), and a magnetic field detection sub-module (magnetsmdetector). The GPSDetector is composed of a GPS module 221, and calculates an outdoor confidence coefficient and an indoor confidence coefficient according to the acquired GPS output precision; the LightDetector consists of a proximity sensor 225, a light sensor 222 and an Android system internal clock 223, and calculates an outdoor confidence coefficient and an indoor confidence coefficient according to the acquired real-time system time and light intensity; the magnetism detector is composed of a magnetic field sensor 224, and calculates an outdoor confidence level and an indoor confidence level according to the acquired real-time magnetic field intensity. And integrating the calculation results of the three sub-modules by using an HMM (hidden Markov model), and calculating the current environment by using a Viterbi algorithm.
Based on the indoor and outdoor seamless positioning system provided by the invention, the invention provides an indoor and outdoor seamless positioning method based on Android equipment, which comprises the following steps:
the method comprises the following steps: the environment detection module 22 detects the environment of the current position in real time;
step two: if the current environment is outdoor, acquiring longitude and latitude coordinates of the current position by using an outdoor GPS module 12, and displaying the position corresponding to the longitude and latitude coordinates on the outdoor electronic map 11 in real time after correction;
step three: if the current environment is indoor, the floor where the current position is located is detected by using the floor detection module 21;
step four: the WIFI signal is scanned by the indoor positioning part 3 and matched with the position fingerprint in the function configuration part 4, the current position coordinate is calculated by using a fingerprint positioning algorithm, and the corresponding position is displayed on the indoor electronic map.
The indoor and outdoor seamless positioning method based on the Android equipment, provided by the invention, comprises the following steps:
step 1 a: acquiring the output precision of the Android device GPS module 221, and calculating the indoor confidence and the outdoor confidence determined by the GPS;
step 1 b: judging whether the current equipment is shielded or not by the Android proximity sensor 225, if not, acquiring the light intensity of the optical sensor 222, acquiring the system time of an internal clock 223 of the Android system, and calculating the indoor confidence and the outdoor confidence determined by the light intensity;
step 1 c: acquiring the magnetic field intensity output by the magnetic field sensor 224, and calculating the indoor confidence and the outdoor confidence determined by the magnetic field intensity;
step 1 d: and integrating the judgment results of the three sub-parts by using an HMM (hidden Markov model), and calculating the current environment by using a Viterbi algorithm.
In the indoor and outdoor seamless positioning method based on the Android equipment, the third step comprises the following steps:
step 3 a: acquiring an air pressure value of the current position by using the air pressure sensor 212;
and step 3 b: acquiring a reference air pressure value of the current position through the longitude and latitude coordinates of the current position and Web service;
and step 3 c: and calculating the altitude of the current position through the air pressure value and the reference air pressure value so as to obtain the floor of the current position.
In the indoor and outdoor seamless positioning method based on the Android equipment, the fourth step comprises the following steps:
step 4 a: scanning the WIFI signal, and matching the WIFI signal with the WIFI signal of the selected AP in the WIFI fingerprint database 41;
and 4 b: if the signal strength is larger than-85 dbm, repeating scanning for multiple times, and calculating the average value of the signal strength of each AP;
and 4 c: and calculating the current position coordinate by using a WKNN algorithm, and displaying the current position coordinate on an indoor electronic map.
In the indoor and outdoor seamless positioning method based on the Android device, the establishment of the position fingerprint in the WIFI fingerprint database 41 comprises the following steps:
step 5 a: selecting a plurality of APs for positioning;
and step 5 b: marking the current position on an indoor electronic map;
and step 5 c: scanning WIFI signals, if the WIFI signals are matched with the selected AP in the WIFI fingerprint database 41 and the signal intensity is larger than-85 dbm, repeating the scanning for multiple times, and calculating the average value of the signal intensity of each AP;
and step 5 d: the average of the signal strengths of the APs along with the current location coordinates are combined into a location fingerprint.
Examples
The invention provides an indoor and outdoor seamless positioning system integrating GPS and WIFI positioning technologies, and referring to fig. 1, the system comprises: outdoor positioning part 1, indoor fingerprint positioning part 3, background detection part 2, and function configuration 4. In this embodiment, the positioning system is mounted on an Android mobile device, and completes a seamless positioning function in the form of Android application software.
In this embodiment, the function configuration 4 is used to establish the WIFI fingerprint libraries 41 of each floor in the indoor environment, and the specific process is as follows: AP selected for positioning, denoted AP1，AP2，AP3，…，APnThe corresponding mac addresses are mac addresses respectively1,mac2,mac3,…,macn. Initializing a program to display an indoor electronic map, clicking a screen at a corresponding position on the map by a user according to the actual position, drawing a point at the position by the program, simultaneously starting a new thread, scanning a WIFI signal, considering the signal as an effective signal if the signal strength is greater than-85 dbm (or equal to) and matched with the selected AP, recording the effective signal in a two-dimensional array, sleeping the thread for 2 seconds, repeating the operation for 5 times, calculating the average signal strength value of each AP by the two-dimensional array, and recording the average signal strength value as RSSI1，RSSI2，RSSI3，…，RSSInThe screen pixel point x, y together with the position form a position fingerprint (x, y, mac)1,RSSI1，mac2,RSSI2，mac3,RSSI3，…,macn，RSSIn) And inserting the data into an SQLite database of the Android system. This operation is repeated at a certain sampling density to build the WIFI fingerprint library 41 for completing the floor. The fingerprint library is available for viewing by a user.
The user opens the application software, detects the current GPS on-off state and the current WIFI connection state of the device, and if the current GPS on-off state and the current WIFI connection state are not opened, a dialog box pops up to prompt the user whether to open the WIFI and the GPS. The software defaults to display an Outdoor interface, calls the Outdoor electronic map 11 and carries out Outdoor positioning by using the GPS module 12, and meanwhile, starts the background detection part 2 to detect the current environment and floor in the background. If the current user is judged to be in the indoor environment, popping up a dialog box to prompt that the user enters the indoor environment currently, switching to an indoor electronic map and positioning by utilizing an improved WIFI fingerprint positioning algorithm if the user clicks to determine, wherein the scanned WIFI signal needs to be judged during positioning, and if the scanned WIFI signal is larger than-85 dbm, the scanned WIFI signal is regarded as an effective signal; and sampling at each point for multiple times, and calculating the average value of the signal intensity corresponding to each AP, so that the positioning accuracy can be improved.
Specifically, an indoor first-floor electronic map is initialized, a WIFI system service is acquired, a WIFI signal is scanned, and the scanned signal and a selected AP for positioning are judged1，AP2，AP3，…，APnIf the AP signals are matched and the signal strength is greater than-85 dbm, recording the AP signals in a two-dimensional array when the conditions are met, sleeping the threads for 2 seconds, repeating the same process for 5 times, calculating the average value of the signal strength of each AP by the two-dimensional array, and recording the average value as RSSI1，RSSI2，RSSI3，…，RSSIn. Reading the fingerprint entries in the WIFI fingerprint database, judging whether the fingerprint entries are larger than a K value set in the WKNN algorithm or not, and respectively calculating the RSSI if the conditions are met1，RSSI2，RSSI3，…，RSSInThe Euclidean distances from the RSSI of the selected AP in the fingerprint library are sorted, K minimum values are selected, and then a weighting coefficient value of each of the K values is calculated. After the calculation is finished, taking out the position coordinate values of the K selected APs currently used for positioning, calculating the coordinate of the current position, and displaying the coordinate on an indoor electronic map; and if the condition is not met, prompting the user to perfect the WIFI fingerprint database. The whole positioning process is circularly executed according to a set period so as to meet the requirement of continuous positioning.
If the user is judged to leave the room, a prompt pops up, and if the user clicks to confirm, the outdoor electronic map 11 is switched to and the GPS module 12 is used for positioning. And if the current position is judged to be on the second floor, popping up a prompt, and if the user clicks to confirm, switching to the second floor electronic map and positioning. Similarly, if the user is judged to be currently located at the third floor, a prompt pops up, and if the user clicks to determine, the electronic map is switched to the third floor for positioning. And if the user is judged to be at the first floor, popping up a prompt, and if the user clicks to confirm, switching to the first floor electronic map and positioning.
In this embodiment, the indoor and outdoor environment detection unit 22 is composed of three sub-modules: GPSDetector, LightDetector, MagnetismDetector. The working principle of the GPSDetector is as follows: acquiring the output precision of the GPS module 221, judging whether the output precision is greater than the value A, if so, the indoor confidence is 1, and the outdoor confidence is 0, otherwise, judging whether the output precision is less than the value B, if so, the indoor confidence is 0, and the outdoor confidence is 1, otherwise, respectively calculating the outdoor confidence and the indoor confidence according to an empirical formula. The LightDetector works as follows: whether the equipment is shielded or not is judged by the proximity sensor 225, if not, the output intensity of the optical sensor 222 is obtained, whether the light intensity is greater than a set threshold value or not is judged, if the conditions are met, the current situation of the equipment is in the direct sunlight situation, the indoor confidence coefficient is 0, the outdoor confidence coefficient is 1, if the conditions are not met, the current time is judged by the system time to be between 7 hours and 17 hours, namely the daytime time, if the light intensity is greater than the C value, the outdoor confidence coefficient is 1, the indoor confidence coefficient is 0, if the light intensity is less than the D value, the outdoor confidence coefficient is 0, the indoor confidence coefficient is 1, and if the light intensity is not less than the D value, the outdoor confidence coefficient. And if the system time is not between 7 hours and 17 hours, judging whether the light intensity is greater than the E value, if so, judging that the indoor confidence coefficient is 1 and the outdoor confidence coefficient is 0, otherwise, judging that the indoor confidence coefficient is 0.33 and the outdoor confidence coefficient is 0.67. The magnisism detector works as follows: and acquiring the magnetic field intensity output by the magnetic field sensor 224, calculating the variance within a period of time, wherein if the variance is greater than a threshold close to 0 and less than a set threshold, the outdoor confidence is 1, the indoor confidence is 0, and otherwise, the indoor confidence is 1, and the outdoor confidence is 0. Integrating the above results by using HMM (hidden Markov model), recording the hidden state as H (t) including indoor and outdoor, and recording the observed state as RL(t)(light),RG(t)(gps),RM(t) (magnetism), R is the confidence level judged by each submoduleThe highest environment type. Note that I is an indoor environment, O is an outdoor environment, transition probabilities are T (I, I) ═ T (I, O) ═ 1/2, and T (O, I) ═ T (O, O) ═ 1/2, and each transmission probability is obtained from training data, and the current environment is estimated by a viterbi algorithm by combining the above calculated data. And then the environment information is carried by the broadcast and sent to the foreground.
In this embodiment, the floor detection portion 21 determines the altitude using the barometric pressure value, because the barometric pressure sensor 212 can output a barometric pressure reading immediately, and the generated reading is relatively accurate, and the barometric pressure sensor 212 is an ideal choice for the situation that the altitude needs to be calculated. The calculation of altitude requires a reference barometric pressure value that defaults to 1013.25kpa, but if only this default parametric value is used, the calculation result is very inaccurate. It is well known that the atmospheric pressure value is affected by various factors such as weather, temperature, humidity, etc., and the change is severe. In this embodiment, a Web service provided by GeoNames is obtained to obtain a reference air pressure, and weather data corresponding to the current longitude and latitude is obtained from the global geographic database of GeoNames, where the weather data includes an average sea level air pressure of the current location, that is, the reference air pressure. And calculating the altitude by using the reference air pressure and the acquired air pressure sensor data so as to judge the floor where the floor is located currently. In the embodiment, Android backstage continuously calculates, and if the current height is detected to be-0.5 m-1.5 m, the current first floor is judged to be entered; when the current height is detected to be 3.5-4.5 m, judging that the second floor is entered currently; and (4) detecting that the current height is 7.5-8.5 m, judging that the current building enters the third floor, and so on. In the current technical field, judge not to have more unified and ripe scheme always about the floor, take wifi signal to confirm the floor, but wifi is influenced seriously by subjective factor, in case withdraw the router that is used for judging promptly, then can't carry out the floor and judge, wifi signal attenuation is serious simultaneously to receive the influence of factors such as barrier, spatial position to make the signal extremely unstable, can't realize this function well. The method for judging the floor height by combining the web service with the air pressure sensor is relatively accurate and is not influenced by subjective factors.
The protection of the present invention is not limited to the above embodiments. Variations and advantages that may occur to those skilled in the art may be incorporated into the invention without departing from the spirit and scope of the inventive concept, and the scope of the appended claims is intended to be protected.
Claims (8)
1. The utility model provides an indoor outer seamless positioning system based on Android equipment which characterized in that includes: the device comprises an outdoor positioning part (1), an indoor positioning part (3), a background detection part (2) and a function configuration part (4);
the outdoor positioning section (1) includes: an outdoor electronic map (11) and a GPS module (12); the GPS module (12) is used for acquiring longitude and latitude coordinates of the current position, correcting and converting the longitude and latitude coordinates into encrypted longitude and latitude data and displaying the encrypted longitude and latitude data on the outdoor electronic map (11);
the background detection unit (2) includes: a floor detection module (21) and an environment detection module (22); the floor detection module (21) acquires the altitude of the current position in real time; the environment detection module (22) is used for detecting the environment of the current position in real time;
the indoor positioning part (3) is used for positioning indoor space and displaying a positioning result on an indoor electronic map;
the function configuration part (4) is used for establishing and viewing a WIFI fingerprint database (41).
2. The Android device-based indoor and outdoor seamless positioning system of claim 1, wherein the floor detection module (21) obtains a reference air pressure through a Web service, obtains an air pressure of a current position by using an air pressure sensor (212), calculates an altitude, and detects a floor where the current position is located.
3. The Android device-based indoor and outdoor seamless positioning system of claim 1, wherein the environment detection module (22) comprises: the system comprises an Android device GPS module (221), a light sensor (222) and an Android system internal clock (223), a magnetic field sensor (224) and a proximity sensor (225); wherein,
the Android device GPS module (221) forms a GPS detection submodule and is used for judging the current environment;
the proximity sensor (225), the optical sensor (222) and the Android system internal clock (223) form a light intensity detection submodule for judging the current environment;
the magnetic field sensor (224) forms a magnetic field detection submodule for determining the current environment.
4. An indoor and outdoor seamless positioning method based on Android equipment, which is characterized by utilizing the indoor and outdoor seamless positioning system of claim 1, and comprises the following steps:
the method comprises the following steps: an environment detection module (22) detects the environment of the current position in real time;
step two: if the current environment is outdoor, acquiring longitude and latitude coordinates of the current position by using a GPS module (12), and displaying the position corresponding to the longitude and latitude coordinates on an outdoor electronic map (11) in real time after correction;
step three: if the current environment is indoor, the floor where the current position is located is detected by a floor detection module (21);
step four: WIFI signals are scanned through the indoor positioning part (3), the WIFI signals are matched with position fingerprints in the function configuration part (4), the current position coordinates are calculated through a fingerprint positioning algorithm, and corresponding positions are displayed on an indoor electronic map.
5. The Android device-based indoor and outdoor seamless positioning method of claim 4, wherein the first step comprises the following steps:
step 1 a: acquiring the output precision of an Android device GPS module (221), and calculating the indoor confidence and the outdoor confidence determined by the GPS;
step 1 b: judging whether the current equipment is shielded or not by an Android proximity sensor (225), if not, acquiring the light intensity of an optical sensor (222), acquiring the system time of an Android system internal clock (223), and calculating the indoor confidence and the outdoor confidence determined by the light intensity;
step 1 c: acquiring the magnetic field strength output by a magnetic field sensor (224), and calculating indoor confidence and outdoor confidence determined by the magnetic field strength;
step 1 d: and integrating the judgment results by using a hidden Markov model, and calculating the current environment by using a Viterbi algorithm.
6. The Android device-based indoor and outdoor seamless positioning method of claim 4, wherein the third step comprises the following steps:
step 3 a: acquiring an air pressure value of a current position by using an air pressure sensor (212);
and step 3 b: acquiring a reference air pressure value of the current position through the longitude and latitude coordinates of the current position and Web service;
and step 3 c: and calculating the altitude of the current position according to the air pressure value and the reference air pressure value, thereby obtaining the floor where the current position is located.
7. The Android device-based indoor and outdoor seamless positioning method of claim 4, wherein the fourth step comprises the following steps:
step 4 a: scanning WIFI signals and matching the WIFI signals with WIFI signals of selected APs in a WIFI fingerprint database (41);
and 4 b: if the signal strength is larger than-85 dbm, repeating scanning for multiple times, and calculating the average value of the signal strength of each AP;
and 4 c: and calculating the current position coordinate by using a WKNN algorithm, and displaying the current position coordinate on an indoor electronic map.
8. The Android device-based indoor and outdoor seamless positioning method of claim 4, wherein the establishment of the location fingerprint in the WIFI fingerprint library (41) comprises the following steps:
step 5 a: selecting a plurality of APs for positioning;
and step 5 b: marking the current position on an indoor electronic map;
and step 5 c: scanning WIFI signals, if the WIFI signals are matched with the selected APs in the WIFI fingerprint database (41) and the signal intensity is larger than-85 dbm, repeating the scanning for multiple times, and calculating the average value of the signal intensity of each AP;
and step 5 d: the average of the signal strengths of the APs along with the current location coordinates are combined into the location fingerprint.
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