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Knowledge Window: Indoor Positioning Technology and Its Application
At present, domestic and foreign research has proposed RFID technology, Bluetooth, WLAN, ultra-wideband and other indoor positioning technologies and systems, some of which have been commercially available. However, due to the complexity and diversity of indoor scenes, different indoor positioning technologies have different shortcomings and limitations, and no universal solution similar to GNSS has yet been formed. This paper briefly introduces the main principles of indoor positioning technology, describes the classification of indoor positioning technology, and finally introduces the application scenarios and development prospects of indoor positioning technology.
First, indoor positioning technology
Indoor positioning refers to positioning in the indoor environment. The wireless communication, base station positioning, inertial positioning, and other technologies are integrated to form a set of indoor location positioning system, so as to realize position monitoring of people, objects, and the like in the indoor space.
With the continuous development and popularization of communication technology and electronic manufacturing technology, indoor positioning technology emerges in an endless stream, positioning accuracy is from several meters to several tens of meters, and has been applied in some industries.
Indoor positioning method
At present, the commonly used positioning methods for indoor positioning are mainly divided into seven types: proximity detection method, centroid positioning method, multilateral positioning method, triangle positioning method, pole method, fingerprint positioning method, and dead reckoning algorithm.
(1) Proximity Detection (Proximity Detection): The proximity detection method, also known as the CoO (Cell of Origin) method or the Cell-ID (Cell Identification) method, determines the presence or absence of a mobile device through the reception of a limited number of physical signals. Near a launch point. The positioning accuracy of this method depends on the placement density and signal coverage of the emission point. Although this method can only provide approximate location information, it has low deployment cost and is easy to build. It is suitable for some applications that do not require high positioning accuracy. For example, an automatic identification system is used by company employees to check in.
(2) Centroid Determination: The centroid positioning method calculates the centroid coordinates of the mobile device as the coordinates of the mobile device according to all the known beacon positions within the range of signals receivable by the mobile device. Correspondingly, the weight of the corresponding beacon may also be set according to a Received Signal Strength Indication ( RSSI) to obtain the weighted centroid as the coordinates of the mobile device. The algorithm of this method is easy to understand, the amount of calculation is small, and the positioning accuracy depends on the layout density of beacons.
(3) Multilateration: This method determines the position of the target to be measured by measuring the distance between the target to be measured and the known reference point. Multi-position based positioning systems can use multiple distance estimation methods. The more common distance estimation methods are based on Time of Arrival (TOA) and Time Difference Of Arrival (TDOA) based on the enhanced observation time difference. (Enhanced Observed Time Difference, E-OTD), based on round trip time (RTT), based on received signal strength indication.
(4) Triangulation: The method of triangulation, also known as Arrival Of Angle (AOA). The method can determine the unique triangle by combining the distance information between two reference points after obtaining the angle of the target to be measured with respect to two known reference points, and can determine the position of the target to be measured. The angle of arrival information, ie the angle at which the signal arrives, can be obtained via a directional antenna. At the same time, a camera-based positioning system can also achieve AOA-based positioning.
(5) Polar Point Method: The pole method determines the position of the point to be measured by measuring the distance and angle to a known reference point. This method only needs to know the position coordinates of a reference point, so it is very convenient to use and has been widely used in geodetic survey. The positions of multiple targets to be measured can be obtained only from the simple establishment of a total station.
(6) Fingerprinting (fingerprint positioning method): The standard amount of fingerprint positioning acquisition is a radio frequency signal, but the fingerprint positioning method may also be implemented using a sound signal, an optical signal, or other wireless signals. Fingerprint positioning usually includes two phases: the first phase, off-line calibration phase, establishing a fingerprint map through actual acquisition or calculation analysis. Specifically, a plurality of location points in an indoor scene are selected to collect the intensities of signals sent by multiple base stations and added to the fingerprint database. The second stage, the positioning stage, compares the signal feature parameters of the real-time received signal in the fingerprint database to find the best matching parameter, and the corresponding position coordinate is considered as the position coordinate of the target to be measured. The advantage of fingerprint positioning is that it requires little reference to measurement points, and the positioning accuracy is relatively high. However, the disadvantage is that the workload of building a fingerprint database off-line in the early stage is huge, and it is difficult to adapt to scenes with large changes in the environment.
(7) Dead Reckoning: The standard amount of fingerprint positioning and acquisition is a radio frequency signal, but the fingerprint positioning method can also be implemented using sound signals, optical signals, or other wireless signals. Fingerprint positioning usually includes two phases: the first phase, off-line calibration phase, establishing a fingerprint map through actual acquisition or calculation analysis. Specifically, a plurality of location points in an indoor scene are selected to collect the intensities of signals sent by multiple base stations and added to the fingerprint database. The second stage, the positioning stage, compares the signal feature parameters of the real-time received signal in the fingerprint database to find the best matching parameter, and the corresponding position coordinate is considered as the position coordinate of the target to be measured. The advantage of fingerprint positioning is that it requires little reference to measurement points, and the positioning accuracy is relatively high. However, the disadvantage is that the workload of building a fingerprint database off-line in the early stage is huge, and it is difficult to adapt to scenes with large changes in the environment.
2. Indoor positioning observation
Different indoor positioning methods select different observations, and the information required by the algorithm is extracted through different observations. The following is a brief introduction to the main observations.
(1) RSSI measurement: RSSI measurement is through the calculation of the signal propagation loss, you can use the theoretical or empirical model to convert the propagation loss into distance, fingerprint positioning can also be used to establish fingerprint database.
In free space, the received signal strength from the antenna at transmitter d can be given by:
PF/PT=(GT×GR×λ2)/((4π)2×d2×L)
Where PF denotes the transmit power; PT denotes the receive power at distance d; GT denotes the gain of the transmit antenna; GR denotes the gain of the receive antenna; λ denotes the signal wavelength; L denotes the loss of the system (L>1).
(2) TOA measurement: The TOA method mainly measures one-way propagation time or back-and-forth propagation time of a signal between a base station and a mobile station. The former requires clock synchronization between the base station and the mobile station.
The positioning method for TOA measurement is multilateration. If the propagation time of the electromagnetic wave from the mobile station to the base station is t and the propagation speed of the electromagnetic wave is c, the mobile station is located on a circle centered on the base station and having a radius of c*t. Similarly, on the circles of the second and third base stations, the position coordinates of the mobile station should be the intersection of these three circles. As shown in the figure below, A, B, and C are three base stations with known locations, P is a mobile station, and R1, R2, and R3 are the distances from the mobile station to the base stations A, B, and C, respectively.
TOA-based positioning principle
(3) TDOA measurement: This method is also used to measure the signal arrival time. However, using the time difference of arrival to perform positioning calculation can determine the position of the mobile station using the hyperbola intersection. Therefore, accurate synchronization of the base station and the mobile station can be avoided.
Through the TDOA measurement, the difference between the distance from the unknown mobile station to the two base stations can be obtained, that is, the mobile station is located on the hyperbola with two base stations as the focus. With the introduction of the third base station, more than two hyperbolic equations can be obtained, and the intersection of the hyperbola is the position of the mobile station. As shown in the figure below, A, B, and C are three known base stations. P is the mobile station. R1, R2, and R3 are the distances from the mobile station to the base stations A, B, and C, respectively. R2-R1, R3- R1 is a constant value.
TDOA-based positioning principle
(4) AOA measurement: The AOA method refers to a receiver that measures the incident angle of an electromagnetic wave through an antenna array, including measuring an angle of a base station signal to a mobile station or an angle of a mobile station signal arriving at a base station. Each way produces a directional line from the base station to the mobile station. Two base stations can get two directions. The intersection point is the location of the mobile station. Therefore, the AOA method requires only two base stations to determine the location of the mobile station. As shown in the following figure, θ1 is the angle at which the signal of the mobile station P arrives at the base station A, and θ2 is the angle at which the signal arrives at the base station B.
AOA-based positioning principle
The AOA needs to accurately measure the incident angle of the electromagnetic wave, and the requirements for the antenna are very high. If each base station is equipped with an antenna array, the complexity of the device will become high. However, multipath effects and environmental changes in the indoor environment can seriously affect the direction of judgment and interfere with the positioning results.
3. Indoor positioning classification
The classification of indoor positioning technology has important value for the construction of indoor positioning structure system. In 2001, J. Hightower and G. Borriello of the University of Washington proposed to classify positioning technology in terms of positioning type, absolute/relative positioning, active/passive positioning, accuracy, coverage, and signals used to facilitate researchers. And developers better evaluate a positioning system. Liu Changzheng et al. of Tsinghua University, in 2003, classified positioning technologies into network-based positioning technologies and mobile terminal-based positioning technologies based on measured and calculated entities. In the year of 2006, Fang Bingyi of Beijing Institute of Technology roughly classified indoor positioning technology into “target discovery†and “smart space†categories according to application accuracy. Li Yong classified indoor positioning systems according to the communication methods and techniques used in the measurements.
In 2009, Liang Yuancheng proposed three classification methods of indoor positioning technology: based on location awareness technology, it is divided into proximity technology based on proximity relations, triangulation and scene-based analysis; based on signal measurement technology, it is divided into RSSI-based measurement, based on TOA Measurements, TDOA-based measurements, AOA-based measurements, Cell-ID based and BER (Bit Error Rate) based measurements; based on sensor type, can be divided into RFID, Infrared, Ultrasound, Bluetooth, Ultra-wideband, Zigbee, WLAN GSM and GPS.
In the same year, F. Seco classified positioning technologies into four categories based on positioning algorithms in indoor positioning: a geometry-based method, a cost-based minimization method, fingerprint positioning, and Bayesian technology.
In 2013, Deng Zhongliang from Beijing University of Posts and Telecommunications proposed that it can be divided into identity, geometric method and fingerprint positioning according to the positioning principle; divided into Wi-Fi, Zigbee, RFID, Bluetooth, ultra-wideband, pseudo-satellite, and cellular network according to different transmission signals. And laser etc.
At the same time, according to the positioning range is divided into a wide area indoor positioning and living in indoor positioning. Other common location classification criteria include distance- and distance-independent positioning technology, incremental and concurrent positioning technologies, location technologies based on beacon nodes and non-beacon nodes, and centralized positioning and distributed positioning technologies.
4. Mainstream indoor positioning technology
According to the above-mentioned positioning method, a variety of indoor positioning technologies are derived, and the mainstream indoor positioning technology will be briefly introduced below.
(1) Visual positioning
The visual positioning system can be divided into two categories. One is to determine the position of the sensor by capturing images from a moving sensor (such as a camera), and the other is to determine the position of the target to be measured in the image by a fixed position sensor. According to the reference point selection, they can be divided into reference 3D building models, images, pre-deployment targets, projection targets, his sensors, and no reference. Reference 3D building models and images are compared against existing building structure databases and pre-calibrated images, respectively. In order to improve the robustness, reference to the pre-deployment goal uses a specific layout of a specific image marker (such as a two-dimensional code) as a reference point; the projection target is to project a reference point in the indoor environment based on the reference pre-deployment target. With reference to other sensors, other sensor data can be integrated to improve accuracy, coverage or robustness.
Hile and Borriello used a camera phone to compare the image and the floor plan to achieve a positioning accuracy of 30cm. Sjö uses a low-resolution camera to implement the SLAM (Simultaneous Localization And Mapping) algorithm based on the reference image, achieving sub-meter positioning accuracy. Mulloni uses a bar code as a reference mark to achieve centimeter to decimeter-level positioning accuracy. Tilch and Mautz use a moving camera and laser for projection with sub-millimeter positioning accuracy. Liu T. uses a 6-degree-of-freedom Inertial Measurement Unit (IMU) and two laser scanners to acquire the position with an average positioning accuracy of 1% of the walking distance.
(2) Infrared positioning
Infrared is an electromagnetic wave whose wavelength is between radio waves and visible waves. Infrared-based positioning systems can be mainly divided into two categories: active beacons, infrared imaging.
Active beacons place a number of infrared receivers indoors, while the object to be tested carries an electronic tag equipped with an infrared transmitter. The tag periodically sends the ID of the DUT. The receiver receives the signal and sends the data to the database for positioning. This method is representative of the Active Badge system jointly released by AT&T Labs and Cambridge in 1992. The system can achieve an average positioning accuracy of 6m.
Infrared imaging is the detection of pedestrians or other targets to be detected through natural infrared radiation generated images in the sensor acquisition environment. In 2011, Ambiplex of Germany provided "IR.Loc" positioning system based on the thermal radiation of the natural environment. Based on AOA, the position of the heat source was determined, and positioning accuracy of 20cm to 30cm within a range of 10m was achieved.
(3) Polar Systems (Polar Positioning)
The system uses the instrument to measure the arrival angle or arrival time for positioning. The instrument usually has a laser tracker, total station and theodolite. Total coverage of the total station is usually 2km ~ 10km, but its high cost of equipment, large volume and the requirements of the visual distance make it not suitable for promotion in indoor positioning. The iGPS (indoor Global Positioning System) released by NikonMetrology in 2011 realized laser-based indoor industrial-grade high-precision three-dimensional positioning. The principle is different from that of GPS, in which no less than two transmitters with fixed positions transmit a sector-shaped laser beam and a reference infrared pulse, and the receiver is positioned based on the TDOA principle. NikonMetrology claims that the system can realize a 0.2mm three-dimensional positioning accuracy in a typical test environment of 1200m2 with 4 to 8 transmitters. But its cost is very expensive, it can be used for industrial-level positioning needs, not suitable for mass market research and promotion.
(4) Ultrasonic positioning
Ultrasonic positioning mainly uses reflective distance measurement method to determine the position of an object through multilateral positioning. The system consists of a main ranger and several receivers. The main rangefinder can be placed on the target to be measured, and the receiver is fixed in the indoor environment. in. During positioning, a signal of the same frequency is transmitted to the receiver, and the receiver receives the signal and transmits the signal to the main ranger. The distance is calculated based on the time difference between the echo and the transmitted wave, thereby determining the position.
Established by Ward in 1997, ActiveBat is a pioneer in ultrasound positioning. It has achieved a positioning accuracy of 3cm by deploying a large number of receiving devices (720 tags). The overall positioning accuracy of ultrasonic positioning is high and the structure is simple. However, ultrasonic waves are greatly influenced by multi-path effects and non-line-of-sight propagation. The ultrasonic frequency is affected by the Doppler effect and temperature. At the same time, a large amount of basic hardware facilities are needed, and the cost is high.
(5) WLAN positioning
The wireless LAN based on the IEEE 802.11b standard has been widely deployed in people's places of life. The advantage of using WLAN signal positioning is that it does not require the deployment of additional equipment, low positioning cost, large signal coverage, and strong applicability, which is conducive to popularization and promotion. The RSSI-based fingerprint positioning method is currently the mainstream WLAN positioning method, and the positioning accuracy depends on the density of calibration points, ranging from 2m to 10m. At the same time, the positioning method based on TOA ranging has poor positioning effect due to multi-path effect and low clock resolution, and the positioning method based on RSSI ranging changes in different environment and equipment conditions due to the relationship between signal attenuation and distance. Not ideal.
(6) RFID positioning
Radio frequency identification (RFID) is a technology that is easy to control and applicable to the field of automatic control. It utilizes the transmission characteristics of inductance and electromagnetic coupling to realize the automatic identification of objects to be identified. RFID positioning system usually consists of an electronic tag, a radio frequency reader and a computer database. The most commonly used positioning method is proximity detection. Using RSSI to implement a multilateration algorithm can also achieve range estimation to some extent. According to whether the electronic tag is active or not, it can be divided into active RFID and passive RFID.
1 Active RFID: Active RFID's electronic tag contains a battery, so the signal transmission range is larger than passive RFID, reaching more than 30m. At the same time, fingerprint positioning based on RSSI measurement can be implemented. Seco used a Gaussian process to describe the propagation of RSSI in the room combined with the method of fingerprint positioning. In a 1600m2 experimental environment, 71 RFID tags were used to achieve a 50% positioning error of 1.5m.
2 Passive RFID: Passive RFID systems rely only on inductive coupling and therefore do not have a battery. Compared to active RFID, it is smaller, more durable and lower cost. Passive RFID positioning systems use proximity detection methods to achieve positioning.
(7) Ultra-wideband positioning
UWB positioning systems usually include UWB receivers, reference tags, and other tags. Ultra-wideband technology transmits ultra-narrow pulses of nanoseconds or less to transmit data, achieving GHz-level data bandwidth, low transmit power, and no carrier. Because of its high bandwidth, centimeter-level positioning is theoretically based on TOA or TDOA methods. Ubisense was released in 2011 using TDOA and AOA indoor positioning system, positioning accuracy of up to 15cm, range of up to 50m. However, the higher system construction cost of the UWB system hinders its popularization and promotion.
(8) Inertial Navigation
The Inertial Navigation System (INS) is widely used for navigation and tracking of guided weapons, warships, rockets, aircrafts, and vehicles. Its core component IMU consists of three orthogonal uniaxial accelerometers and three orthogonal ones. Gyroscope composition. With the development of micro-electromechanical technology, sensors have become smaller in size and lower in cost. At the same time, magnetometers have been added and are widely used in pedestrian navigation.
Inertial navigation is based on dead reckoning methods, so cumulative errors occur over time, and their positioning accuracy depends on the quality of the sensor and the location of the sensor. The inertial navigation tied to the feet can use a zero-speed correction to limit the drift. The positioning error is less than 1% of the walking distance, while positioning in other positions is often greater than 1%. With the popularity of smart phones and the development of micro-electromechanical devices, inertial navigation based on smart phones has become a research hotspot.
(9) Geomagnetic positioning
Modern buildings generally have reinforced concrete structures. The metal structures inside the walls of these buildings will have a great impact on the indoor geomagnetic field, and indoor electrical equipment will also affect the magnetic field. At the same time, the indoor magnetic field has a strong stability. Therefore, the indoor geomagnetic field is an effective information source that can be used for indoor positioning navigation. Geomagnetic positioning refers to a technical solution that uses the specificity of the geomagnetic field to obtain position information. The positioning method mainly uses the fingerprint positioning method. Due to the original magnetic field information, the cost is lower than other positioning technologies, but it is still necessary to create a database manually. IndoorAtlas's geomagnetic positioning program is representative of it, positioning accuracy can reach 1 ~ 2m.
(10) Pseudolites
A satellite is a ground-based generator that can transmit signals similar to GNSS. The simplest component is a GNSS signal generator and transmitter. The pseudo-satellite, which is different from the GNSS signal system, can avoid interference to normal satellite signals and can achieve centimeter-level positioning accuracy, but the equipment is complicated and the cost is high. The system Locata released in 2010 can achieve a positioning accuracy of 2cm within 50km2.
(11) Bluetooth and ZigBee positioning
Similar to Bluetooth and ZigBee technology, there are some overlapping bands, and both positioning technologies are based on short-range low-power communication protocols: ZigBee is a low-power LAN protocol based on the IEEE 802.15.4 standard; currently Bluetooth uses Bluetooth 4.0 specifications. Based on Bluetooth low energy (BLE) technology. Both have the characteristics of close range, low power consumption, and low cost. ZigBee (Bluetooth) positioning is based on the placement of a static reference point (Bluetooth Beacon) in the indoor environment, enabling positioning systems based on proximity detection, centroid, multilateration, and fingerprint positioning. The positioning accuracy mainly depends on the deployment density of the infrastructure. The Bluetooth 5.0 protocol released in 2016 supports Angle of Arrival (AoA) and Angle of Departure (AoD) parameter estimation of BLE Direction Finding. These parameters will provide technical support for indoor positioning within 1m.
(12) Cellular Network Location
Cellular network technology is a mature communication technology and is mainly used to locate mobile phones. The cellular network can detect neighboring soundings, AOA, TOA, and OTDOA (Observed Time Difference Of Arrival) by detecting characteristic parameters (RSSI, propagation time or time difference, incident angle, etc.) of signals transmitted between the mobile station and multiple base stations. Time difference) to achieve positioning, can be used as a universal positioning program. The current Cell-ID plus RTT solution accuracy is 20 ~ 60m. Using smart antenna MIMO+TDOA/AOA technology, the accuracy can reach 5~10m. The future 5G network has the advantages of large bandwidth, multiple antennas, and dense networking, and can achieve positioning accuracy within 1m.
(12) Fusion positioning
Fusion location refers to the integration of multiple positioning technologies and multi-sensor information for comprehensive positioning, to achieve complementary advantages, improve positioning accuracy, robustness, and reduce positioning costs. The choice of location technology is mainly based on the needs of the scene, and is mostly a combination of absolute positioning technology and relative positioning technology. For example, Guo Weilong of Zhejiang University has achieved an indoor positioning system combining geomagnetic and inertial navigation, and the 90% positioning error is less than 4.5m during a smooth walking. Qian Jiuchao of Shanghai Jiaotong University combined the inertial navigation positioning with the map to achieve the indoor positioning of the mobile phone. The 95% error under the normal holding gesture is 0.8m. At the same time, there are many studies that combine Wi-Fi and INS to achieve better results. For pedestrians' complex movement behavior, relevant literature proposes a pedestrian identification method assisted by motion recognition, which improves the robustness of indoor positioning.
(13) Cooperative positioning
Cooperative positioning refers to the existence of known nodes and unknown nodes in a positioning scenario. Information can be exchanged between unknown nodes, and ranging, direction finding, or proximity detection can be performed between them, and positioning information from past moments can be used. In order to achieve the current position of the unknown node. The specific method of co-location can be adjusted according to a specific location technology. The goal is to improve the positioning performance of a single node and the entire system through collaborative cooperation between nodes. Cooperative positioning is attracting more and more attention in the research of multi-robot positioning, wireless network positioning, underwater autonomous vehicles and satellite positioning. The literature reviews the research on co-localization of wireless sensor networks. The R. Garello team of the Politecnico of Italy conducted research on co-locating satellite-assisted terminal assisted capture and compared the performance of several common localization algorithms. The relevant literature reviews the collaborative positioning of autonomous underwater vehicles.
(14) Crowdsensing
Group Wisdom perception is based on the common user's mobile device as the basic unit of perception, through the formation of network communications network intelligence perception, so as to achieve the distribution of sensing tasks and awareness of data collection, complete large-scale and complex social sensing tasks. In the field of computer science, concepts related to group-wise perception include: Crowd computing, Social sensing, Crowdsourcing, and so on. In the field of indoor positioning, group perception has also been widely studied and applied. The literature analyzes the use of Crowd Sensing for opportunity signal acquisition and applies it to indoor positioning methods. Wu Chenyu of Tsinghua University proposed a wireless signal fingerprint map construction technique without artificial site survey using the mobile group intelligence perception mechanism. Zhang Min of Shanghai Jiaotong University combines the user's motion information with wireless signals, and uses wireless virtual landmarks and GraphSLAM graph optimization methods to build a wireless location fingerprint database using group intelligence perception. Gao Wenzheng of Shanghai Jiaotong University is also based on group intelligence perception. It proposes an attenuation life cycle description method for fingerprint signals and implements an adaptive update of the wireless location network fingerprint database.
Second, the application of indoor positioning technology
Indoor positioning technology as a continuation of positioning technology in the indoor environment, to make up for the deficiencies of the traditional positioning technology, has been put into practical application in a specific industry, and has achieved certain application results, has a good application prospects.
Indoor location service
Indoor location services are used in large-scale supermarkets, airports, hotels, museums, convention centers and other large indoor scenes. In large-scale supermarkets where layouts are relatively complex, users can find the location of products of interest; in large shopping malls, users can also search for shops and entertainment venues that they want to go to. Meanwhile, merchants can also conduct targeted advertisements and provide personalities. Marketing. In a museum or convention center, indoor positioning can also easily provide location navigation services.
2. Public safety
Indoor positioning plays an important role in emergency rescue, firefighting, and security enforcement. When an emergency such as an earthquake or fire occurs, the necessary condition for rescue is to quickly determine the location of the person. Especially when buildings change due to the layout of emergency situations, it is difficult to quickly locate personnel positions based on experience. Indoor positioning technology can provide strong technical support for rescue, better protect the safety of rescue workers and trapped persons, and carry out effective rescue more quickly.
3. Personnel management
Indoor positioning can provide indoor positioning and monitoring services for special populations such as students, patients, and prisoners. Specifically, students' parents are provided with the student's arrival status; the company's employees are provided with attendance services; prisons are provided with prisoner activity reports; and kindergartens are provided with electronic fences for real-time monitoring.
At the same time, indoor positioning can also provide positioning services for warehousing, which facilitates anti-theft, sorting, and transportation of items and provides full-range location records.
4. Intelligent Transportation
Indoor positioning technology combined with traditional positioning technology can provide indoor and outdoor seamless positioning and navigation services, which can provide vehicles with full navigation services from roads to parking lots, and also solve the problem of finding cars for large and complex underground parking lots.
5. Big data analysis
Indoor positioning can record the trajectory of the user's activity, perform big data analysis on the data, and link the user's location with the behavior and interest preferences behind it. Therefore, the mining and analysis of indoor positioning data has great commercial value and application prospects. For example, an analysis of a consumer's activity in a mall can analyze the frequency and duration of visits to a store, so as to obtain consumers' interests and preferences, as well as store popularity, and provide powerful help for business analysis.
6. Social network
Social networks play an important role in people's lives. Location is the core of social networks. In an indoor environment that accounts for about 80% of people's lives, true and accurate locations can associate friends with activities.
III. Difficulties and development trends of indoor positioning
Although the accuracy of indoor positioning technology has been continuously improved, it has not been popularized in all walks of life. The main difficulties are as follows:
Complex environment
The layout of the indoor environment is complex and varied, with many obstacles including furniture, rooms and pedestrians. At the same time, there are many sources of interference in the indoor environment. Lighting, temperature, sound, and other sources of interference will affect positioning.
2. Unknown environmental positioning difficulties
At present, most indoor positioning technologies are based on a priori understanding of the indoor environment. Some positioning technologies also require the deployment of base stations in advance. However, in actual applications, environmental information may not be available, or positioning base stations may be disturbed and destroyed, such as earthquakes and fires. on site. Reducing the dependence on the environment is also a difficulty in indoor positioning.
3. It is difficult to balance positioning accuracy and cost
Current high-precision indoor positioning technologies require relatively expensive additional auxiliary equipment or a large amount of manual processing in the early stage, which greatly restricts the popularization of the technology. Low-cost positioning technology needs improvement in positioning accuracy. Reducing costs on the basis of providing high-precision positioning is also a direction of indoor positioning.
With the continuous development of indoor positioning technology, high-precision, low-cost, universal indoor positioning technology is the future goal. The integrated use of various positioning technologies and information fusion will be a feasible solution to the current difficulties in indoor positioning. The rapid development of computer vision, 5G mobile communication networks, NB-IOT Internet of Things and other technologies will provide more technical approaches for indoor positioning technology. In the future, large-scale indoor positioning solutions that are widely used, such as outdoor GNSS, will inevitably emerge. In combination with outdoor positioning technologies, full-space seamless positioning will be realized.
Fourth, the conclusion
The demand for indoor positioning has been reflected in all aspects of people's lives. How to achieve high-precision and low-cost universal indoor positioning is already a problem that is being addressed in the field of positioning. This article describes the main indoor positioning methods, positioning techniques, application scenarios and development difficulties for reference.