The advances in localization based technologies and the increasing importance of ubiquitous computing and context-dependent information have led to a growing business interest in location-based applications and services. Today, most application requirements are locating or real-time tracking of physical belongings inside buildings accurately; thus, the demand for indoor localization services has become a key prerequisite in some markets. Moreover, indoor localization technologies address the inadequacy of global positioning system inside a closed environment, like buildings. Based on this, though, this paper aims to provide the reader with a review of the recent advances in wireless indoor localization techniques and system to deliver a better understanding of state-of-the-art technologies and motivate new research efforts in this promising field. For this purpose, existing wireless localization position system and location estimation schemes are reviewed, as we also compare the related techniques and systems along with a conclusion and future trends.
Location based services (LBSs) [
The basic components of LBS are software application (provided by the provider), communication network (mobile network), a content provider, a positioning device, and the end user’s mobile device. There are several ways to find the location of a mobile client indoors and outdoors. The most popular technology outdoors is global positioning system (GPS) [
Positioning system can be categorized depending on the target environment as either indoor, outdoor, or mixed type. For localization in an outdoor environment, global navigation satellite systems (GNSS) such as GPS have been used in a wide range of applications including tracking and asset management systems; transport navigation and guidance; synchronization of telecommunications networks; geodetic survey. GPS works extremely well in outdoor positioning. Unfortunately, GPS does not perform well in urban canyons, close to walls, buildings, trees, indoors, and in underground environments as the signal from the GPS satellites is too weak to come across most buildings thus making GPS ineffective for indoor localization [
Indoor positioning [
Signal strength pattern.
Indoor navigation technologies.
The performance criteria associated with localization systems can be classified into the following areas.
Accuracy (or location error) of a system is the important user requirement of positioning systems. Accuracy can be reported as an error distance between the estimated location and the actual mobile location. Sometimes, accuracy is also called the area of uncertainty; that is, the higher the accuracy is, the better the system is.
The responsiveness determines how quickly the location estimate of a moving target is updated.
The problem of determining the network coverage for a designated area is important when evaluating the effectiveness of a positioning system. Coverage is closely related to accuracy. Coverage can be categorized as local coverage, scalable coverage, and global coverage. Local coverage is a small well-defined, limited area which is not extendable (e.g., a single room or building). In this case, the coverage size is specified (e.g., (m), (m2), or (m3)). Scalable coverage means systems with the ability to increase the area by adding hardware, and global coverage means system performance worldwide or within the desired/specified area.
Environmental influence changes may affect the localization system performance. The ability of the localization system to cope with these changes is called its adaptiveness. A system that is able to adapt to environmental changes can provide better localization accuracy than systems that cannot adapt. An adaptive system can also prevent the need for repeated calibration.
Scalability is a desirable property in almost any system that suggests how well the system performs when it operates with a larger number of location requests and a larger coverage. Poor scalability can result in poor system performance, necessitating the reengineering or duplication of systems. A scalable positioning system should be able to handle large numbers of tags without unnecessary strain.
The cost gained from a positioning system can arise from the cost of extra infrastructure, additional bandwidth, money, lifetime, weight, energy, and nature of deployed technology. The cost may include installation and survey time during the deployment period. If a positioning system can reuse an existing communication infrastructure, some part of infrastructure, equipment, and bandwidth can be saved. The complexity of the signal processing and algorithms used to estimate the location is another issue that needs to be balanced with the performance of positioning systems. Tradeoffs between the system complexity and the accuracy affect the overall cost of the system.
Several different methods are used for location techniques and algorithms in wireless based localization. Location detection techniques can be divided into three general categories: proximity, triangulation and scene analysis as shown in Figure
Location detection based classification.
Proximity detection or connectivity based is one of the simplest positioning methods to implement. It provides symbolic relative location information. The position of mobile client is determined by cell of origin (CoO) method with known position and limited range [
Triangulation uses the geometric properties of triangles to determine the target location. It has two derivations: lateration and angulation. Techniques based on the measurement of the propagation-time system (e.g., TOA, RTOF, and TDOA) and RSS-based and received signal phase methods are called lateration technique [
Angle-of-arrival positioning method.
AOA-based techniques have their limitations. AOA requires additional antennas with the capacity to measure the angles which increase the cost of the AOA system implementation. In indoor environments, AOA-based methods are affected by multipath and NLOS propagation of signals, along with reflections from walls and other objects, so it is not good for indoor implementation. Due to these factors, it can significantly change the direction of signal arrival and thus degrade the accuracy of an indoor AOA-based positioning system [
Positioning based on TOA/RTOF measurements.
ToA method needs precise knowledge of the transmission start time(s). Due to this, all receiving beacons along with mobile devices are accurately synchronized with a precise time source. ToA is the most accurate technique used in indoor environment which can filter out multi-path effects [
Time difference of arrival (source [
The majority of wireless localization systems compute the distance to the positioning device using either timing information or angle based. In both scenarios, they are influenced by the multipath effect. Due to this, the accuracy of estimated location can be decreased. The substitute method is to estimate the distance of unknown node to reference node from some sets of measuring units using the attenuation of emitted signal strength [
Dead reckoning is the process of estimating known current position based on last determined position and incrementing that position based on known or estimated speeds over elapsed time. An inertial navigation system which provides very accurate directional information uses dead reckoning and is very widely applied [
This method is based on the theory of pattern recognition [
This section presents a review of most prominent state-of-the-art wireless positioning systems as shown in Figure
Comparisons of indoor position methods.
Method | Measurement type | Indoor accuracy | Coverage | Line of sight (LOS)/nonline-of sight (NLOS) | Affected by multipath | Cost | Notes |
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Proximity |
Signal type | Low to high | Good | Both | No | Low | (1) Accuracy can be improved by using additional antenna. However, it will increase the cost. |
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Direction (AoA) | Angle of arrival | Medium | Good (Multipath issues) | LOS | Yes | High | (1) Accuracy depends on the antenna’s angular properties |
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Time (ToA, TDoA) | Time difference of arrival | High | Good (Multipath issues) | LOS | Yes | High | (1) Time synchronization needs. |
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Fingerprinting | Received signal strength | High | Good | Both | No | Medium | (1) Need heavy calibration. |
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Dead |
Acceleration, velocity | Low to medium | Good | NLOS | Yes | Low | Inaccuracy of the process is cumulative, so the deviation in the position fix grows with time. |
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Map matching | An algorithm based on algorithms based on |
Medium | Medium (indoor) |
NLOS | Yes | Medium | (1) Map matching purely focus on algorithms and not fully on position methods, coordinate transformation, and geocoding |
Taxonomy of position systems.
Global positioning system (GPS) is the most popular and worldwide radio navigation system to find the location and the position of the objects especially for outdoor environment [
Infrared radiation (IR) positioning systems are one of the most common positioning systems that use wireless technology. The spectral region of infrared has been used in various ways for detection or tracking of objects or persons and available in various wired and wireless devices such as mobile phone, PDAs, and TV [
Radio frequency technologies [
Radio frequency identification (RFID) has been recognized as the next promising technology in serving the positioning system for locating objects or people. RFID enables a one way wireless communication using a noncontact and advanced automatic identification technology that uses radio signals that put an RFID tag on people or objects, for the purpose of automatic identification, tracking, and management. Tracking the movements of objects in RFID is done through a network of radio enabled scanning devices over a distance of several meters. RFID technology is used in a wide range of applications including people, automobile assembly industry, warehouse management, supply chain network, and assets without the need of line of sight contact [
Bluetooth is a wireless standard for wireless personal area networks (WPANs). Almost every WiFi enabled mobile device, such as mobile phone or computer, also has an embedded bluetooth module. Bluetooth operates in the 2.4 GHz ISM band. The benefit of using bluetooth for exchanging information between devices is that this technology is of high security, low cost, low power, and small size. Each bluetooth tag has a unique ID, which can be used for locating the Bluetooth tag. There are several recent research works dedicated to bluetooth based localization systems [
Ultrawideband (UWB) is a radio technology for short-range, high-bandwidth communication holding the properties of strong multipath resistance. Widespread use of UWB in a variety of localization applications requiring higher accuracy 20–30 cm than achievable through conventional wireless technologies (e.g., radio frequency identification (RFID), wireless local area networks (WLAN), etc.) [
The FM radio based system is popular through the ages. It is widely available across the globe especially in most households and in cars. FM radio uses the frequency-division multiple access (FDMA) approach which splits the band into a number of separate frequency channels that are used by stations. FM band ranges and channel separation distances vary in different regions. There are only a few works dedicated to FM radio based positioning. Recently [
The ZigBee technology is an emerging wireless technology standard which provides solution for short and medium range communications due to its numerous benefits [
Hybrid positioning systems are defined as systems for determining the location of a mobile client combining several different positioning technologies [
Ultrasound system is a technology based on the nature of bats and operates in the low frequency band compared to the other two signaling technologies. The ultrasound signals are used to estimate the position of the emitter tags from the receivers. Ultrasound is unable to penetrate walls but reflects off most of the indoor obstructions. However, it has a lower level of accuracy (in centimeters) and suffers a lot of interference from reflected ultrasound signals propagated around by other sources such as the collision of metals. Some recent research work [
One of the advantages of using WiFi Positioning Systems is to locate the position of almost every WiFi compatible device without installing extra software or manipulating the hardware. Beside this, in WLAN, line of sight is not required. Due to this advantage, WiFi positioning systems have become the most widespread approach for indoor localization [
Most positioning systems based on WLAN (WiFi) are available as commercial products as prototypes based on measurements on the received signal strength (RSS). WiFi based positioning systems have several advantages.
Firstly in terms of cost effect, WLAN infrastructures implementation of position algorithms does not need any additional hardware as network interface cards (NICs) measure signal strength values from all wireless access points in range of the receiver. Therefore, signals needed for positioning can be obtained directly from NICs available on most handheld computing devices. Due to the ubiquity of WLANs, this mode of positioning provides a particularly cost-effective solution for offering LBS in commercial and residential indoor environments [
WiFi strengths, weaknesses, and opportunities.
Strengths | (i) Found in almost every building, fairly good available signal strengths. |
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Weaknesses | (i) Site surveying time consuming and labor intensive. |
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Opportunities |
(i) Fingerprinting does not need geometric surveys. |
Comparison of common position systems used for localization.
System | Accuracy | Principles used for localization | Coverage | Power |
Cost | Remarks |
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GPS |
6 m–10 m | ToA | Good outdoor Poor indoor | Very high | High | (1) Satellite based Positioning. |
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Infrared | 1 m-2 m | Proximity, ToA | Good Indoor | Low | Medium | (1) Short range detection. |
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WiFi | 1 m–5 m | Proximity, ToA, TDoA, RSSI Fingerprinting, and RSSI theoretical propagation model | Building level (outdoor/indoor) | High | Low | (1) Infrastructure available everywhere. |
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Ultrasound | 3 cm–1 m | ToA, AoA | Indoor | Low | Medium | (1) Sensitive to environmental. |
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RFID | 1-2 m | Proximity, TOA, RSSI theoretical propagation model | Indoor | Low | Low | (1) Real time location system. |
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Bluetooth | 2 m–5 m | RSSI fingerprinting and RSSI theoretical propagation model | Indoor | Low | High | (1) Data transfer speed is high. |
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ZigBee | 3 m–5 m | RSSI fingerprinting and RSSI theoretical propagation model | Indoor | Low | Low | (1) Low data transmission rate. |
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FM | 2 m–4 m | RSSI fingerprinting | Indoor | Low | Low | (1) Less susceptible to objects. |
cm: centimeters; m: meters.
Most indoor localization approaches adopted fingerprint matching as the basic scheme of location determination. The main theme is to collect features of the scene (fingerprint) from the surrounding signatures at every location in the areas of interest and then build a fingerprint database. The location of an object is then determined by matching online measurement with the closed location against the database [
Fingerprinting based positioning.
This method does not require specialized hardware in either the mobile device or the receiving end nor is no time synchronization necessary between the stations. It may be implemented totally in software which can reduce complexity and cost significantly compared to angulation or purely time-based lateration systems [
The location fingerprinting also called a fingerprinting method consists of two phases [
Fingerprinting-based positioning algorithms using pattern recognition techniques are deterministic and probabilistic,
In this part of paper, we are presenting some recent research work done on WiFi localization with a specific focus on fingerprinting-based localization technique.
Different approaches using WiFi access points are studied from time to time. Pereira et al. [
Indoor localization using WiFi based fingerprinting and trilateration techniques for LBS application is presented by S. Chan et al. [
In [
By using Wi-Fi, it is possible to define the position of people or assets with good accuracy. In [
A novel, information-theoretic approach is presented by Fang and Lin [
Received signal strength indication (RSSI) is defined by the IEEE 802.11 Standard. It is a measurement of the RF energy, and the unit is dBm. Mobile client (MC) can get the RSSI from access point (AP) on the WLAN. The RSSI is decreased exponentially as the distance from AP increased, and this can be expressed by log path loss model. Reference [
Fingerprinting accuracy performance depends on the number of base stations and the density of calibration points where the fingerprints are taken. Recorded RSSI varies in time, even if there are no changes to the environment. In order to eliminate the deviation of attenuation in the signal, the RSS values are to be averaged over a certain time interval up to several minutes at each fingerprint location. Hansen et al. [
In [
Aboodi and Tat-Chee [
The authors of [
Simplified block diagram [
Yang et al. [
IEEE 802.11n is an amendment to the IEEE 802.11-2007 wireless networking standard to improve network throughput over the two previous standards—802.11a and 802.11g—with a significant increase in the maximum net data rate from 54 Mbit/s to 600 Mbit/s. It also improves WLAN standard in terms of network throughput by adding a technology which supports multiple antenna configurations, known as multiple-input multiple-output (MIMO). Xiong and Jamieson [
This paper surveys the recent advances in wireless indoor localization techniques and system. Different technological solutions for wireless indoor positioning and navigation are discussed, and several tradeoffs among them are observed. Regardless of the plenty of approaches which exist to handle the indoor positioning problem, current solutions cannot cope with the performance level that significant applications required. In short, requirements for different application environments are accuracy/precision, coverage, availability, and minimal costs for local installations. To achieve this shortcoming, a good portion of research approaches is required to handle these challenges. Some of the future trends of wireless indoor positioning systems are as follows: new hybrid solution for positioning and tracking estimation in 4G with the currently available position system, need of cooperative mobile localization which will help mobile nodes among each other to determine their locations, new innovative applications for mobile in which location information can be used to improve the quality of users’ experience and to add value to existing services offered by wireless providers.
The authors would like to thank the National University of Malaysia and the Ministry of Science, Technology and Innovation for the financial support of this work, under the Grant Ref. 01-01-02-SF0788. The authors also would like to thank the anonymous reviewers for their valuable feedback.