Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances†
- We provide an updated survey and a comparative analysis of existing indoor positioning technologies that we believe would spur further exploration by the research community of this difficult problem space (see Section 2).
- We conduct a strengths, weaknesses, opportunities and threats (SWOT) analysis for UWB technology, which provides new directions and deeper insights into the state of this technology beyond its well-known pros and cons (see Section 5).
2. Indoor Positioning Systems
2.1. Why Indoor Positioning Systems?
2.2. IPS Performance Metrics
2.3. Indoor Positioning Technologies
3. UWB Positioning
3.1. Why UWB Has Gained Attention Recently?
3.2. Signal Modulation
3.3. Policy and Regulation of UWB Use
4. UWB Positioning Algorithms
4.1. AOA-Based Algorithms
4.2. TOA-Based Algorithms
4.3. TDOA-Based Algorithms
4.4. RSS-Based Algorithms
4.5. Hybrid-Based Algorithms
4.6. Comparison of Positioning Algorithms
5. SWOT Analysis
6. Lessons Learned and Concluding Remarks
Conflicts of Interest
|Biased Kalman Filtering||BKF|
|Binary Phase Shift Keying||BPSK|
|Carrier Sense Multiple Access with Collision Avoidance||CSMA/CA|
|Channel Impulse Response||CIR|
|Extended Kalman Filter||EKF|
|Federal Communications Commission||FCC|
|Full Function Device||FFD|
|Global Positioning System||GPS|
|Global System for Mobile Communications||GSM|
|Impulse Radio Ultra WideBand||IR-UWB|
|Indoor Positioning System||IPS|
|Infrared Data Association||IrDA|
|Joint Committee for Guides in Metrology||JCGM|
|Least Square with Distance Contraction||LS-DC|
|Line of Sight||LOS|
|Local Area Network||LAN|
|Low data Rate UWB||LR-UWB|
|Maximum Likelihood Estimation||MLE|
|Micro Electro Mechanical Sensors||MEMS|
|Pulse Amplitude Modulation||PAM|
|Pulse Position Modulation||PPM|
|Pulse Width Modulation||PWM|
|Real-Time Location System||RTLS|
|Received Signal Strength||RSS|
|Reduced Function Device||RFD|
|Strengths, Weaknesses, Opportunities, and Threats||SWOT|
|Time Difference of Arrival||TDOA|
|Time Division Multiple Access||TDMA|
|Time-Hopping Binary Phase Shift Keying||TH-BPSK|
|Time-Hopping Pulse Position Modulation||TH-PPM|
|Time-Hopping Spread Spectrum||TH-SS|
|Time Modulated Ultra WideBand||TM-UWB|
|Angle of Arrival||AOA|
|Time of Arrival||TOA|
|Transmit Power Control||TPC|
|Weighted Least Square with Multidimensional Scaling||WLS-MDS|
|Wireless Local Area Network||WLAN|
|Wireless Personal Area Network||WPAN|
|Worldwide Interoperability for Microwave Access||WiMAX|
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|Pandey et al. ||2006||Indoor, Outdoor||General||Localization techniques for wireless networks|
|Liu et al. ||2007||Indoor||Wireless||A quantitative comparison of indoor positioning solutions|
|Khodjaev et al. ||2009||Indoor||UWB||A comparison of different methods of NLOS identification and error mitigation|
|Honkavirta et al. ||2009||Indoor||Wireless||A comparative study of WLAN location fingerprinting methods based on RSS values|
|Wang et al. ||2009||Indoor, Outdoor||General||Localization methods of sensor nodes in WSN|
|Guvenc et al. ||2009||Indoor||RF||TOA positioning algorithms in NLOS environments|
|Ruiz-López et al. ||2010||Indoor||General||An analytic review of different positioning techniques in relation several quality attributes|
|Al Nuaimi and Kamel ||2011||Indoor||General||A short survey of existing indoor positioning technologies|
|Ijaz et al. ||2013||Indoor||RF, Ultrasonic||A comparison of the ultrasonic system based on performance, accuracy and limitations|
|Adalja Disha ||2013||Indoor||Wireless||A performance comparisons including (among others) precision complexity, accuracy, scalability, cost, and robustness|
|Zhu et al. ||2014||Indoor||General||A review of indoor positioning technologies|
|Accuracy||“The closeness of agreement between a measured quantity value and a true quantity value of a measure” |
|Availability||The positioning service availability in terms of time percentage|
|Coverage Area||The area covered by an IPS|
|Scalability||The degree to which the system ensures the normal positioning function when it scales in one of two dimensions: geography and number of users|
|Cost||Can be measured in different dimensions; money, time, space, and energy which can be affected at different levels of the system: system installation and maintenance, infrastructure components, and positioning devices [3,5]|
|Privacy||Strong access control over how users’ personal information is collected and used |
|Author-Year||Classified based on||Categories|
|Collin et al.—2003||Need for hardware||Technologies that require hardware in the building, and self-contained ones|
|Gu et al.—2009||Existence of network||Network-based and non-network-based technologies|
|System architecture||Self-positioning architecture, self-oriented infrastructure-assisted architecture, and infrastructure positioning architecture|
|Main medium used to determine positions||Ultrasound, radio frequency, magnetic, vision-Based, and audible sound technologies|
|Al Nuaimi and Kamel—2011||Installed system in a building||Fixed indoor positioning and indoor pedestrian positioning|
|Chliz et al.—2011||Prior knowledge||Parametric and non-parametric technologies|
|Rainer Mautz—2012||Sensor type||Camera, infrared, tactile & polar systems, sound, WLAN and WiFi, RFID, ultra wideband, high sensitivity GNSS, pseudolites, other radio frequencies , inertial navigation, magnetic systems , and infrastructure systems|
|Technology||Common Measurement Methods||Advantages||Disadvantages|
|RFID||Proximity, RSS||Penetrate solid, non-metal objects; does not require LOS between RF transmitters and receivers .||The antenna affects the RF signal, the positioning coverage is small, the role of proximity lacks communications capabilities, cannot be integrated easily with other systems , RF communication is not inherently secure and consumes more power than IR devices .|
|UWB||ToA,TDOA||High accuracy positioning, even in the presence of severe multipath, effectively passes through walls, equipment, and any other obstacles; UWB will not interfere with existing RF systems if properly designed .||High cost of UWB equipment ; although UWB is less susceptible to interference relative to other technologies, it is still subject to interference caused by metallic materials .|
|Infrared||Proximity, Differential Phase-shift, AoA||Since IR signals cannot penetrate through walls, it is suitable for sensitive communication because it will not be accessible outside a room or a building .||Does not penetrate walls, therefore it is typically used in small spaces such as one room; IR communication is blocked by obstacles that block light which includes almost everything solid ; requires LOS between sender and receiver when using direct IR; One problem with diffuse infrared systems is their poor performance in locations with direct sunlight or fluorescent lighting because the infrared emissions (of the light sources) may interfere with the signals .|
|Ultrasonic||ToA, TDOA||Does not require LOS; do not interfere with electromagnetic waves ||Does not penetrate solid walls; there may be loss of signal because of obstruction; false signals because of reflections; and interference caused by high frequency sounds (e.g., keys jangling) .|
|Zigbee||RSS, Phase Shift Measurement||Its sensors require very little energy [25,27], and Low cost .||ZigBee which operates in unlicensed IS bands seems vulnerable to interference caused by a wide range of signal types (using the same frequency). This might disrupt radio communication ; it is suitable for networks in which conversation between two devices takes some few milliseconds which allows the transceiver to switch to sleep mode quickly .|
|WLAN||RSS||Use existing communication networks that may cover more than one building; the majority of devices available nowadays are equipped with WLAN connectivity; WLANs exist approximately in the majority of buildings; LOS is not required .||A major drawback of WLAN fingerprinting systems is the recalculation of the predefined signal strength map in case of changes in the environment (e.g., open/closed doors and the moving of furniture in offices). .|
|Cellular Based||RSS||No interference with devices that operate at the same frequency; the hardware of customary mobile phones can also be used .||Low reliability due to varying signal propagation conditions .|
|Bluetooth||Proximity, RSS||Does not require LOS between communicating devices ; a lighter standard and highly ubiquitous; it is also built into most smartphones, personal digital assistants, etc. .||The greater the number of cells, the smaller the size of each cell and hence better accuracy, but more cells increase the cost; requires some relatively expensive receiving cells; requires a host computer to locate the Bluetooth radio. Because the 2.4 GHz spectrum that Bluetooth is using is unlicensed, new uses for it are to be expected, and as the spectrum becomes more widely used; radio interference is more likely to occur .|
|Dead Reckoning||Tracking||Does not require additional hardware such as sensors||The DR calculates only an approximate position .|
|Image based technologies||Pattern recognition||They are relatively cheap compared with other technologies such as ultrasound and ultra wideband technologies .||Requires LOS, coverage is limited .|
|Pseudolites||RSS||They allow to extend the coverage area much farther to several kilometres and provide great flexibility in deployment that can be optimized for a particular application and they are also compatible with existing GPS receivers .||They are negatively affected by multipath, signal interference among pseudolites, weak time synchronization due to less accurate clocks within pseudolites and carrier phase ambiguities .|
|US||Unlicensed||3.1–10.6 GHz||Indoor only|
|Cannot be used in fixed outdoor environments or those linked to a fixed outdoor antenna|
|Europe||Unlicensed||3.1–10.6 GHz||Indoor only|
|Devices must be installed in road and rail vehicles, transmit power control (TPC) of a range 12 dB relative to the maximum allowed radiated power. The maximum mean e.i.r.p. spectral density must be −53.3 dBm/MHz when no TPC is in place|
|UK||Unlicensed||3.1–10.6 GHz||In harmony with European regulations|
|Outdoor but not attached to fixed installation, infrastructure or automotive vehicle (or railway vehicle)|
|The equipment must not cause interference to any wireless telegraphy|
|S. Korea||Unlicensed||3.1–10.2 GHz||Indoor only|
|It is similar to bands allocated by FCC and it uses a different emission mask for accommodating its spectrum environment|
|for UWB devices operating in the 3100 to 4200 MHz band, it requires use of detect and avoid technology|
|Japan||Unlicensed||3.4–10.25 GHz||Indoor only|
|In the 3400–4200 MHz band must incorporate interference mitigation techniques|
|In the 4200–4800 MHz band it can operate without mitigation techniques|
|Singapore||Unlicensed||3.4–9 GHz||Indoor only|
|The PSD limit shall be −41.3 dBm/MHz for devices equipped with interference mitigation techniques. For devices without mitigation techniques, the permissible PSD limit is −70 dBm/MHz|
|No.||Authors||Year||Accompanied Technology||Algorithm||Environment||More Details|
|1||Ch’oliz et al. ||2011||TOA||LOS, NLOS||Compared the performance of impulse radio (IR) UWB indoor tracking systems using different parametric and non-parametric algorithms such as weighted least square with multidimensional scaling (WLS-MDS), trilateration, least square with distance contraction (LS-DC), particle filter (PF), and extended kalman filter (EKF).|
|2||Guangliang Cheng ||2012||TOA||LOS, NLOS||Presented a new UWB-based personnel localization system for coal mines.|
|3||Fischer et al. ||2010||TOA||LOS, NLOS||Designed a new monolithic integrated IR-UWB transceiver chipset with a high-precision TOA measurement unit using two-way ranging and 8-PPM modulation.|
|4||Krishnan et al. ||2007||TDOA||NLOS||Used multi-cell implementation to cover large spaces, using Chan’s method to provide an accurate estimate of the mobile tag’s position within each cell. A heuristics-based approach was used to improve the accuracy at the boundaries.|
|5||Rowe et al. ||2013||TDOA||Presented a new multi-tag millimeter accuracy localization system that utilize digital sampling to enhance its accuracy.|
|6||Jiang et al. ||2010||GPS||AOA, TDOA||LOS, NLOS||Provided indoor/outdoor location tracking in a hospital environment by integrating UWB and GPS technologies in one system. Ubisense solutions are used to provide a UWB infrastructure and a system and to work as location platform with a standard bidirectional time division multiple access control channel.|
|7||Pittet et al. ||2008||MEMS||AOA, TDOA||Combined UWB positioning with micro electro mechanical sensors (MEMS) inertial sensors in an extended Kalman filter to improve positioning and navigation performance.|
|8||Shahi et al. ||2012||AOA, TDOA||LOS, NLOS||Developed a UWB positioning system for material and activity tracking in indoor construction projects and studied the effect of construction materials on performance.|
|9||Segura et al. ||2012||TOA, TDOA||LOS, NLOS||Developed a UWB navigation system for mobile robot (MR) in indoor environments. Synchronization by the receivers is not required since a centralized transmitter with TDMA is used. Also, an adaptive threshold crossing algorithm is used to improve TOA estimator resistance to noise and interference.|
|10||Cao and Li ||2012||AOA, TOA||LOS||Developed a new filter based algorithm to estimate the location and velocity of a target object in a real-time.|
|11||Mucchi et al. ||2010||AOA, TOA||LOS||Developed an UWB real-time positioning system using Ubisense UWB solutions to provide cinematic data that helps in monitoring the performance of a professional athlete, especially after a surgery.|
|12||Liu et al. ||2012||GPS||TDOA||LOS, NLOS||Developed an indoor and outdoor cooperative real-time positioning system for disaster aid missions by considering their requirements.|
|13||Kuhn et al. ||2011||TDMA, FPGA||TDOA||Designed a multi-tag access scheme for UWB positioning systems with millimeter range accuracy for surgical navigation which allows simultaneous tracking of up to 30 UWB tags.|
|14||Zhang et al. ||2010||FPGA||TDOA, RSS||Presented a new noncoherent UWB indoor positioning system with millimeter range accuracy.|
|15||Deissler et al. ||2012||MIMO||AOA||Presented a new indoor mapping system using a UWB radar and a simple mobile antenna array with one transmitter and two receivers to extract the round-trip-times. In order to cope with lack of infrastructure and prior knowledge of the surrounding environment, a Rao-Blackwellized particle filter was used for estimation algorithms.|
|16||Tuchler et al. ||2005||TOA||LOS||Evaluated location accuracy of a UWB positioning system in an indoor environment showing that short transmitted pulses improve the accuracy in a multi-path environment.|
|17||Jiang et al. ||2012||TOA, RSS||LOS, NLOS||Proposed a new circuit to fully integrate a non-coherent IR-UWB transceiver, which rectified the baseband pulses and provided the digitized data to the digital baseband of the receiver.|
|18||Tomé et al. ||2010||TOA||LOS||Presented a large-scale deployable UWB-based indoor positioning system that relies on a developed application specific integrated circuits (ASICs) to provide a cost-competitive solution for possible future commercialization.|
|19||Arias-de-Reyna and Mengali ||2013||TOA||LOS||Built a new UWB indoor positioning system which relies on a combination of the maximum likelihood principle with range error models (and special fingerprints) based on prior knowledge obtained from the service area.|
|20||Kilic et al. ||2013||TOA||LOS||Proposed a new device-free stationary person detection and ranging method using existing fixed UWB infrastructure via detecting small low-frequency variations caused by a person’s presence.|
|21||Mahfouz et al. ||2011||FPGA||TDOA||LOS, NLOS||Designed a millimeter range UWB indoor positioning system for medical applications using an adaptive leading-edge detection algorithm to distinguish LOS from NLOS in order to optimize the ranging algorithm accordingly.|
|22||McCracken et al. ||2013||CIR||RSS||NLOS||Presented a device free positioning system that uses UWB radios together with RSS sensors to localize and track people through a building.|
|23||Jiang et al. ||2013||TOA, TDOA||Presented a fast three dimensional node UWB positioning system that uses a modified propagator method for time delay estimation and a 3D Chan algorithm for position determination.|
|24||Yang et al. ||2013||TDOA||LOS||Proposed a space-time Bayesian compressed sensing (STBCS) algorithm for the compressed sensing UWB positioning system to decrease the ADC sampling rate and improve noise tolerance.|
|25||Mirza et al. ||2012||Ultrasound sensor, compass||AOA, TDOA||LOS||Proposed a UWB indoor positioning and navigation system using Ubisense technologies to help physically disabled people to perform their daily activities.|
|26||Ubisense ||2010||AOA, TDOA||LOS, NLOS||Developed a UWB real-time vehicle tracking system to help dispatch managers in assigning vehicle to particular track or parking place at a yard area.|
|27||Ubisense ||2011||AOA, TDOA||LOS, NLOS||Developed a UWB real-time bus tracking system that manages buses parking and driver assignments in the company’s yard area using Ubisense technology.|
|28||Ubisense ||2010||AOA, TDOA||LOS, NLOS||Developed a UWB real-time positioning and tracking system for personnel safety in the oil and gas industry where devices and sensors cannot hold or produce enough energy to create sparks and should meet safety requirements.|
|29||Manon kok et al. ||2015||Inertial sensor||TOA||LOS, NLOS||Designed a novel approach for UWB calibration which consider the possibility of UWB delays due to NLOS and multipath.|
|30||Harikrishnan Ravikrishnan ||2014||AOA, TDOA||LOS||Used a map of an assembly line to improve UWB position tracking for indoor experiments with eight Ubisense sensors where inAve are located inside a laboratory and three outside.|
|31||Bharadwaj et al. ||2014||CIR, Peak detection||TOA||LOS, NLOS||Used UWB to locate body-worn sensors with different configurations and shapes.|
|32||Zaric et al. ||2013||Optical localization algorithm||TOA||LOS||Implemented a trilateration algorithm to calculate positions.|
|33||Ruiqing Ye ||2012||TDOA||LOS||Proposed new method to reduce the effect of path overlap and outperforms other methods such as first peak and search subtract and readjust (SSR) methods.|
|34||Zwirello et al. ||2012||TDOA, AOA||LOS||Combined TDOA and AOA in localization systems to achieve best results.|
|35||Wang and Zhang ||2014||Joint Estimation||TOA, AOA||NLOS||Used sparse representation framework for joint estimation of TOA and AOA.|
|36||Muller et al. ||2014||TOA||LOS, NLOS||Compared generalised Gaussian mixtures (GGM) with extended Kalman filter in nvironment with uncertainty.|
|37||Leitinger et al. ||2014||RSS||NLOS||Combined maximum likelihood estimator with floor plan information to improve accuracy.|
|38||Garcia et al. ||2015||TDOA||LOS, NLOS||Applied extended Kalman filter to improve accuracy in a highly complex indoor scenario.|
|39||Perrat et al. ||2015||TOA, TDOA||LOS||Used Ubisense for real-time positioning of wheelchair athletics.|
|Position Estimation||The intersection of several pairs of angle direction lines||Time taken by the signal to go from the target node to several reference nodes||The delta in time between the signal’s arrival at multiple reference nodes||The received signals strength from several reference nodes at the target node|
|The distance is directly proportional to the propagation time||The time differences are mapped to multiple intersected hyperbolas||The distance is inversely proportional to the signal strength|
|2D space||At least two reference nodes||At least three reference nodes||At least three reference nodes||At least three reference nodes|
|3D space||At least three reference nodes||At least four reference nodes||At least four reference nodes||At least four reference nodes|
|Synchronization||Lower requirement in terms of clock precision and synchronization||All transmitters and receivers in the system have to be precisely synchronized||Only the reference nodes need to be synchronized||Not required|
|Difficult and costly|
|LOS vs NLOS||Require a clear line-of-sight (LOS) between sender and receiver||Prefer LOS to reduce multipath effects|
|Multi-Path effects change phase of a signal and cause large position error||Great negatively affected by existence of obstacles and walls|
|Issues||Small errors in angle measurement will negatively impact accuracy||Relative clock drift between sender and receiver||Lower accuracy than TOA with the same system geometry||Sensitive to channel inconsistency|
|Require costly and large dimensions of antenna arrays||Require short distances between nodes|
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