Location Estimation Media, Location Estimation Media, Algorithms and Systems, Algorithms and Systems, Location Technologies Location Technologies Gábor Nyíri 06/04/2005 1
Agenda Agenda � Introduction � Taxonomy of Location � Location Estimation Media � Location Estimation Algorithms � Location Estimation Systems � Summary 06/04/2005 2
Introduction Introduction � Wired – wireless – Location is constantly changing – „A key distinguishing feature of mobile computing is the ability to detect, react to and make use of changing environmental conditions to provide users with a better seamless and intuitive experience” � Revenue: 2000: $1 billion 2006: over $40 billion � Location-based application (LBA) – Applications capable of finding the geographical location of an object and providing services based on this location information – NOT only in mobile communication systems – Examples: • E-911 • Road assistance • Geotargeting adverisement • Fleet tracking … 06/04/2005 3
LBA - - Examples Examples LBA 06/04/2005 4
General framework to support LBA’s General framework to support LBA’s Location Location Measurement Location Estimation Sensor Estimation Format Infrastructure Algorithm Transformation Location Estimation System Presentation Location- Requirements, Preferences Based Applications 06/04/2005 5
Taxonomy of Location Taxonomy of Location � Physical and Symbolic Location – Physical location: • uniquely identifies a point on a 2D map of the Earth eg.:degree/min/sec(DMS) • (in 3D also altitude is required) • Helsinki, Latitude: 60°10´N Longitude 25°0´E – Symbolic location: • In the way of natural-language • Like: at home, in the bed, on the train… • Not always needed the precise physical location eg.:home security sys. • Coarse – Can be mapped to each other with help from a location information database • Resolution: in a room ~ 10m 06/04/2005 6
Taxonomy of Location Taxonomy of Location � Absolute and Relative Location – Absolute location • uses a shared reference grid like DMS – Relative Location • Depends on its own frame of reference – With the help of relative location absolute location can be computed 06/04/2005 7
Location Estimation Media Media Location Estimation � Radiofrequency: – widely used: cellular phone systems, satellite communication systems, WLAN systems – Most estimation algorithms depends on the existence of a line of sight – Accuracy: • Dominant source of error: Multipath propagation: line of sight (LOS) + NLOS – Reflection & Diffraction & Scattering • Multipath fading – Rapid variation in signal strength – Received signal strenght (RSS) • Delay spread – Signal on NLOS paths are delayed – act as noise – Mainly outdoors 06/04/2005 8
Location Estimation Media Media Location Estimation Infrared (IR) � – Interference with ambient light source (incandescent sources, fluorescent lighting, sunlight) – Mainly used for object detection, sensing and tracking – Every object emit unique IR radiation -> fingerprint database • Advantage: no transmitter required • Disadvantage: very sensitive IR receivers are required (expensive) distinguishing same type of objects? • Not suitable for general-purpose location estimation services – With limited transmission range it is cheap and can be integrated to large-scale sensor networks 06/04/2005 9
Location Estimation Media Media Location Estimation � Ultrasound – 20-100kHz – Speed of sound in air: v=331+0.6*T (at 20C 343m/s) – More accurate than systems based on RF and IR – Measurement errors: like with RF + speed changes (humidity & temp) – Sensitive to in-band noise – Inexpensive – piezoelectric ceramic 06/04/2005 10
Location Estimation Algorithms Algorithms Location Estimation Triangulation � – Location is estimated relative to some known framework – Lateration & angulation – Time of Arrival (TOA): • At least 3 base station measures the time of arrival • Distance can be computed, target at the intersection of circles – Time Difference of Arrival (TDOA): • The same but with hyperbolas • Two pair of measurement • Eliminates the clock offset of the estimated object – Angle of Arrival (AOA): • Directional antennas or antenna arrays are required 06/04/2005 11
Location Estimation Algorithms Location Estimation Algorithms Scene analysis � First collects features/fingerprints not directly related to – geometric information Than matching with the closest a priori location – fingerprints Eg: – smart floor: pressure sensors in the floor (Georgia IT) • 3D cameras (Easy Living by Microsoft) • RF-based scene analysis?! – No need for special infrastructure, wireless infrastructure is • already deployed indoors (WLAN, bluetooth) Two main characteristics: • Signal strength (SS), Signal-to-noise ratio (SNR) – Cannot be used to derive accurate location information – 06/04/2005 12 Rather match SS entries in a database –
Location Estimation Algorithms Location Estimation Algorithms � Scene analysis – 2 General Framework of scene analysis: – • Profiling – Off line: The area is devided into small pieces, containing multiple observation points – Sampling of RF parameters are collected -> stored in a database after postprocessing – This procedure has to be repeated: • After the building layout is changed • Samples has to be collected at different times of the day – Increasing the number of observation points leads to larger database, and after a threshold no much influence • Matching – Real- time measaurement is obtained – Comparing the measurements with the entries of the database • Estimation 06/04/2005 13 – Location estimation based on the match(es) – Kind of averaging
Location Estimation Systems Location Estimation Systems � Indoor Location Estimation Systems – RADAR (Microsoft Research) • WLAN based scene analysis • 3APs, floor with 50rooms • SS & SNR measured by APs • SS is orientation dependent (multiple measurements are collected) – BAT (AT&T) • Central RF basestation + matrix of receivers • Measured objects equipped with RF receiver and ultrasonic transmitter + unique ID • Base station broadcasts ID, in respose an immediate ultrasonic pulse from the owner of the ID • Also the neighbours can measure their distance from the measured object 06/04/2005 14
Location Estimation Systems Location Estimation Systems � Indoor Location Estimation Systems – 2 – Cricket (MIT) • Privacy! = Location estimation on user side • RF + ultasonic transmitters – Active Badge • Infrared based • One IR sensor per room • Employees are equipped with a badge that sends out IR beacons with a unique ID every 15 secs 06/04/2005 15
Positioning Positioning Method Accuracy Deployment / Limitations System Precision Scale E911 (Cellular Base station 50-300m Density of cellular Only where cell Networks: GSM, triangulation infrastructure coverage exists etc.) GPS RF time-of-flight 1-5m 24 satellites Not indoors lateration worldwide Cricket (MIT) RF and ultrasound 4ft 1 beacon per 16 Ceiling beacon ultrasound; grid required; ultrasound; proximity lateration receiver proximity computation lateration RADAR (Microsoft Cell-id (802.11 RF 3-4m 3+ bases per floor RADAR Research) triangulation) & (Microsoft scene analysis Research) SmartLOCUS (HP synchronized RF 2-15**cm** Nodes placed Labs) and ultrasound every 2-15 m differential time of flight Active Bats (AT&T Cell-id (Ultrasound 9cm 1 base per 10 sq Ceiling sensor Cambridge) time-of-flight m grid required lateration) UbiTags Time-of-flight + 15cm 2-4 sensors per (UbiSense) angle-of-arrival cell (100-1000m); 1 UbiTag per object
Location Estimation Systems Location Estimation Systems � Outdoor Location Estimation Systems – GPS: • 24 satellites, 5 monitor stations, 3 ground antennas, master control station • 2 levels: precise positioning service(PPS) and standard positioning service (SPS) • PPS is originally for military purposes from 1 st May 2000 it is available for civil use • Satellites are broadcasting their positions • 4 satellites are required at the same time for 3D positioning • Differential GPS accuracy can be higher ~1m • 20mm is also achievable ~ $15.000 • Assisted GPS: reduces search time from minutes to seconds special HW/SW 06/04/2005 17
Location Estimation Systems Location Estimation Systems � Outdoor Location Estimation Systems – Cellular-based systems: • Since 1996 in the US operators must provide E-911 services • This information can be used for a lot more purposes • Cell location is known during a call – Cell ID • Between calls location information is updated in the network • If the cell is known, location can be measured (TOA,TDOA) – This can require add-ons, more expensive than cell id determination • Time synchronization nedded among basestations 06/04/2005 18
Recommend
More recommend
