Indoor Localization II Location Systems. Petteri Nurmi Autumn 2015

Transkriptio

1 Indoor Localization II Location Systems Petteri Nurmi Autumn

2 Learning Objectives What are the main dimensions for categorizing location systems? Which are main error sources for indoor localization? How indoor location systems operate? Proximity sensing techniques (Ultra)sound, radio wave techniques Fingerprinting: WiFi and Magnetic Pedestrian Dead Reckoning

3 Location Systems System that provides measurements that can be used to determine the position of an entity Possible dimensions for characterizing location systems: Location representation: absolute, relative, symbolic Scale: worldwide, indoors, outdoors Location system type Measurement Error sources

4 Location Systems - Location System Type Active or passive Determines whether client transmits anything or not Client-based Client is responsible for estimating its own position without assistance from network infrastructure Infrastructure-based Infrastructure is responsible for estimating the location of the client Infrastructure-assisted Client and infrastructure both participate in determining the location

5 Location Systems - Location System Type Active or passive Determines whether client transmits anything or not Client-based Client is responsible for estimating its own position without assistance from network infrastructure Infrastructure-based Infrastructure is responsible for estimating the location of the client Infrastructure-assisted Client and infrastructure both participate in determining the location

6 Location Systems - Evaluation Criteria Accuracy: difference between estimate location and true location Kilometer, meter or centimeter level accuracy Consistency: how often a reported position accuracy can be obtained Typically reported in terms of percentiles For example, 95-percentile of 12cm means that system error is within 12cm 95% of times Latency Time period between a position request and delivery of position fix

7 Location Systems - Evaluation Criteria Overhead Signaling overhead: additional burden on communication infrastructure Computation overhead: burden on client/infrastructure resulting from necessary calculations Power overhead: how much power is required from the terminal Roll-out and operating cost Roll-out costs refer to expenditure required to make the system operational Operating costs refer to expenditure required to maintain the system operational

8 Location Systems Error Sources As discussed during previous lecture, measurements provided by location systems are inaccurate Noise in measurements causes errors in distance / angle values Geometry of reference points amplifies effects of noise Errors in coordinates of reference points can cause further errors Dilution of Precision (DoP) characterizes how range and geometry affect position estimates

9 Error Sources Geometry Reference point geometry has a strong influence on positioning accuracy When reference points orthogonal, the size of the region of uncertainty smallest As reference points move closer to each other, size of the region of uncertainty increases

10 Error Sources Time Errors Sound waves (e.g., ultrasound positioning) propagate at speeds between 290 and 360 m/s Error of 10ms causes a distance error of 3 meters Radio signals travel approximately at the speed of light ( m/s) Error of 1ms causes 300,000m estimation error Time synchronization critical for positioning! If sufficiently many reference points which share same time, time offset can be treated as unknown and solved Used in satellite positioning systems

11 Error Sources Multipath Propagation Source: wiki/multipath_propaga tion Propagation phenomenon caused by signal reaching receiver along various paths Reflection: when wavelength of signal much shorter than size of obstacles, signals reflect Diffraction: bending of a signal as it hits on irregularities of an obstacle Scattering: signal multiplied at obstacles whose size is less or the same magnitude as the signal s wavelength Reflection Diffraction Scattering

12 Location Systems - Measurement Refers to the signal and type of measurement that is used for position estimation Types of signal: radio, infrared, ultrasound Measurement types ID: Identifier of a radio beacon RSS: Received signal strength of a radio beacon Time: Time of flight or time difference or arrival Angle: Orientation between transmitter and receiver

13 Location Systems Proximity Sensing First indoor positioning systems were based on proximity, i.e., closeness of a reference point Essentially a variation of trilateration where only a single reference point can be observed Uncertainty determined by the range of the transmitters The higher the positioning accuracy requirement, the higher the cost for infrastructure Limitations in terms of Range Latency Receiving angle

14 Location Systems ActiveBadge Source: s/index.html One of the first indoor location tracking systems Introduced by Olivetti Research Laboratory (Cambridge, UK) in 1992 Badge transmits IR signal every seconds Receivers that detected the signal store information about badge location in a central database Location of receivers known, position of client can be estimated from badge observations Designed to operate up to 6m away from a sensor However, infrared generally weak and are only slightly reflected and scattered è line-of-sight usually needed

15 Location Systems Wireless Indoor Positioning System Variant of ActiveBadge, position estimated on the terminal instead of the network infrastructure Transmitters installed in the infrastructure When badge receives signal from transmitter, it sends information using WLAN to a central server

16 Proximity Sensing Other Techniques Radio Frequency Identification (RFID) Radio signals that are exchanged between a reader and tags (or transponders) Active tags: use own power supply Passive tags: draw energy from signals emitted by reader Essentially a proximity sensing technique Bluetooth Wireless technology for transmitting data over short distances Proximity sensing or trilateration can be used for position estimation Main issue latency due to Bluetooth scanning and difficulty in obtaining suitable transmitters

17 Proximity Sensing Beacon Scan Request Instead of requiring dedicated badges, recently several systems that identify mobile devices Overall principle same as in Active Badge Devices detected from beacon broadcast messages, which are performed while scanning for devices Position estimated as the location within infrastructure where scan observed ibeacon: Bluetooth Low Energy (BLE) WalkBase: WiFi

18 ibeacon

19 Walkbase

20 Estimating Distances Recall (from previous lecture) that trilateration can be used to estimate position with distance measurements Two reference points required Four main methods (3 time, 1 signal-based): Time of arrival: travel time from transmitter to receiver requires synchronization between them Time difference of arrival: difference in arrival times between multiple receivers Requires synchronization between receivers Round-trip time: time from transmitter to receiver and back (or vice versa) Signal strength: Propagation modeling based on signal decay

21 Location Systems - Ultrasound Based on sound signals operating at frequencies higher than 20kHZ Speed of sound fast, but slower than speed of radio signal propagation è less prone to timing/synchronization errors Better penetration through walls and other obstacles than radio signals Positioning can be based either on distance (trilateration) or angular direction (triangulation) Main drawback need for special equipment both on the infrastructure side and on the client

22 Source: esearch/dtg/research/wiki /BatSystem/BatPhotos Location Systems Ultrasound I: ActiveBat Ultrasonic location tracking system Receivers dispersed in environment Tags emit short ultrasound pulses Position estimated using trilateration Receivers use radio frequency to cue for badges When badge receivers cue, it emits an ultrasound pulse Receiver uses time difference between sending the cue and receiving the ultrasound pulse to estimate distance Acoustic signals travel significantly slower than radio signals è delay from the polling signal negligible

23 Location Systems Ultrasound II: Cricket Source: ojects/cricket/ Beacons affixed to the environment emit RF message together with ultrasound pulse Ultrasound pulse used to estimate distance from beacons RF messages contain information about beacon positions Trilateration can be used to estimate the position of the client given a set of beacon observations Ultrasound does not penetrate obstacles è lineof-sight required Trilateration è at least three beacons need to be observed

24 Location Systems Ultrasound III: Relate Source: Source: ac.uk/software/ Peer-to-peer ultrasound positioning sensing system that provides relative position information Estimates distance and angle between devices Non-linear regression used to estimate relative 2D positions of objects Ad hoc radio communications used to exchange information between objects Provides also time synchronization Enables refining estimates of objects

25 Location Systems: Ultra-wide band Low-energy, high-bandwidth, short-range Wide-band = uses large portion of radio spectrum (> 500 MHz) In positioning, between 3.1 and 10.6 GHz (regulated) Very high accuracy, but short range implies high installation costs Positioning can be based either on distance (trilateration) or angular direction (triangulation) Distance: time of arrival (TOA), time difference of arrival (TDOA), round trip time (RRT), propagation modeling

26 Ubisense (Ultrawide Band UWB)

27 Estimating Angular Directions Recall (from previous lecture) that triangulation can be used to estimate position with angular measurements Two reference points required Two main methods for estimating angles of arrival Beamforming: fixed number of beams used to scan plane, angle corresponds to beam with highest power Multiarray systems: multiple receivers organized into an array and used to estimate angle Two main signal sources: Acoustic: ultrasound, speech, or other audible sounds Radio signal: delays in observed signal patterns

28 Estimating Angular Directions: Multiarray Systems Time delay between receivers given by d = a(p i P 0 ) / c a is direction of arrival for the signal P i and P 0 are the locations of two receivers c is propagation speed Relative time delay can be estimated from (discrete) Fourier transform of the delayed signal Classical methods: least squares, Bartlett, Subspace methods: Multiple Signal Classification (MUSIC) Performance depends on SNR (signal-to-noise ratio) Highly varying computational complexity between different approaches

29 Example: Quuppa HAIP (High Accuracy Indoor Positioning) Triangulation based on single reference point (2D) Ceiling of indoor space mounted with locators Angular direction of tags estimated within the locator If the location and height of the locator, and an approximate height of the tag are known, 2D position can be estimated 3D position requires two observable locators Submeter accuracy: typically 0.5 1m Depends on density and configuration of locators Works best in open ceiling areas

30 Quuppa

31 Location Systems: Fingerprinting Recall that fingerprinting refers to techniques that exploit spatial variations in signal characteristics for positioning Calibration: collect measurements together with information about their locations, construct a radio map Estimation: given new measurements, estimate their most likely location using the radio map Two main methods: Deterministic: position determined based on distances between current measurement and those stored in radio map Typically Euclidean distance Probabilistic: position determined based on probabilistic model

32 Location Systems: WiFi Fingerprinting The most common signal source for (location) fingerprinting Radar: knn-based fingerprinting using a full index Horus: probabilistic (Gaussian) signal model Fingerprints constructed from WiFi scans Each scan contains information about available access points and their signal strengths Meter-level accuracy: Offices / closed spaces: 1-3m, open areas 5-10m Widely also used as recalibration method in PDR

33 Ekahau

34 Magnetometer Sensor that measures the strength and direction of magnetic field in the current environment Many ways to measure the strength of the field Most common ways (magnetoresistance and Hall effect) measure changes in electric properties Sensitivity Determines the maximal possible accuracy that can be achieved with the sensor, e.g., 0.5 μt 3 Range: should be at least ±1000 μt Output: Three dimensional vector M = [M x, M y, M z ]

35 Magnetometer Noise: Hard and Soft Iron Noise Theoretically, magnetic field measurements in a single location should form a perfect circle as device is rotated Permanently magnetized ferromagnetic components cause a so-called hard iron offset on magnetometers Magnets, speakers, or any other ferromagnetic objects Results in an additive bias in the magnetometer, i.e., the centre of the circle shifts Soft iron Caused by materials that distort the magnetic field, but that do not generate their own field Depends on the orientation of the material relative to the sensor and the field Perturbs the circle into an ellipse

36 Magnetic Fingerprinting Fingerprints correspond to vectors characterizing local magnetic distortions Typically either the raw measurements (i.e., vector M) or a normalized vector M = M / M Normalized vector rotation-invariant, i.e., measurements do not depend on orientation of device Raw measurements better at separating between true variations and the actual magnetic field Alternatively, measurements can be projected to a reference frame (see Mobile Sensing course) first Otherwise idea similar to WiFi (and other) fingerprinting solutions

37 Indoor Atlas

38 Location Systems: Pedestrian Dead Reckoning Source: org/wiki/dead_rec koning Recall that dead (or deduced) reckoning refers to extrapolation of position from last known position Requires information about Direction of motion Distance travelled since last known position Pedestrian Dead Reckoning Implementation of dead reckoning for pedestrian motion Distance travelled estimated by analyzing walking patterns step counting + step length model Orientation estimated using sensor fusion Attitude estimation (reference frame alignment) using accelerometer, gyroscope and magnetometer For details, please see materials of the Mobile Sensing course

39 PDR Example

40 Other Location Systems Source: washington.edu/wiki/ PLP FM Radio FM signals are radio waves è propagation models or fingerprinting can be used to provide location Pressure floors Load sensors embedded within floor tiles PowerLine positioning Specialized modules emit signals along powerlines which tags carried by users sense Airbus positioning Determines room transitions and gross movement by sensing differential air pressure in a home Camera tracking