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projekt User location estimation by means of WLAN Carl-Friedrich-Gauss-Str. 2 47475 Kamp-Lintfort Germany Dennis Vredeveld IMST GmbH IMST ipos
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projekt 2 User location estimation by means of WLAN / DV Contents Location-aware applications Indoor positioning: IMST ipos Experimental testbed Deterministic and probabilistic approach Software design Summary Outlook
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projekt 3 User location estimation by means of WLAN / DV Location-aware Applications Locate people and nearby resources Product location information Example: Metro Future Store, Rheinberg Tracking Who/what is close? Navigation How do I get there?
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projekt 4 User location estimation by means of WLAN / DV = AP Experimental testbed IMST 1st floor StandardIEEE 802.11b # of AP‘s7 Dimensions69 x 22 m OSLinux/Windows Hardwarehp iPAQ Lucent ORiNOCO IMST ipos
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projekt 5 User location estimation by means of WLAN / DV Experimental testbed (2) Example for 1 AP Colour indicates measured average signal strength Calibrated radio map Orientation matters
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projekt 6 User location estimation by means of WLAN / DV ipos WLAN overview Determine signal strength from beacons received from „visible“ access points Average of k Nearest Neighbours in Signal Space (k- NNSS) Deterministic Data base contains averaged signal strength values Determine smallest Euclidean distance Probabilistic Data base contains histograms of signal strengths Determine largest joint probability Postprocessing (averaging, etc)
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projekt 7 User location estimation by means of WLAN / DV Simplified example 3 visible AP‘s Only 1 NNSS used Table Room 117! Signal Strength Measurements WLAN IEEE 802.11b beacon
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projekt 8 User location estimation by means of WLAN / DV Deterministic approach Data base with measured average values for each calibrated location: ss 1, ss 2,… ss n Average k NN to obtain location estimation Mobile station with real time signal strength measurements from n Access Points: ss 1 ’,… ss n ’ Nearest neighbours are calibrated values with minimal Euclidean distance in signal space:
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projekt 9 User location estimation by means of WLAN / DV Probabilistic approach Data base with histograms instead of averages with Estimated joint probability: Assume AP‘s are independent:
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projekt 10 User location estimation by means of WLAN / DV ipos system design wireless techn. dependent independent of wireless techn. Location estimation Display location Powerpoint GUI Building map HTML Control Interface Postprocessing / filtering Floorplan checker Sliding window average Location profile Kalman filtering Trajectory prediction... Data Distribution WLAN module Preprocessing Raw WLAN data CE1 LCF1 LCF = Location Calculation Filter Interface New technology module Raw... data Preprocessing CE1 LCF1 Raw UWB data Preprocessing CE1 LCF1 UWB module
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projekt 11 User location estimation by means of WLAN / DV Technology dependent Technology independent Location calculation filter Location Estimation Raw data Data Collection Raw data Store3 Store1 Store2 Preprocessing/ Filtering Raw data A1A3 A2‘A1‘ Postprocessing Location Estimation P1 P2P3 P2‘P1‘ P4 Data Distribution Location Estimation Dist3 Dist2 Dist1 ipos data processing
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projekt 12 User location estimation by means of WLAN / DV Example: user tracking
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projekt 13 User location estimation by means of WLAN / DV Summary Use existing WLAN infrastructure Find best match of AP beacons‘ signal strength measurements to a calibrated radio map Realtime positioning with average error of 1-3 meter in testbed
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projekt 14 User location estimation by means of WLAN / DV Outlook Identify and resolve error sources Influence of environmental changes (number of persons, etc) Differences between WLAN hardware Design and implement ipos-software Research into new data sources and calculation algorithms
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projekt 15 User location estimation by means of WLAN / DV Questions?
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projekt 16 User location estimation by means of WLAN / DV Thank you for your attention! Vredeveld@imst.de ✉
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