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Outline Location sensing techniques Location systems properties Existing systems overview WiFi localization techniques WPI precision personnel locator.

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Presentation on theme: "Outline Location sensing techniques Location systems properties Existing systems overview WiFi localization techniques WPI precision personnel locator."— Presentation transcript:

1 Outline Location sensing techniques Location systems properties Existing systems overview WiFi localization techniques WPI precision personnel locator

2 Location sensing techniques 1. Triangulation Lateration Direct Time of flight Attenuation Angulation 2. Scene analysis 3. Proximity (ex. CC, RFID tags,…)

3 Location systems properties Physical Vs symbolic location Absolute Vs relative location Accuracy (mt) and precision (%) Localized Vs centralized computation Cost Scale (object located by certain amount of infrastructure) Limitations

4 LBS – Location Based Services GPS Satellite-based Wireless Network-based WiFi Inertial GSM Existing infrastructure Ad-hoc hw ultrasounds IR UWB

5 TechnologyTechniqueAccuracy/ Precision CostLimits GPSMicrowave time- of-flight lateration 5-15 mt (95- 99%) LowNot indoors or in densely built areas GSM (E911)Lateration or Angulation or Scene analysis 150-300 mt (95%) LowCell coverage Wi-Fi (RADAR, Ekahau PS) Triangulation/ Scene analysis 3-4 mt (50%) LowCalibration / fingerprinting cost Existing infrastructure

6 TechnologyTechniqueAccuracy/ Precision CostLimits IR (Active Badge) Proximity5-15 mt (95- 99%) HighSunlight interference, high base station cost Ultrasounds (Active Bat) Time-of-flight lateration 9 cm (95%) HighHigh base station cost MC-UWB (WPI PPL) Lateration0.5 mt (99%) HighRequires outdoor base units, high hw costs Inertial (WPI PPL) Local computation of location (Enhanced ?)LowFast drifting: enhancer for existing systems? Ad hoc infrastructure

7 WiFi RSSI lateration RSSI-based distance estimation from at least 3 base stations / access points Simple intersection computation Indoor problems Distance attenuation Penetration losses (walls, windows,...) Reflection and multipath  Complex propagation modeling

8 WiFi RSSI fingerprinting 1. Training phase: map of RSSI measured at reference points 2. Online phase: comparation of collected RSSI with the training data NN algorithms Probabilistic algorithms Neural networks  Training phase to be repeated if APs are moved  Slightly better accuracy than in the lateration approach

9 WiFi TOA lateration 1. Estimate TOA assuming clock synchronization 2. Calculate distance and then trilaterate  Needs additional hw for clock accuracy

10 WPI Precision Personnel Locator Locators 3 or more reference units (deployed outside the building) Base Station (trilateration algorithm)

11 WPI Precision Personnel Locator Multicarrier Ultra-wide band signal between locators and reference stations TDOA recovery from phase shift (at least 2 carriers required) Multicarrier = multipath immunity Low bandwidth consumption Improvement with inertial sensors?


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