Wireless Localization using RSSI

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Wireless Localization using RSSI

• Eryk Druszkiewicz and Mike Ciak

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Beacon 1
Base Mote attached to PC
Sends a notification that it is done
This process repeats for each power level the
amount of times the request asked for
Central
Beacon 2
Beacon 3
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Software
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Triangulation

• Characterized the RSSI versus distance
• Collected RSSI values over a range of 20.4 meters
  with 60 cm divisions for 31 different transmit
  powers
• Analyzed the resulting 1054 files of data to
  determine 93 best fit formulas, one for each
  transmit power for each beacon
• Cycle through transmit powers and determine most
  likely distance from each transmit power and
  beacons formula
• Average possible distances to get most likely
  distance
• Found the place where those circles intersected
  as the most likely area that the central mote
  would be

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Transmit Power of 4
Distance ((RSSI 32657.8)/ 32951.2) - 2579.1
Distance ((RSSI 42496.6)/ 42804.9) -2918.4
Distance ((RSSI 18701.7)/ 18996.2) -1485.1
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Transmit Power of 15
Distance ((RSSI 2016.5)/ 2339.5)-152.9
Distance ((RSSI 314.6)/ 657.1)-34
Distance ((RSSI 2016.5)/ 21144.7) -1497.9
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Transmit Power of 27
Distance ((RSSI 2591)/ 2920.7) -189.8
Distance ((RSSI 238.9)/ 593.9) -28.5
Distance ((RSSI 23786.7)/ 24113.6) -1703
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Results
3m
Be2
Be3
Central
3m
Be1
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Problems of the approach

• The antennas on the motes were very bad, and
  often a very different RSSI value would result if
  the transmitting mote was oriented in a different
  way
• We attached better antennas onto the motes which
  greatly increased the reliability of the signal

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Problems of the Approach

• First we tried waiting for the central mote to
  hear the third beacon to have it retransmit at a
  different transmit power, however if the transmit
  power was too low beacon 3 would not fire and
  thus the central mote would not retransmit
• Changed it so that the central mote waits 4 ms
  after when the third mote should have fired
  (roughly 22 ms)
• Multipath issues prevented reliable use in an
  indoor environment
• Atmospheric conditions affect characterization of
  the RSSI values
• The standard deviation between samples of same
  transmit power are so small that atmospheric
  conditions play one of the largest roles in the
  incorrect data
• One possible solution would be to use the
  humidity and temperature sensors on the motes to
  adjust the formulas according to the atmospheric
  conditions