DATAMAN. VOR Base Stations for Indoor Positioning. Dragoş Niculescu. MOBILE COMPUTING LABORATORY

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1 DATAMAN MOBILE COMPUTING LABOATOY VO Base Stations for Indoor 80. Positioning Dragoş Niculescu

2 indoor positioning no GPS indoors! classifications of existing systems infrastructure existing 80. base stations specialized beacons measurement medium F (radio frequency) infrared ultrasound actual positioning method triangulation trilateration signal strength map Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

3 positioning basics. range based - trilateration. angle based - triangulation 3. signal strength map - nearest neighbor, Bayes Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

4 trilateration N α N A M β B γ N C (x M x A ) + (y M y A ) = MA (x M x B ) + (y M y B ) = MB solve for (x M, y M ) (x M x C ) + (y M y C ) = MC MA, MB, MC are affected by errors several methods available Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

5 example: Cricket (MIT) mobile pros: cons: measures ranges to ceiling beacons TDOA between F and ultrasound triangulates good accuracy.3m extensive infrastructure line of sight to the beacons Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

6 triangulation N α N A M β B γ N C (x M x A ) sin α = (y M y A ) cos α (x M x B ) sin β = (y M y B ) cos β solve for (x M, y M ) (x M x C ) sin γ = (y M y C ) cos γ α, β, γ -affected by errors (Gaussian) several methods available Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

7 signal strength map build SS map: for each point, measure SS to all 5 BS query: measure SS to 5 BS best match in the map Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

8 example: ADA (Microsoft) use nearest neighbor to decide for the best match pros: cons: no additional infrastructure requires high resolution sampling people, furniture, BS position affect the SS map median position error 3m Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

9 example: LANDMAC (MSU) replaces training points with FID tags BS with FID readers mobile uses an FID tag nearest neighbor, etc. pros: cons: no remapping updates map on the fly additional infrastructure (FID) many readers, tags Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

10 VOBA - VO BAse stations goals: no signal strength map less infrastructure move complexity to the 80. base station use: angles ranges angles and ranges Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

VOBA prototype 90 I receiver I sender 50 0 60 30 antenna 80 0 30 0 0 3 0 0 80.

11 VOBA prototype 90 I receiver I sender antenna card prototype directional antenna pattern Dragoş Niculescu VO Base Stations for Indoor 80. Positioning

12 basic measurements ents signal strength [dbm] mean SS discrete angles angle distribution range SS(α) Dragoş Niculescu VO Base Stations for Indoor 80. Positioning 3

13 experiments frag replacements 3 3 measurement points 5 + base stations N/E/S/W measurements of 3- revolutions each Dragoş Niculescu VO Base Stations for Indoor 80. Positioning 3

14 best peak distribution 0.6 histogram of number of peaks 0.6 Histogram of SS rank mean =.5 peaks of best peak ents 3 0 probability 60% 30% number of peaks peak rank.5 peaks on average best peak is first/second 90% of the time Dragoş Niculescu VO Base Stations for Indoor 80. Positioning 3

15 other peak distribution ments 3 true direction 3 true direction 5% 33% other peaks point away from true direction Dragoş Niculescu VO Base Stations for Indoor 80. Positioning 3

16 discrete angle positioning replacements 3 cumulative probability using best angle using first two angles angle distribution error in meters 3.5m median position error 3m if we knew the best peak Dragoş Niculescu VO Base Stations for Indoor 80. Positioning 3

17 ln ents triangulation analysis ln σ a simulation lower bound ln simulation lower bound σ a σ a simulation lower bound ln V ar[x] > σ a ln m V ar[x] - standard dev. of positioning error - density of basestations / m to improve positioning:. decrease measurement error σ a. use more basestations 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning σa

18 ln quantized angles ents 3 ln σ a o x78 55x908 8x x79 776x ln 3 σ a o + + 8x78 55x908 8x x79 776x measurements rounded to the nearest 5 simulation 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning σa

19 ln quantized angles replacements 3 ln cumulative probability σ a best angle (non quantized) quantization 5 quantization.5 quantization error in meters little degradation for 6 directions (.5 ) 8 directions (5 ) 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning σa

20 ln angle distribution placements 3 ln σ a 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning σa

21 ln range inference open space attenuation: d(ss) SS[dBm] = SS 0 [dbm] log 0 ( d d 0 ) n obtained through fitting known to be unreliable we obtain it from integration of SS(α) 5-fold cross validation corridor basestations - waveguide effect median range error.8m 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning σa

22 ln positioning w. ranges frag replacements 3 ln cumulative probability σ a error in meters trilateration 5 base stations median position error.5m 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning σa

23 ln ranges and angles frag replacements ln 3 σ a α N A M β N B γ N C x M = x A + MA cos α = x B + MB cos β = x C + MC cos γ y M = y A + MA sin α = y B + MB sin β = y C + MC sin γ one base station is theoretically enough α, β, γ, MA, MB, MC - affected by errors 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning σa

24 ln position uncertainty ln σ r σ y σ a A σ a r M σ x approximate uncertainty as an ellipse error ellipse increases with distance σ a = 0. radians σ r = 0.r 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning σa

25 ln σ a uncertainty w. ranges & angles Sfrag replacements how to combine 3 several readings? Kalman filter. ln ρ α BS σ a BS BS 3 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning α ρ BS BS BS3

26 ln σ a positioning w. ranges & angles 3 ln σ a cumulative probability α ρ BS BS BS BS 5 BS 3 BS 0 BS error in meters more base stations better positions.m median position error (all 7 BS) 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning α ρ BS BS BS3

27 ln σ a discussion triangulation with large outliers use more than two angles? no correlation between angle error and distance angle error and SS corridors waveguides revolving signal at the mobile? data performance? 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning α ρ BS BS BS3

28 ln σ a summary VOBA = VO base station complexity into the base station less infrastructure no SS map revolving basestation measures SS(α) to derive discrete angles angle distributions ranges works with quantized angles as well can achieve.m - m median error 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning α ρ BS BS BS3

29 ln σ a index indoor positioning trilateration Cricket triangulation SS map ADA LANDMAC VO BAse station prototype basic measurements experiment setup peak distribution angle positioning discrete angles quantized angles angle distributions range positioning range+angle pos. uncertainty performance discussion summary 3 Dragoş Niculescu VO Base Stations for Indoor 80. Positioning α ρ BS BS BS3

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