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A Practical Approach to Landmark Deployment for Indoor Localization Yingying Chen, John Chen, John- -Austen Francisco, Austen Francisco, Yingying Wade Trappe, and Richard P. Martin Wade Trappe, and Richard P. Martin Dept. of Computer

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WINLAB IAB, May 2006

A Practical Approach to Landmark Deployment for Indoor Localization

Yingying Yingying Chen, John Chen, John-

  • Austen Francisco,

Austen Francisco, Wade Trappe, and Richard P. Martin Wade Trappe, and Richard P. Martin

  • Dept. of Computer Science
  • Dept. of Computer Science

Wireless Information Network Laboratory Wireless Information Network Laboratory Rutgers University Rutgers University

May 15 May 15th

th, 2006

, 2006

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

[-35,-68,-56]

RSS Reading (x?,y?)

[(x,y),s1,s2,s3] [(x,y),s1,s2,s3]

(x2,y2) (x1,y1) (x3,y3) angle θ time t

Background

Transmit Packet at Transmit Packet at unknown unknown location location Landmarks Landmarks Rx Rx Modality Modality

Received Signal Strength (RSS) Received Signal Strength (RSS) Time Time-

  • Of

Of-

  • Arrival (TOA)

Arrival (TOA) Angle Angle-

  • Of

Of-

  • Arrival (AOA)

Arrival (AOA)

Principle Principle to compute position to compute position

Lateration/Angulation Lateration/Angulation Scene matching Scene matching Training data/radio map Training data/radio map Localization Localization results results

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Motivation

Localizing sensor nodes is a critical input for high Localizing sensor nodes is a critical input for high-

  • level networking applications:

level networking applications:

Tracking, monitoring, and geometric Tracking, monitoring, and geometric-

  • based routing

based routing Location Location-

  • based services become more prevalent

based services become more prevalent

Recent active research efforts have resulted in a Recent active research efforts have resulted in a plethora of localization methods. plethora of localization methods. Study to improve the Study to improve the deployment of landmarks deployment of landmarks and and thus help thus help a wide variety of algorithms a wide variety of algorithms. .

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Contributions

Impact of landmark placement on localization Impact of landmark placement on localization performance performance

Analytic Model Analytic Model Experimental Results Experimental Results

Compute Compute upper bound upper bound on the maximum location error

  • n the maximum location error

given the placement of landmarks. given the placement of landmarks. Find Find optimal patterns

  • ptimal patterns for landmark placement

for landmark placement

Novel algorithm Novel algorithm maxL

maxL-

  • minE

minE

Generic Generic analysis works for a variety of: analysis works for a variety of: algorithms algorithms, , networks networks, and , and ranging modalities ranging modalities. .

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Outline

Background and motivation Background and motivation Theoretical Analysis Theoretical Analysis Finding an Optimized Landmark Deployment Finding an Optimized Landmark Deployment Experimental Study Experimental Study Conclusion Conclusion Related work Related work

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Analysis with Least Squares

in Localization

Ranging step: Ranging step:

Distance estimation between unknown and Distance estimation between unknown and landmarks landmarks Various methods available Various methods available Focus on Focus on RSS RSS and and TOA TOA

Lateration Lateration step: step:

Traditional: Non Traditional: Non-

  • linear Least squares method

linear Least squares method

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Reduce to Linear Least Squares: Reduce to Linear Least Squares: Localization result: Localization result: ideal ideal Localization result: Localization result: actual actual Location estimation error: Location estimation error:

With With

Error Analysis

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Error Analysis

The landmark deployments with equal The landmark deployments with equal eigenvalues eigenvalues minimize errors! minimize errors!

, , where are the singular values of

where are the singular values of A

A

The The eigenvalues eigenvalues of

  • f A

AT

TA

A are the squares of the singular

are the squares of the singular values of values of A

A

The The eigenvalues eigenvalues of

  • f A

AT

TA

A can be found as:

can be found as:

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

7 landmarks (square plus nested triangle) 8 landmarks (nested squares) 6 landmarks (nested triangles) 3 landmarks (equilateral triangle) 4 landmarks (square) 5 landmarks (square plus center of mass)

Patterns

for Optimal Landmark Placements

? ? ? ? ? ?

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Finding the Optimal Deployment

Analytic analysis gives us Analytic analysis gives us shape shape Length of sides unknown Length of sides unknown Physical constrains Physical constrains of a building

  • f a building

MaxL MaxL-

  • MinE

MinE Algorithm:

Algorithm:

Get Get optimal pattern

  • ptimal pattern based on geometry

based on geometry Fit optimal pattern into maximum floor size Fit optimal pattern into maximum floor size Stretch/shrink Stretch/shrink the deployment shape until such the deployment shape until such movements stop reducing localization errors movements stop reducing localization errors An An iterative search iterative search algorithm algorithm

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Outline

Background and motivation Background and motivation Theoretical Analysis Theoretical Analysis Finding an Optimized Landmark Deployment Finding an Optimized Landmark Deployment Experimental Study Experimental Study Conclusion Conclusion Related work Related work

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Experimental Study

Networks: Networks:

802.11 ( 802.11 (WiFi WiFi) ) 802.15.4 ( 802.15.4 (ZigBee ZigBee) )

Localization algorithms: Localization algorithms:

Point Point-

  • based:

based: RADAR RADAR Area Area-

  • based:

based: ABP (Area Based Probability) ABP (Area Based Probability) Lateration Lateration: :

BN (Bayesian Networks) BN (Bayesian Networks) LS (Least Squares) LS (Least Squares)

Ranging modalities: Ranging modalities:

RSS (Received Signal Strength) RSS (Received Signal Strength) TOA (Time of Arrival) TOA (Time of Arrival)

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Experimental Setup

  • 802.11 network

802.11 network

  • 4 landmarks in two deployments:

4 landmarks in two deployments: Colinear Colinear case case Square case Square case

  • 115 training points

115 training points

  • 802.15.4 network

802.15.4 network

  • 4 landmarks in two deployments:

4 landmarks in two deployments: Horizontal case Horizontal case Square case Square case

  • 70 training points

70 training points

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Evaluation Metrics

Error CDF Error CDF

Provide statistical specification of the localization Provide statistical specification of the localization accuracy accuracy

Average error Average error

Average of the distances between the estimated Average of the distances between the estimated location to the true location location to the true location

H Hö ölder metrics lder metrics

Relates the magnitude of the perturbation in signal Relates the magnitude of the perturbation in signal space to its effect on the localization results space to its effect on the localization results

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Localization Accuracy

RSS RSS 802.11 Network

802.11 Network

Colinear Colinear case case Square case Square case Error CDF across algorithms Error CDF across algorithms

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Localization Accuracy

RSS RSS 802.15.4 Network

802.15.4 Network

Horizontal case Horizontal case Square case Square case Error CDF across algorithms Error CDF across algorithms

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Using Time of Arrival

TOA RSS

Distance estimation based on round trip time between a Distance estimation based on round trip time between a node and a landmark node and a landmark Distance error analysis: TOA vs. RSS Distance error analysis: TOA vs. RSS TOA error modeling: TOA error modeling:

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Localization Accuracy

TOA TOA 802.11 Network

802.11 Network

Colinear Colinear case case Square case Square case Error CDF across algorithms Error CDF across algorithms

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Localization Accuracy

Optimized landmark deployment Optimized landmark deployment

TOA TOA RSS RSS

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Conclusion

Derived Derived an upper bound an upper bound on the maximum location

  • n the maximum location

error given the placement of landmarks error given the placement of landmarks Developed Developed a novel algorithm a novel algorithm, , maxL maxL-

  • minE

minE, for , for finding the optimal landmark placement finding the optimal landmark placement Significant performance improvement Significant performance improvement of a wide

  • f a wide

variety of algorithms variety of algorithms

ABP and RADAR: ABP and RADAR: > 20% > 20% LS: LS: > 30% > 30% BN: BN: ~ 10% ~ 10% Tension Tension between optimized landmark deployment for between optimized landmark deployment for localization vs. deployments that optimize for signal localization vs. deployments that optimize for signal coverage coverage

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Related Work

Localization strategies: Localization strategies:

Range Range-

  • based

based [patwari05loc]:

[patwari05loc]: RSS

RSS [bahl00,elnahrawy04limits],

[bahl00,elnahrawy04limits], TOA

TOA

[GPS, toa04berlin] [GPS, toa04berlin] and TDOA

and TDOA [nissanka00];

[nissanka00]; or

  • r range

range-

  • free

free [shang03,

[shang03, niculescu01aps] niculescu01aps]

Lateration Lateration [Langendoen03Survey,GPS,niculescu01aps,

[Langendoen03Survey,GPS,niculescu01aps, zang05robust,chinta04ad]; zang05robust,chinta04ad]; angulation

angulation; or ; or scene scene-

  • matching

matching

[youssef03localization,roos02stat,bahl00,elnahrawy04limits] [youssef03localization,roos02stat,bahl00,elnahrawy04limits]

Aggregate Aggregate [dohertyl01, shang03]

[dohertyl01, shang03] or

  • r singular

singular (only refer to landmarks)

(only refer to landmarks)

Study of AP deployment for localization: Study of AP deployment for localization:

Simulation to study the location error and signal strength model Simulation to study the location error and signal strength model for a for a few AP configurations few AP configurations [chen02signal]

[chen02signal]

Developed a set of heuristic search algorithms to find optimal A Developed a set of heuristic search algorithms to find optimal AP P deployment deployment [battiti03optimal]

[battiti03optimal]

examined placement, but did not find optimal solutions examined placement, but did not find optimal solutions

[krish05accuracy] [krish05accuracy]

Network signal coverage perspective: Network signal coverage perspective:

AP placement to maximize coverage and throughput properties of AP placement to maximize coverage and throughput properties of wireless LANs and sensor networks wireless LANs and sensor networks

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WINLAB IAB, May 2006 WINLAB IAB, May 2006

Thank you Thank you & & Questions Questions