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PSI (deg)<br />

m<br />

Node 2, MPATH #1: PSI<br />

150<br />

100<br />

50<br />

0 20 40 60 80<br />

Time (s)<br />

Node 2, MPATH #1: Offset<br />

80<br />

60<br />

40<br />

20<br />

0<br />

0 20 40 60 80<br />

Time (s)<br />

Figure 12. Multipath parameter estimation: Node 2<br />

measurements.<br />

For Node 1, the parameters for the first indirect path (off<br />

the West wall) are estimated with reasonable accuracy after<br />

40 s. The parameters for the second path (off the South<br />

wall) cannot be estimated for the first 27 s since the indirect<br />

path is blocked by the rectangular object. When estimation<br />

commences at 27.5 s, the parameters are almost immediately<br />

estimated with high accuracy, and this accuracy level<br />

continues until the direct path is blocked at 73.5 s.<br />

For Node 2, the parameters for the first indirect path (off<br />

the East wall) are estimated with reasonable accuracy<br />

after 45 s. The direct path becomes blocked at 55.5 s, so<br />

that further updating of the parameter estimates was not<br />

possible. The second indirect path (off the South wall)<br />

was blocked for the first 34 s. At 34.5 s, the indirect path<br />

became unblocked and the indirect path parameters were<br />

estimated. At the next time step (35 s), the direct path<br />

became blocked and remained blocked for the remainder<br />

of the simulation, precluding further estimation of the<br />

indirect path parameters. Thus, in this case, the indirect<br />

parameter estimates are based on a single measurement<br />

pair.<br />

As discussed previously, the variation in the true multipath<br />

parameters was relatively small in this representative<br />

example, so that relatively accurate tag tracking could be<br />

maintained when it was no longer possible to perform<br />

parameter estimation.<br />

12 Innovative Indoor Geolocation Using RF Multipath Diversity<br />

deg<br />

m<br />

Node 2, MPATH #2: PSI<br />

50<br />

0<br />

-50<br />

0 20 40 60 80<br />

Time (s)<br />

Node 2, MPATH #2: Offset<br />

80<br />

60<br />

40<br />

20<br />

0<br />

0 20 40 60 80<br />

Time (s)<br />

x1par2<br />

Conclusion<br />

A new approach is suggested for the problem of indoor<br />

geolocation in the presence of dominating multipath using<br />

RF time-of-arrival measurements. Multipath delays are<br />

modeled using a geometry-based argument. Assuming a<br />

series of specular reflections off planar surfaces, the model<br />

contains a maximum of three unknown multipath parameters<br />

per path, which may be estimated in a nonlinear<br />

filter. Simulation results for a relatively simple representative<br />

example suggest that multipath parameters can be<br />

estimated with sufficient accuracy to maintain geolocation<br />

accuracy when one or more direct paths are undetected.<br />

This approach allows the possibility of building up indoor<br />

map information as the geolocation process commences.<br />

references<br />

[1] Pahlavan, K. and X. Li, “Indoor Geolocation Science and<br />

Technology,” IEEE Communications Magazine, February<br />

2002.<br />

[2] Pahlavan, K., F. Akgul, M. Heidari, and H. Hatami, “Precision<br />

Indoor Geolocation in the Absence of Direct Path,” submitted<br />

to IEEE Communications Magazine.<br />

[3] Moghaddam, P.P., H. Amindavar, R. L. Kirlin, “A New Time-<br />

Delay Estimation in Multipath,” IEEE Trans. on Signal Processing,<br />

Vol. 51, No. 5, May 2003, pp. 1129-1142.<br />

[4] Voltz, P.J. and D. Hernandez, “Maximum Likelihood Time of<br />

Arrival Estimation for Real-Time Physical Location Tracking<br />

of 802.11a/g Mobile Stations in Indoor Environments,” IEEE<br />

Paper No. 0-7803-8416-4/04, 2004.<br />

[5] Qi, Y., H. Suda, H. Kobayashi, “On Time-of-Arrival Positioning<br />

in a Multipath Environment,” IEEE Paper No. 0-7803-<br />

8521-7/04, 2004.<br />

[6] Giremus, A. and J.-Y. Tourneret, “Joint Detection/Estimation<br />

of Multipath Effects for the Global Positioning System,” Proc.<br />

IEEE ICASSP, 2005.<br />

[7] Do, J.-Y., M. Rabinowitz, P. Enge, “Linear Time-of Arrival Estimation<br />

in a Multipath Environment by Inverse Correlation<br />

Method,” Proc. ION Annual Meeting, Cambridge, MA, June<br />

2005.<br />

[8] Erickson, J.W., P.S. Maybeck, J.F. Raquet, “Multipath-Adaptive<br />

GPS/INS Receiver,” IEEE Trans. Aero. Elect. Sys., Vol.<br />

41, April 2005, pp. 645-657.<br />

[9] Jourdan, D.B., J.J. Deyst, M.Z. Win, N. Roy, “Monte Carlo<br />

Localization in Dense Multipath Environments Using UWB<br />

Ranging,” Proc. IEEE International Conference on Ultra-<br />

Wideband, Zurich, September 2005, pp. 314-319.<br />

[10] Ristic, B., S. Arulampalam, N. Gordon, Beyond the Kalman<br />

Filter, Chapter 3, Artech House, Boston, 2004.<br />

[11] Jazwinski, A.H., Stochastic Processes and Filtering Theory,<br />

Academic Press, New York, 1970.<br />

[12] Bierman, G.J., Factorization Methods for Discrete Sequential<br />

Estimation, Academic Press, New York, 1977.

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