Each - Draper Laboratory
Each - Draper Laboratory
Each - Draper Laboratory
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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.