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|a Li, William Wei-Liang
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|a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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|a Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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|a Win, Moe Z.
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|a Iltis, Ronald A.
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|a Win, Moe Z.
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|a Integrated IMU and radiolocation-based navigation using a Rao-Blackwellized particle filter
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|b Institute of Electrical and Electronics Engineers (IEEE),
|c 2015-06-05T18:11:43Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/97201
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|a In this paper, we develop a cooperative IMU/radio-location-based navigation system, where each node tracks the location not only based on its own measurements, but also via collaboration with neighbor nodes. The key problem is to design a nonlinear filter to fuse IMU and radiolocation information. We apply the Rao-Blackwellization method by using a particle filter and parallel Kalman filters for the estimation of orientation and other states (i.e., position, velocity, etc.), respectively. The proposed method significantly outperforms the extended Kalman filter (EKF) in the set of simulations here.
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|a National Science Foundation (U.S.) (Grant ECCS-0901034)
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|a United States. Office of Naval Research (Grant N00014-11-1-0397)
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|a Defense University Research Instrumentation Program (U.S.) (Grant N00014-08-1-0826)
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|a Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies
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|a Article
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|t Proceedings of the 2013 IEEE International Conference on Acoustics, Speech and Signal Processing
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