Abstract
We develop algorithms for sequential signal encoding from sensor measurements, and for signal estimation via fusion of channel-corrupted versions of these encodings. For signals described by state space models, we present optimized sequential binary-valued encodings constructed via threshold-controlled scalar quantization of a running Kalman filter signal estimate from the sensor measurements. We also develop methods for robust fusion from observations of these encodings corrupted by binary symmetric channels.
Original language | English |
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Pages (from-to) | 2577-2580 |
Number of pages | 4 |
Journal | Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing |
Volume | 4 |
Publication status | Published - 2001 |
Externally published | Yes |
Event | 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States Duration: 7 May 2001 → 11 May 2001 |