PROGRESSIVE ESTIMATION AND DETECTION

For large-scale multi-hop wireless sensor networks, progressive es-timation and detection algorithms are developed. For progressive estimation, the classical principles of best linear unbiased estimation (BLUE) and linear minimum mean square error (LMMSE) estima-tion are applied. The difference and similarity between the two are revealed. For progressive detection, a tradeoff between detection performance and limited decision propagation is studied. The pro-gressive estimation and detection algorithms are distributed and per-formed at the application layer of wireless sensor networks, which are fully adaptive to the operations at the networking and other lower layers which can be designed for high spectral efficiency. Index Terms — Progressive estimation and detection, distrib-uted estimation and detection, wireless sensor networks, large-scale multi-hop networks 1