The discrete DS-UWB channel estimation problem is modeled by the knowledge of set theory, and an UWB channel estimation algorithm based on obe algorithm is proposed. The influence of different spreading codes on the e...
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ISBN:
(纸本)9781728111902
The discrete DS-UWB channel estimation problem is modeled by the knowledge of set theory, and an UWB channel estimation algorithm based on obe algorithm is proposed. The influence of different spreading codes on the estimated mean square error of the channel is analyzed. Simulations show that even in the case of unknown channel lengths, the channel tap values are well estimated in a determinate dimensional space.
A set-membership (SM) normalized least-mean-square (NLMS) (SMNLMS) algorithm is developed using SM theory in the class of optimal bounding ellipsoid (obe) algorithms. This signed version of NLMS algorithm requires a p...
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A set-membership (SM) normalized least-mean-square (NLMS) (SMNLMS) algorithm is developed using SM theory in the class of optimal bounding ellipsoid (obe) algorithms. This signed version of NLMS algorithm requires a priori knowledge of a bound for the error magnitude, which is unknown in most applications. A very simple algorithm is proposed for the case in which the unknown magnitude of the measurement noise is slowly time-varying. The proposed algorithm is able to extract the noise magnitude information and exploit this magnitude to enhance or accelerate the learning process without risk of overbounding or performance loss due to underbounding. The performance of the proposed algorithm is compared with that of SMNLMS using some simulation examples.
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