The terrain between grid points is used to modify locally the background error correlation matrix in an objective analysis system. This modification helps to reduce the influence across mountain barriers of correction...
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The terrain between grid points is used to modify locally the background error correlation matrix in an objective analysis system. This modification helps to reduce the influence across mountain barriers of corrections to the background field that are derived from surface observations. This change to the background error correlation matrix is tested using an analytic case of surface temperature that encapsulates the significant features of nocturnal radiation inversions in mountain basins, which can be difficult to analyze because of locally sharp gradients in temperature. Bratseth successive corrections, optimal interpolation, and three-dimensional variational approaches are shown to yield exactly the same surface temperature analysis. Adding the intervening terrain term to the Bratseth approach led to solutions that match more closely the specified analytic solution. In addition, the convergence of the Bratseth solutions to the best linear unbiased estimation of the analytic solution is faster. The intervening terrain term was evaluated in objective analyses over the western United States derived from a modified version of the Advanced Regional Prediction System Data Assimilation System. Local adjustment of the background error correlation matrix led to improved surface temperature analyses by limiting the influence of observations in mountain valleys that may differ from the weather conditions present in adjacent valleys.
The use of selective partial updating method for reducing computational complexity of adaptive algorithms has been proposed recently. However, its performance analysis has not been studied as extensively and exactly a...
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The use of selective partial updating method for reducing computational complexity of adaptive algorithms has been proposed recently. However, its performance analysis has not been studied as extensively and exactly as LMS or RLS algorithms for time-varying channel estimation. This paper provides performance analysis of the low-complexity family of affine projection algorithms based on selective partial update method on the estimation of multipath Rayleigh fading channels in the presence of carrier frequency offsets (CFO) and random channel variations. The analysis is based on the calculation of the error correlation matrix of the estimation, the mean-square weight error (MSWE) and the mean-square estimation error (MSE) parameters. The analysis does not use strong assumptions like small or large step-size, and explicit closed-form expressions for the MSE of estimation are obtained only from common hypotheses in wireless communication context. In this paper, the optimum step-size parameters minimizing the MSE of estimation are analytically derived without any simplifying assumptions. For the sake of comparison with other analytical approaches, the performance of the introduced algorithms is also investigated using the energy conservation relation. Likewise, for exact performance analysis, all the moment terms that appear in closed form expressions for the MSE of estimation are evaluated. Simulations are conduced to corroborate the presented studies and show that the theoretical results agree well with the simulation results over non-stationary multipath Rayleigh fading channels.
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