Radar network scanning coordination based on ensemble transform Kalman filtering variance optimization

In this work, the variance of the error of analyzed wind fields obtained from an ensemble Kalman filter is used as a criterion with which to optimize radar network scanning strategies. The measurement equation in the Kalman filter approach is obtained from variational wind retrieval and, thus, is a function of the retrieval scanning parameters. It is shown that the mapping from radar parameters to the variance of the error is differentiable. The ensemble transform is introduced to facilitate the computational effort. The approach presented in principle may be used to optimize the scanning strategy in a network with any number of radars. Numerical examples are presented with networks consisting of two, four and nine radars using a quasi-Monte Carlo optimization scheme. Error estimates for the approximation of the optimal strategies are discussed.