added: new KalmanCovariance struct to handle covariance sparsity efficiently#216
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Similarly to #202 for the objective function weights in MPCs, a new
KalmanCovarianceparametric struct is created. First, it avoid duplicate code in the constructor of the Kalman filters. Second, two new parameters are introduced to preserve special types likeDiagonal{NT, Vector{NT}}. It will also preserves other special types likeSparseMatrixCSC. The performance advantages will be mainly visible for theMovingHorizontEstimatorwith nonlinear plant models, since the objective is computed with e.g.dot(V̂, invR̂_Nk, V̂)and the operation is faster wheninvR̂_Nkis aDiagonalmatrix.