Abstract:
Discrete filtering is considered with emphasis on computational aspects. A short survey of numerically stable filter implementations is given founded on the basic mathematical ideas: positive definite (covariance or information) matrix factorization, vector measurement scalarization, matrix triangularization and array-matrix orthogonalization. Using them, LD-algorithm of Extended Kalman Filtering is proposed as applied to the non-linear problem of target motion analysis. Application of the algorithm to ship navigation and conning (including collision avoidance) is discussed.
Keywords:computer data engineering, algorithms of least squares method, discrete filtering, filter divergence, numerical stability, extended Kalman filter, specific statistical applications and models, digital simulation and system modeling.