Kalman tracking filter in 3-D space
Andon Dimitrov Lazarov, Christo A. Kabakchiev, Atanas Dimitrov, Dimitar Minchev · 2017
In this work a Kalman filter for tracking Unmanned Aerial Vehicle (UAV) moving near the base lane of a bistatic radar system and illuminated by GPS signals in three-dimensional (3-D) space is suggested. Continuous-time and discrete-time state equations are derived to define a linear time-invariant model. Model matrices describing the behavior of the object, state vectors, measurement vectors and vector noise process with its statistical characteristic are defined. Structures of the discrete state transition matrix of the dynamic model and covariance noise matrix are given. Linear time-invariant model matrices are derived. State model matrices with constant entries, measurement model matrix, state transition matrix of the dynamic model, covariance noise state matrix and covariance matrix of the measurements, are defined. Recurrent Kalman equations are described. To verify a 3-D Kalman tracking a numerical experiment is performed.