Title :
Separated covariance filtering
Author :
Portmann, G.J. ; Moore, J.R. ; Bath, W.G.
Author_Institution :
Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA
Abstract :
A separated covariance filter (SCF) for estimating position and velocity given noisy measurements is discussed. The SCF calculates the state errors due to measurement errors and those due to target acceleration separately. The SCF overcomes two difficulties with the standard Kalman filter technique: (1) selection of the process noise covariance; and (2) interpreting the Kalman state covariance. The SCF is adaptable to a stream of unsequenced measurements
Keywords :
filtering and prediction theory; measurement errors; radar theory; measurement errors; noisy measurements; position estimation; separated covariance filter; separated covariance filtering; state errors; target acceleration; unsequenced measurements; velocity estimation; Acceleration; Accelerometers; Adaptive filters; Covariance matrix; Measurement errors; Position measurement; Predictive models; State estimation; Steady-state; Trajectory;
Conference_Titel :
Radar Conference, 1990., Record of the IEEE 1990 International
Conference_Location :
Arlington, VA
DOI :
10.1109/RADAR.1990.201208
