Title :
Generalized input-estimation technique for tracking maneuvering targets
Author :
Lee, Hungu ; Tahk, Min-Jea
Author_Institution :
Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea
fDate :
10/1/1999 12:00:00 AM
Abstract :
A new input estimation technique for target tracking problem is proposed. Conventional input estimation techniques assume that the target maneuver level is constant within the detection window, which has been the major drawback of the techniques. The proposed technique is developed to overcome this drawback by modeling the target maneuver as a linear combination of some basic time functions. The resulting algorithm has a generalized formulation including earlier works on input estimation. A detection performance of the proposed algorithm is analyzed by investigating the detection sensitivity according to the selection of maneuver models and other design parameters such as the detection window size, measurement noise level, and sampling step size. A computer simulation study shows that the estimation performance of the proposed algorithm is comparable to Bogler´s input estimation method while the computation time is greatly reduced
Keywords :
adaptive Kalman filters; adaptive estimation; covariance matrices; least mean squares methods; linear systems; modelling; performance index; radar tracking; recursive estimation; sensitivity analysis; state estimation; target tracking; tracking filters; Kalman filter; adaptive filters; algorithm performance; basic time functions; computer simulation; covariance matrix; detection logic; detection performance; detection sensitivity; detection window size; generalized input-estimation technique; incremental performance index; jerk model; least squares estimates; linear combination; linear time-invariant system; measurement noise level; radar tracking; recursive formulation; sampling step size; selection of maneuver models; sensitivity analysis; target maneuver modeling; target tracking problem; tracking maneuvering targets; two-state model; Adaptive filters; Algorithm design and analysis; Estimation error; Filtering algorithms; Noise level; Noise measurement; Performance analysis; Recursive estimation; Size measurement; Target tracking;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on