摘要
A control-based full state observer scheme is explored for video target tracking application, and is enhanced with a lowpass filter for improving the tracking precision, thus forming an Enhanced Full State Observer (EFSO). The whole design is based on the given lab-generated video sequence with motion of an articulate target. To evaluate the EFSO’s stochastic noise tolerance, a Kalman Filter (KF) is intentionally employed in tracking the same target with the given Gaussian white noises. The comparison results indicate that, for system noises of certain statistics, the proposed EFSO has its own noise resistance capacity that is superior to that of KF and is more advantageous for implementation.
A control-based full state observer scheme is explored for video target tracking application, and is enhanced with a lowpass filter for improving the tracking precision, thus forming an Enhanced Full State Observer （EFSO）. The whole design is based on the given lab-generated video sequence with motion of an articulate target. To evaluate the EFSO＇s stochastic noise tolerance, a Kalman Filter （KF） is intentionally employed in tracking the same target with the given Gaussian white noises. The comparison results indicate that, for system noises of certain statistics, the proposed EFSO has its own noise resistance capacity that is superior to that of KF and is more advantageous for implementation.
基金
Supported by the Science Foundation of Zhejiang Education Department (Y200804700)
Ningbo Natural Science Foundation of Zhejiang Province (No. 201001A6001075)
