State estimation with incomplete nonlinear constraint

Yuan Huang; Xueying Wang; Wei An

doi:10.1117/12.2277999

4 October 2017 State estimation with incomplete nonlinear constraint

Yuan Huang, Xueying Wang, Wei An

Proceedings Volume 10431, Remote Sensing Technologies and Applications in Urban Environments II; 104310U (2017) https://doi.org/10.1117/12.2277999
Event: SPIE Remote Sensing, 2017, Warsaw, Poland

Abstract

A problem of state estimation with a new constraints named incomplete nonlinear constraint is considered. The targets are often move in the curve road, if the width of road is neglected, the road can be considered as the constraint, and the position of sensors, e.g., radar, is known in advance, this info can be used to enhance the performance of the tracking filter. The problem of how to incorporate the priori knowledge is considered. In this paper, a second-order sate constraint is considered. A fitting algorithm of ellipse is adopted to incorporate the priori knowledge by estimating the radius of the trajectory. The fitting problem is transformed to the nonlinear estimation problem. The estimated ellipse function is used to approximate the nonlinear constraint. Then, the typical nonlinear constraint methods proposed in recent works can be used to constrain the target state. Monte-Carlo simulation results are presented to illustrate the effectiveness proposed method in state estimation with incomplete constraint.

Citation Download Citation

Yuan Huang, Xueying Wang, and Wei An "State estimation with incomplete nonlinear constraint", Proc. SPIE 10431, Remote Sensing Technologies and Applications in Urban Environments II, 104310U (4 October 2017); https://doi.org/10.1117/12.2277999

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