An Error Registration Method Based on UKF for Maritime Multi-Platforms

Article Preview

Abstract:

To establish the uniform situation map, the platforms’ low-precision navigation information and the location information measured mutually are used to carry out the sensor data alignment for martime multi-platforms. This method can avoid the dependences on high-precision navigation equipments and the errors introduced by assuming the earth’s surface to be the plane. The models of coordinate conversion for aligning are presented. Then the measure equations and the state equations with regard to navigation systematic error and sensor systematic error are built respectively, and a registration algorithm based on Unscented Kalman filtering is designed for estimating online and compensating those two systematic errors. Consequently, the error registration for martime multi-platforms is achieved, and the higher precision information can be provided for the subsequent data association and data fusion. The simulation results demonstrate the correctness and validity of the algorithm.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

192-197

Citation:

Online since:

February 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Li Yue and Qiu Zhihe, in: Navigation and Localization 2nd ed [M]. Beijing: National Defense Industry Press, (2008).

Google Scholar

[2] Dana P. M, in: Registration: A Prerequisite for Multiple Sensor Tracking. edited by Y. Bar-Shalom, Multitarget-Multisensor Tracking: Advanced Applications, Dedham MA: Artech House, 1990: 180-185.

Google Scholar

[3] Zhou Yifeng, Leung H and Yip C. P, in: An Exact Maximum Likelihood Registration Algorithm for Data Fusion [J]. IEEE Trans. on Signal Processing, 1997, 45(6): 1560-1572.

DOI: 10.1109/78.599998

Google Scholar

[4] Lerro D and Bar-Shalom Y, in: Tracking with Debiased Consistent Converted Measurement vs. EKF [J]. IEEE Trans. on Aerospace and Electronics Systems, 1993, 29(3): 1015-1022.

DOI: 10.1109/7.220948

Google Scholar

[5] Hu Hongtao, Jing Zhongliang and Hu Shiqiang, in: An Unscented Kalman Filter Based Multi-platform Multi-sensor Registration [J]. Journal of Shanghai Jiao Tong University, 2005, 39(9): 1518-1521.

Google Scholar

[6] Julier J. S, in: The Scaled Unscented Transformation. Proc. of American Control Conf., Jefferson City, 2002: 4555-4559.

Google Scholar

[7] Pan Quan, Yang Feng etc, in: Survey of a Kind of Nonlinear Filters — UKF [J]. Control and Decision, 2005, 20(5): 481-489.

Google Scholar