State estimation in range coordinate using range-only measurements

doi:10.23919/JSEE.2022.000050

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (3): 497-510.doi: 10.23919/JSEE.2022.000050

• • 下一篇

收稿日期:2021-03-06 接受日期:2022-01-14 出版日期:2022-06-18 发布日期:2022-06-24

State estimation in range coordinate using range-only measurements

Keyi LI(), Zhengkun GUO(), Gongjian ZHOU*()

¹ School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China

Received:2021-03-06 Accepted:2022-01-14 Online:2022-06-18 Published:2022-06-24
Contact: Gongjian ZHOU E-mail:likeyi@hit.edu.cn;guozkbetter@163.com;zhougj@hit.edu.cn
About author:|LI Keyi was born in 1991. He received his B.E. degree in communication engineering and M.E. and Ph.D. degrees in information and communication engineering from Harbin Institute of Technology, Harbin, China, in 2014, 2016, and 2020, respectively. He is currently a lecturer in the School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China. From November 2020, he held a Postdoctoral Fellowship in the Department of Aerospace Engineering, Harbin Institute of Technology. From September 2018 to September 2019, supported by China Scholarship Council, he was a visiting Ph.D. student in McMaster University, Hamilton, ON, Canada. His research interests include estimation, target tracking and information fusion. E-mail: likeyi@hit.edu.cn||GUO Zhengkun was born in 1985. He received his B.E. degree from the School of Electronic Information, Wuhan University, Wuhan, China, in 2008, his M.E. degree from Shanghai Academy of Spaceflight Technology, Shanghai, China, in 2011 and his Ph.D. degree from the School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China. He is currently working as an assistant engineer in Shanghai Academy of Spaceflight Technology. From March 2016 to March 2017, supported by China Scholarship Council, he was a visiting Ph.D. student in McMaster University, Hamilton, ON, Canada. His research interests include signal processing, estimation, tracking and information fusion. E-mail: guozkbetter@163.com||ZHOU Gongjian was born in 1979. He received his B.E., M.E., and Ph.D. degrees in information and communication engineering from Harbin Institute of Technology, Harbin, China, in 2000, 2002, and 2008, respectively. From February 2009 to March 2011, he held a Postdoctoral Fellowship in the Department of Aerospace Engineering, Harbin Institute of Technology. From April 2011 to May 2012, he was a visiting professor with the Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada. He is currently a professor with the Department of Electronic Engineering, Harbin Institute of Technology. He is also a Longjiang Young Scholar. His research interests include estimation, tracking, detection, information fusion and signal processing. E-mail: zhougj@hit.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (61671181; 62101162)

摘要/Abstract

Abstract:

In some tracking applications, due to the sensor characteristic, only range measurements are available. If this is the case, due to the lack of full position measurements, the observability of Cartesian states (e.g., position and velocity) are limited to particular cases. For general cases, the range measurements can be utilized by developing a state estimation algorithm in range-Doppler (R-D) plane to obtain accurate range and Doppler estimates. In this paper, a state estimation method based on the proper dynamic model in the R-D plane is proposed. The unscented Kalman filter is employed to handle the strong nonlinearity in the dynamic model. Two filtering initialization methods are derived to extract the initial state estimate and the initial covariance in the R-D plane from the first several range measurements. One is derived based on the well-known two-point differencing method. The other incorporates the correct dynamic model information and uses the unscented transformation method to obtain the initial state estimates and covariance, resulting in a model-based method, which capitalizes the model information to yield better performance. Monte Carlo simulation results are provided to illustrate the effectiveness and superior performance of the proposed state estimation and filter initialization methods.

Key words: range-only measurement, state estimation, filter initialization, target tracking, unscented Kalman filter (UKF)

. [J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 497-510.

Keyi LI, Zhengkun GUO, Gongjian ZHOU. State estimation in range coordinate using range-only measurements[J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 497-510.

图/表 12

参考文献 39

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State estimation in range coordinate using range-only measurements

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