Joint Registration and State Estimation for Two-Station Passive Tracking

Qiang Zhu; Jian Xun Li

doi:10.4028/www.scientific.net/AMM.427-429.675

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 427-429Joint Registration and State Estimation for...

Joint Registration and State Estimation for Two-Station Passive Tracking

Abstract:

Registration and nonlinearity are two crucial factors affecting the performance of the two-station passive locating system. In this paper, an online joint registration and data fusion algorithm is proposed to estimate the sensor bias and target state simultaneously using the angle-only measurements from the two ownship stations. The system model of the passive radar is firstly developed followed by the expectation-maximization (EM) approach dealing with the derivation of maximum likelihood (ML) function of the complete data. The unscented Kalman filter (UKF) is chosen to alleviate the influence caused by nonlinearity generated in the measurement function. Computer simulation shows that the proposed method is effective and reliable for this specific tracking scenario.

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Periodical:

Applied Mechanics and Materials (Volumes 427-429)

Pages:

675-679

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.427-429.675

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Online since:

September 2013

Authors:

Qiang Zhu, Jian Xun Li

Keywords:

Angle-Only, Em-UKF, Passive Radar, Registration, Tracking

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