Model based joint target tracking and classification with RCS measurement

Ronghui Zhan; Liping Wang

doi:10.1117/12.2559548

31 December 2019 Model based joint target tracking and classification with RCS measurement

Ronghui Zhan, Liping Wang

Proceedings Volume 11384, Eleventh International Conference on Signal Processing Systems; 113840S (2019) https://doi.org/10.1117/12.2559548
Event: Eleventh International Conference on Signal Processing Systems, 2019, Chengdu, China

Abstract

A model-based joint tracking and classification (JTC) method is proposed for narrowband radar with kinematic and radar cross section (RCS) measurements. The method is derived from the 3D scattering center model (3DSCM), which can construct an explicit relation between the aspect angle and the predicted RCS. To deal with the numerical problem in observation model, a modified likelihood function for RCS measurement is adopted under the assumption of additive Gaussian observation noise. The JTC processing is realized by sequential Monte Carlo (SMC) technique. Specifically, a bank of particle filters are used to obtain type-dependent target state and type estimates. Compared with the traditional JTC methods using low resolution sensor, the proposed method is free from the constraint that target classification has to rely on different maneuvering modes. Simulation results validate the effectiveness of the proposed method with maritime application scenario.

Citation Download Citation

Ronghui Zhan and Liping Wang "Model based joint target tracking and classification with RCS measurement", Proc. SPIE 11384, Eleventh International Conference on Signal Processing Systems, 113840S (31 December 2019); https://doi.org/10.1117/12.2559548

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