Ship Recognition from Chaff Clouds with Sophisticated Polarimetric Decomposition

Li, Yongzhen; Quan, Sinong; Xiang, Deliang; Wang, Wei; Hu, Canbin; Liu, Yemin; Wang, Xuesong

doi:10.3390/rs12111813

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Ship Recognition from Chaff Clouds with Sophisticated Polarimetric Decomposition

by

Yongzhen Li

¹,

Sinong Quan

^1,*

,

Deliang Xiang

²

,

Wei Wang

³,

Canbin Hu

²,

Yemin Liu

⁴ and

Xuesong Wang

¹

State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha 410073, China

²

National Innovation Institute of Technology, Beijing 100091, China

³

College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China

⁴

Unit 32579 of the PLA, Guilin 541001, China

^*

Author to whom correspondence should be addressed.

Remote Sens. 2020, 12(11), 1813; https://doi.org/10.3390/rs12111813

Submission received: 9 April 2020 / Revised: 25 May 2020 / Accepted: 2 June 2020 / Published: 4 June 2020

(This article belongs to the Section Remote Sensing Perspective)

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Abstract

Ship recognition from chaff cloud jamming is challenging since they have similar dimensions and radar cross sections. In this paper, a polarimetric recognition technique with sophisticated polarimetric decomposition is proposed. To this end, a seven-component model-based decomposition is first put forward by integrating three sophisticated scattering models, thus the dominant and local scattering of ships can be characterized accurately. According to the derived scattering contributions, a robust discrimination feature is then designed based on the concept of contrast and suppression. Coupled with the average scattering angle estimated from eigen-based decomposition, the constructed feature vector is inputted into the support vector machine and the recognition is finally fulfilled. The proposed method is tested on simulated and real polarimetric radar data and the results demonstrate that the proposed method achieves the highest recognition rate of over 98%, which outperforms the state-of-the-art methods.

Keywords: ship recognition; chaff cloud jamming; sophisticated polarimetric decomposition

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MDPI and ACS Style

Li, Y.; Quan, S.; Xiang, D.; Wang, W.; Hu, C.; Liu, Y.; Wang, X. Ship Recognition from Chaff Clouds with Sophisticated Polarimetric Decomposition. Remote Sens. 2020, 12, 1813. https://doi.org/10.3390/rs12111813

AMA Style

Li Y, Quan S, Xiang D, Wang W, Hu C, Liu Y, Wang X. Ship Recognition from Chaff Clouds with Sophisticated Polarimetric Decomposition. Remote Sensing. 2020; 12(11):1813. https://doi.org/10.3390/rs12111813

Chicago/Turabian Style

Li, Yongzhen, Sinong Quan, Deliang Xiang, Wei Wang, Canbin Hu, Yemin Liu, and Xuesong Wang. 2020. "Ship Recognition from Chaff Clouds with Sophisticated Polarimetric Decomposition" Remote Sensing 12, no. 11: 1813. https://doi.org/10.3390/rs12111813

APA Style

Li, Y., Quan, S., Xiang, D., Wang, W., Hu, C., Liu, Y., & Wang, X. (2020). Ship Recognition from Chaff Clouds with Sophisticated Polarimetric Decomposition. Remote Sensing, 12(11), 1813. https://doi.org/10.3390/rs12111813

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Ship Recognition from Chaff Clouds with Sophisticated Polarimetric Decomposition

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