Bistatic Radar Coincidence Imaging Based on Multiple Measurement Vectors for Rotating Cone-Shaped Targets

Rui Li,Yijun Chen,Jia Liang,Ying Luo,Qun Zhang

doi:10.1155/2020/3878525

Rui Li, Yijun Chen + Show 3 more

Open Access

https://doi.org/10.1155/2020/3878525

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Abstract

Bistatic radar imaging can overcome limitations of monostatic radar imaging and obtain abundant target feature information; thus, it is followed with interest. Different from bistatic inverse synthetic aperture radar (Bi-ISAR) imaging, bistatic radar coincidence imaging (Bi-RCI) provides a new tack on the bistatic radar imaging technique. In this paper, a Bi-RCI based on multiple measurement vectors (MMV) for rotating cone-shaped targets is proposed to realize Bi-RCI coherent processing and improve imaging performance. Based on the mixed mode signals, a MMV parametric model is established and measurement number coarse selection is proposed. Finally, a modified sparse Bayesian learning (MSBL) algorithm is introduced to reconstruct the target image. Simulation results demonstrate the validity and the superiority of the proposed method.

Highlights

Due to the separation of the transmitter and receiver, bistatic radar has better survivability and antijamming performance, can obtain more abundant target feature information, and can effectively reduce the system cost [1]
As one of the imaging techniques, the inverse synthetic aperture radar (ISAR) imaging using bistatic configuration can overcome some limitations of monostatic ISAR imaging and is exploited in territory air defense [7], ocean surveillance [8], and other fields
If the value of ξ is small, the measurement vectors (MMV) parametric model established based on the obtained measurement number is more likely to succeed, but the imaging performance may not be significantly improved

Summary

Introduction

Due to the separation of the transmitter and receiver, bistatic radar has better survivability and antijamming performance, can obtain more abundant target feature information, and can effectively reduce the system cost [1]. In this paper, in order to solve the first problem, the signal waveform is repeatedly transmitted to obtain coherent echoes for accumulation, and a multiple measurement vector (MMV) parametric model is established to realize the Bi-RCI coherent accumulation process. The advantages of the proposed method can be summarized as follows: (1) because of the separation of the transceiver and receiver, the continuous waveform can be used to shorten the observation time to realize fast and real-time imaging of rotating targets; (2) the coherent accumulation time is short, so the influence of target motion and rotation can be neglected, and it is not necessary to implement the echo translational motion compensation in the imaging process; and (3) coherent processing can enhance the antinoise ability and further improve the imaging quality.

Bi-RCI Based on MMV

Simulation and Analysis

Conclusions