Point spread function generation method of Geo-stationary GNSS based bistatic forward looking SAR

Shi, Zhiming; Zeng, Zhangfan; Zhou, Yanling; Li, Wenchao; Pan, Yongcai; Lan, Ting

doi:10.1016/j.ijleo.2018.10.178

Cited by 2 publications

(3 citation statements)

References 8 publications

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“…Soon after being reflected from the target, the signal is received by the GeoSta-GNSS-BFLSAR ground receiver. After demodulation, the received signal is given by [1]:normals(t,η)=σ⋅p[t−R(η)/c]·exp{−j2πfc[t−R(η)]/c} where λ is the carrier wavelength, t and η are the fast time and slow time, respectively. p[·] is the envelope of the received signal.…”

Section: Geosta-gnss-bflsar Signal Model and Analysismentioning

confidence: 99%

“…In this section, the 2-dimensional spectrum of a GeoSta-GNSS-BFLSAR received signal is derived on the basis of the echo signal, i.e., Equation (1), by introducing the Point of Stationary Phase (POSP) method. Applying a Taylor Expansion, the slant range between receiver and target, i.e., Rr(η), could be approximated as [1]:Rr(η)=Rc2+v2η2−2Rcvηsinθ≃Rccos[1+v2(η−Rcsinθv)22Rc2cosθ2]…”

Section: Geosta-gnss-bflsar Signal Model and Analysismentioning

confidence: 99%

“…The Geo-Stationary GNSS-based bistatic forward looking SAR (GeoSta-GNSS-BFLSAR) is a bistatic SAR system subclass [1]. It employs geo-stationary GNSS as the illuminator, while the receiver is mounted on a moving aircraft.…”

Section: Introductionmentioning

confidence: 99%

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A Fourier-Based Image Formation Algorithm for Geo-Stationary GNSS-Based Bistatic Forward-Looking Synthetic Aperture Radar

Zeng

Shi

Xing

et al. 2019

Sensors

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A Geo-Stationary GNSS-based Bistatic Forward-Looking Synthetic Aperture Radar (GeoSta-GNSS-BFLSAR) system is a particular kind of passive bistatic SAR system. In this system, a geo-stationary GNSS is used as the transmitter, while the receiver is deployed on a moving aircraft, which travels towards a target in a straight line. It is expected that such a radar system has potential for self-landing, self-navigation and battlefield information acquisition applications, etc. Up to now, little information from a research perspective can be found about GeoSta-GNSS-BFLSAR systems. To address this information gap, this paper proposes a preliminary image formation algorithm for GeoSta-GNSS-BFLSAR. The full details of the mathematical derivation are given. It is highlighted that, to overcome the long dwell time and spatial variance of GeoSta-GNSS-BFLSAR, a modified migration correction factor must be designed. In addition, the system performances and technical limitations of GeoSta-GNSS-BFLSAR such as focusing depth and spatial resolution are analytically discussed. In the end, a set of simulations including the image formation algorithm, focusing depth and spatial resolution were conducted for verification. It is demonstrated that the focusing performances of the proposed algorithm have a high level of similarity with the theoretical counterparts. This article thus proves the feasibility of GeoSta-GNSS-BFLSAR systems from a simulation level and establishes a foundation for the real applications of such a radar scheme in the future.

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Section: Geosta-gnss-bflsar Signal Model and Analysismentioning

confidence: 99%

Section: Geosta-gnss-bflsar Signal Model and Analysismentioning

confidence: 99%

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A Fourier-Based Image Formation Algorithm for Geo-Stationary GNSS-Based Bistatic Forward-Looking Synthetic Aperture Radar

Zeng

Shi

Xing

et al. 2019

Sensors

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An Improved Pre-Processing Algorithm for Resolution Optimization in Galileo-Based Bistatic SAR

et al. 2019

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Galileo based bistatic synthetic aperture radar (Galileo-BiSAR) is a subclass of passive radar, where the Galileo satellite is used as the transmitter and the receiver can be mounted on a moving vehicle or fixed on the ground. Such scheme is cost-effective and safe, and therefore can be widely used in military areas such as battle monitoring or civil scenarios such as ground deformation monitoring, change detection, etc. However, the drawback of Galileo-BiSAR system lies on the fact that, same with other passive radar, the transmitter and receiver are separately located, which introduces the necessity of pre-processing before further processing such as image formation. The existing pre-processing algorithm for Galileo-BiSAR system was established on the idea that only single band E5b signal is used. Due to its bandwidth of 20MHz, however, the range resolution of resulting image is merely up to 15m, which is not acceptable for most applications. Aimed at improving range resolution, this article proposes a new pre-processing algorithm for Galileo-BiSAR. Rather than employing the single band signal as well as duplicate of transmitting signal as the local reference signal in tradition way, a novel technique of dual matched filtering is proposed for pre-processing. Full simulations of the proposed pre-processing and further image formation were both performed. The results demonstrated the full functionality of the proposed pre-processing algorithm and verified its capability of higher resolution imaging against traditional algorithm. In addition, the paper also highlights its good computational efficiency and performance limitation against noise. Bistatic SAR, pre-processing, resolution. INDEX TERMS

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Point spread function generation method of Geo-stationary GNSS based bistatic forward looking SAR

Cited by 2 publications

References 8 publications

A Fourier-Based Image Formation Algorithm for Geo-Stationary GNSS-Based Bistatic Forward-Looking Synthetic Aperture Radar

A Fourier-Based Image Formation Algorithm for Geo-Stationary GNSS-Based Bistatic Forward-Looking Synthetic Aperture Radar

An Improved Pre-Processing Algorithm for Resolution Optimization in Galileo-Based Bistatic SAR

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