Chirp scaling algorithm for GEO SAR based on fourth-order range equation

Bao, Min; Xing, Mengdao; Li, Y.C.

doi:10.1049/el.2011.1892

Cited by 27 publications

(16 citation statements)

References 5 publications

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“…In order to compare the imaging results obtained by proposed algorithm and algorithm in [19], simulation results of the algorithm in [19] are also shown in Table 2.…”

Section: Simulation Resultsmentioning

confidence: 99%

A Generalized Chirp-Scaling Algorithm for Geosynchronous Orbit SAR Staring Observations

2017

Sensors

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Geosynchronous Orbit Synthetic Aperture Radar (GEO SAR) has recently received increasing attention due to its ability of performing staring observations of ground targets. However, GEO SAR staring observation has an ultra-long integration time that conventional frequency domain algorithms cannot handle because of the inaccurately assumed slant range model and existing azimuth aliasing. To overcome this problem, this paper proposes an improved chirp-scaling algorithm that uses a fifth-order slant range model where considering the impact of the “stop and go” assumption to overcome the inaccuracy of the conventional slant model and a two-step processing method to remove azimuth aliasing. Furthermore, the expression of two-dimensional spectrum is deduced based on a series of reversion methods, leading to an improved chirp-scaling algorithm including a high-order-phase coupling function compensation, range and azimuth compression. The important innovations of this algorithm are implementation of a fifth-order order slant range model and removal of azimuth aliasing for GEO SAR staring observations. A simulation of an L-band GEO SAR with 1800 s integration time is used to demonstrate the validity and accuracy of this algorithm.

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“…In order to compare the imaging results obtained by proposed algorithm and algorithm in [19], simulation results of the algorithm in [19] are also shown in Table 2.…”

Section: Simulation Resultsmentioning

confidence: 99%

A Generalized Chirp-Scaling Algorithm for Geosynchronous Orbit SAR Staring Observations

2017

Sensors

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“…However, inspired by these methods, some scholars developed algorithms for GEO SAR. Bao et al [11] modified the chirp scaling (CS) algorithm based on a fourth-order polynomial model, and achieved an 8-m resolution within a 40 × 40 km swath. Hu et al [12] improved the conventional nonlinear CS algorithm by accounting for a linear spatial variance in the range direction in the polynomial model.…”

Section: Slant Range History Of Squint Mode Geo Sarmentioning

confidence: 99%

Squint Mode GEO SAR Imaging Using Bulk Range Walk Correction on Received Signals

Geng

et al. 2018

Remote Sensing

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Geosynchronous synthetic aperture radar (GEO SAR) has the potential for conducting long-term observation of target zones, which is essential for remote sensing applications such as disaster monitoring and vegetation measurements. The squint imaging mode is crucial for long-term observation using GEO SAR. However, this type of SAR imaging is problematic because the squint mode introduces a nonzero range cell walk, which increases the prevalence of invalid data in echoes and intensifies the coupling between the azimuth and range. Therefore, this paper proposes a novel squint mode GEO SAR imaging method based on the correction of the bulk range walk of received signals. Adjusting the starting time of the receiving window significantly reduces the redundancy in echoes. Then, first-order filtering, range cell migration correction, range compression, partial dechirp, and azimuth compression are used to obtain the imaging result. Simulation results for the GEO SAR imaging of Wenchuan County in China demonstrate that the proposed algorithm can achieve a resolution of 5 m within a 30 × 30 km swath over 48% of the orbital period.

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“…In this case, the range history R i (t) becomes R i (t) + ∆R i (t), and an additional phase modulation will be in S (k,t). The error ∆R i (t) will cause the SAR image degradation, such as smearing and deformation (Huang et al, 2011;Bao et al, 2012;Liao et al, 2013).…”

Section: Signal Modelmentioning

confidence: 99%

Motion Error Compensation for Quad-rotor Miniature Unmanned Aerial Vehicle SAR Imaging

Zhou

Yang

et al. 2016

Proceedings of the 13th International Joint Conference on E-Business and Telecommunications

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Quad-rotor miniature unmanned aerial vehicle (QMUAV) synthetic aperture radar (SAR) is an ultra-small airborne SAR system. Because of lowing flying altitude and small size constraints, the motion errors of QMUAV-SAR are very complicated which introduces difficulty to the QMUAV-SAR imaging processing. To deal with this problem, an effective motion compensation approach for QMUAV-SAR is proposed. By establishing the relationship between the motion errors and the Doppler parameters of SAR echoes, the motion errors of QMUAV platform are extracted from the estimated Doppler rates. After the majority of the motion error being properly compensated, phase gradient autofocusing (PGA) is employed to estimate and compensate the residual phase errors to further improve the focusing quality of the SAR image. Experimental results are provided and the image quality is evaluated to demonstrate the ability of achieving well focused image and high spacial resolutions of the proposed method.

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Chirp scaling algorithm for GEO SAR based on fourth-order range equation

Cited by 27 publications

References 5 publications

A Generalized Chirp-Scaling Algorithm for Geosynchronous Orbit SAR Staring Observations

A Generalized Chirp-Scaling Algorithm for Geosynchronous Orbit SAR Staring Observations

Squint Mode GEO SAR Imaging Using Bulk Range Walk Correction on Received Signals

Motion Error Compensation for Quad-rotor Miniature Unmanned Aerial Vehicle SAR Imaging

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