A High-Order Imaging Algorithm for High-Resolution Spaceborne SAR Based on a Modified Equivalent Squint Range Model

Wang, Pengbo; Liu, Wei; Chen, Jie; Niu, Mu; Yang, Wei

doi:10.1109/tgrs.2014.2336241

Cited by 87 publications

(70 citation statements)

References 38 publications

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“…In this paper, 't' and 'r' denote the transmitter and receiver, respectively. After reviewing the studies in the available literature [9,10,16,[38][39][40][41][42][43], we integrate the important results and then show that the flight path of spaceborne SAR can be equivalent to a curved path, which is mainly caused by the curved orbit and the rotating planetary surface and the flight path of the missile can be described by using the motion parameters, including the velocity, acceleration, and higher-order parameters, obtained from the information provided by the inertial navigation system (INS). According to the imaging geometry, the instantaneous slant range |r(η, A)| of the point A is expressed as:…”

Section: Geometric Modelmentioning

confidence: 99%

Modeling and Precise Processing for Spaceborne Transmitter/Missile-Borne Receiver SAR Signals

et al. 2019

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The spaceborne transmitter/missile-borne receiver (ST/MR) synthetic aperture radar (SAR) could provide several unique advantages, such as wide coverage, unrestricted geography, a small detection probability of the missile, and forward-looking imaging. However, it is also accompanied by problems in imaging, including geometric model establishment and focusing algorithm design. In this paper, an ST/MR SAR model is first presented and then the flight-path constraint, characterized by geometric configurations, is derived. Considering the impacts brought about by the maneuvers of the missile, a non-'Stop-Go' mathematical model is devised and it can avoid the large errors introduced by the acceleration, which is neglected in the traditional model. Finally, a two-dimensional (2-D) scaling algorithm is developed to focus the ST/MR data. Without introducing any extra operations, it can greatly remove the spatial variations of the range, azimuth, and cross-coupling phases simultaneously and entirely in the 2-D hybrid domain. Simulation results verify the effectiveness of the proposed model and focusing approach. missile-borne SAR will inevitably bring some limitations, such as the large power antenna and high probability of being detected. Moreover, the monostatic SAR is incapable of forward-looking imaging, which seriously limits its applicability in the military field because information in the movement direction cannot be obtained directly. Compared with the monostatic missile-borne SAR, the ST/MR SAR has many advantages and they are:(1) The large-maneuver and receiving-only features of the missile-borne receiver reduce the detection probability. The corresponding anti-interference and anti-interception are greatly improved in the ST/MR SAR system. (2) The radar antenna, installed on the missile-borne platform, is used to receive the echo signals without a transmitting function, which indicates that a large power device can be avoided in the missile system to greatly save space and costs.(3) Spaceborne transmitter has the characteristics of wide coverage, unrestricted geography, net flexibility, and a high revisiting-frequency, which could provide some degrees of freedom (DOFs) in target area selection, flight trajectories, and number of missile-borne receivers. (4) By setting the transmitter and receiver on different platforms with a special style, the non-complete coupling areas between iso-range and iso-Doppler lines could be formed in front of missile, which means that the missile has the capability of forwarding-looking imaging.Note that these advantages for the ST/MR SAR also hold for other BiSAR systems, such as the spaceborne/airborne SAR and the airborne BiSAR, which are of special significance for the missiles mainly applied in the military fields. Generally, these common features of the BiSAR can avoid disadvantages inherent in the monostatic missile-borne SAR and make the ST/MR SAR a flexible and effective tool for information retrieval [11][12][13][14][15]. However, there are also a number of problems broug...

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Section: Geometric Modelmentioning

confidence: 99%

Modeling and Precise Processing for Spaceborne Transmitter/Missile-Borne Receiver SAR Signals

et al. 2019

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“…However, for the MEO SAR, the straight path approximation cannot properly fit the actual path and another degree of freedom should be used to make the range model more accurate. To improve the precision of the range model, an additional cubic component and quartic component are introduced in the range equation, 12 as shown below: Fig. 1 Geometry of a typical spaceborne synthetic aperture radar (SAR).…”

Section: Range Modelmentioning

confidence: 99%

“…In this paper, a modified equivalent squint range model (MESRM), which was employed in our work in Ref. 12, is used as the range model for MEO SAR.…”

Section: Introductionmentioning

confidence: 99%

Higher order nonlinear chirp scaling algorithm for medium Earth orbit synthetic aperture radar

Wang

Liu

Chen

et al. 2015

J. Appl. Remote Sens

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Abstract. Due to the larger orbital arc and longer synthetic aperture time in medium Earth orbit (MEO) synthetic aperture radar (SAR), it is difficult for conventional SAR imaging algorithms to achieve a good imaging result. An improved higher order nonlinear chirp scaling (NLCS) algorithm is presented for MEO SAR imaging. First, the point target spectrum of the modified equivalent squint range model-based signal is derived, where a concise expression is obtained by the method of series reversion. Second, the well-known NLCS algorithm is modified according to the new spectrum and an improved algorithm is developed. The range dependence of the twodimensional point target reference spectrum is removed by improved CS processing, and accurate focusing is realized through range-matched filter and range-dependent azimuth-matched filter. Simulations are performed to validate the presented algorithm. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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“…Thanks to its superior characteristics, including all-weather day-and-night observation, high-resolution imaging capability, and so forth, synthetic aperture radar (SAR) imaging plays an indispensable role in both military and civil applications. Essentially, SAR is an active microwave detection device for remote sensing, which is diversely utilized in geographical surveying, environment and Earth system monitoring, climate change research [1,2], and more. The combination of the electromagnetic scattering mechanism and a coherent imaging system enables SAR images to contain rich features, which provides important information for target recognition [3].…”

Section: Introductionmentioning

confidence: 99%

Multi-Stream Convolutional Neural Network for SAR Automatic Target Recognition

Zhao

Zou

et al. 2018

Remote Sensing

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Despite the fact that automatic target recognition (ATR) in Synthetic aperture radar (SAR) images has been extensively researched due to its practical use in both military and civil applications, it remains an unsolved problem. The major challenges of ATR in SAR stem from severe data scarcity and great variation of SAR images. Recent work started to adopt convolutional neural networks (CNNs), which, however, remain unable to handle the aforementioned challenges due to their high dependency on large quantities of data. In this paper, we propose a novel deep convolutional learning architecture, called Multi-Stream CNN (MS-CNN), for ATR in SAR by leveraging SAR images from multiple views. Specifically, we deploy a multi-input architecture that fuses information from multiple views of the same target in different aspects; therefore, the elaborated multi-view design of MS-CNN enables it to make full use of limited SAR image data to improve recognition performance. We design a Fourier feature fusion framework derived from kernel approximation based on random Fourier features which allows us to unravel the highly nonlinear relationship between images and classes. More importantly, MS-CNN is qualified with the desired characteristic of easy and quick manoeuvrability in real SAR ATR scenarios, because it only needs to acquire real-time GPS information from airborne SAR to calculate aspect differences used for constructing testing samples. The effectiveness and generalization ability of MS-CNN have been demonstrated by extensive experiments under both the Standard Operating Condition (SOC) and Extended Operating Condition (EOC) on the MSTAR dataset. Experimental results have shown that our proposed MS-CNN can achieve high recognition rates and outperform other state-of-the-art ATR methods.

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A High-Order Imaging Algorithm for High-Resolution Spaceborne SAR Based on a Modified Equivalent Squint Range Model

Cited by 87 publications

References 38 publications

Modeling and Precise Processing for Spaceborne Transmitter/Missile-Borne Receiver SAR Signals

Modeling and Precise Processing for Spaceborne Transmitter/Missile-Borne Receiver SAR Signals

Higher order nonlinear chirp scaling algorithm for medium Earth orbit synthetic aperture radar

Multi-Stream Convolutional Neural Network for SAR Automatic Target Recognition

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