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A Unified Multimode SAR Raw Signal Simulation Method Based on Acquisition Mode Mutation | IEEE Journals & Magazine | IEEE Xplore

A Unified Multimode SAR Raw Signal Simulation Method Based on Acquisition Mode Mutation


Abstract:

Raw signal simulators for synthetic aperture radar (SAR) in different acquisition modes have been studied individually. This letter is dedicated to presenting a method fo...Show More

Abstract:

Raw signal simulators for synthetic aperture radar (SAR) in different acquisition modes have been studied individually. This letter is dedicated to presenting a method for simulating multimode SAR raw signal in a unified framework. To this end, we first simulate stripmap SAR raw signal, and then mutate the raw signal from stripmap mode into the desired acquisition mode. The acquisition mode mutation is implemented by azimuth-time-variant and range-frequency-dependent bandpass filtering. While processing in range-frequency domain brings forth high accuracy, processing in azimuth-time domain makes the method applicable for flexible antenna steering laws specified by multiple SAR acquisition modes, such as staring spotlight mode, sliding spotlight mode, and terrain observation by progressive scans mode. The proposed method is validated by the simulation results.
Published in: IEEE Geoscience and Remote Sensing Letters ( Volume: 14, Issue: 8, August 2017)
Page(s): 1233 - 1237
Date of Publication: 31 May 2017

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I. Introduction

Raw signal simulators for synthetic aperture radar (SAR) are useful tools for the development of SAR systems, innovation of imaging formation algorithms, educational purposes, and so on. As different SAR acquisition modes have been proposed, such as stripmap mode, terrain observation by progressive scans (TOPS) mode, staring spotlight mode, and sliding spotlight mode, study on multimode SAR raw signal simulation draws wide interest. Raw signal simulators for different SAR acquisition modes have been studied individually [1]–[4].

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1.
G. Franceschetti, M. Migliaccio, D. Riccio and G. Schirinzi, "SARAS: A synthetic aperture radar (SAR) raw signal simulator", IEEE Trans. Geosci. Remote Sens., vol. 30, no. 1, pp. 110-123, Jan. 1992.
2.
G. Franceschetti, R. Guida, A. Iodice, D. Riccio and G. Ruello, "Efficient simulation of hybrid stripmap/spotlight SAR raw signals from extended scenes", IEEE Trans. Geosci. Remote Sens., vol. 42, no. 11, pp. 2385-2396, Nov. 2004.
3.
A. S. Khwaja, L. Ferro-Famil and E. Pottier, "Efficient SAR raw data generation for anisotropic urban scenes based on inverse processing", IEEE Geosci. Remote Sens. Lett., vol. 6, no. 4, pp. 757-761, Oct. 2009.
4.
W. Xu, Y. Deng, F. Feng, Y. Liu and G. Li, "TOPS mode raw data generation from wide-beam SAR imaging modes", IEEE Geosci. Remote Sens. Lett., vol. 9, no. 4, pp. 720-724, Jul. 2012.
5.
Y. Liu, W. Wang, X. Pan, Q. Fu and G. Wang, "Inverse omega-K algorithm for the electromagnetic deception of synthetic aperture radar", IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 9, no. 7, pp. 3037-3049, Jul. 2016.
6.
T. S. Yeo, N. L. Tan, Y. H. Lu and C. B. Zhang, "A stripmap to spotlight data converting algorithm", Proc. IEEE Int. Geosci. Remote Sens. Symp. (IGARSS), pp. 1168-1170, Jul. 1998.
7.
P. Prats, R. Scheiber, J. Mittermayer, A. Meta and A. Moreira, "Processing of sliding spotlight and TOPS SAR data using baseband azimuth scaling", IEEE Trans. Geosci. Remote Sens., vol. 48, no. 2, pp. 770-780, Feb. 2010.
8.
Y. Liu, X. Pan, Z. Gu, W. Wang and G. Wang, "Raw signal simulator for SAR with trajectory deviation based on spatial spectrum analysis" in IEEE Trans. Geosci. Remote Sens.
9.
Imagery: Airbus Defence and Space, May 2017, [online] Available: http://www.geo-airbusds.com/en/23-sample-imagery.
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References

References is not available for this document.