Multiple-input multiple-output synthetic aperture radar antenna arrangement for wide-swath remote sensing

2015 ◽  
Vol 9 (1) ◽  
pp. 094097 ◽  
Author(s):  
Huaizong Shao ◽  
Wen-Qin Wang
Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4839
Author(s):  
Kong ◽  
Xu

A fully-polarimetric unitary multiple signal classification (UMUSIC) tomography algorithm is proposed, which can be used for acquiring high-resolution three-dimensional (3D) imagery, in a polarimetric multiple-input multiple-output synthetic aperture radar (MIMO-SAR) with a small number of baselines. In terms of the elevation resolution, UMUSIC provides an improvement over standard MUSIC by utilizing the conjugate of the complex sample data and converting the complex covariance matrix into a real matrix. The combination of UMUSIC and fully-polarimetric data permits a further reduction of the noise of the sample covariance matrix, which is obtained through pixel averaging of multiple two-dimensional (2D) images. Considering the consistency of four polarizations, this algorithm not only makes scattering centers have the same estimated height in four polarizations, but it also improves the estimation accuracy. Simulation results show that this algorithm outperforms the popular distributed compressed sensing (DCS). Image processing of measured data of an aircraft model using a multiple-input multiple-output synthetic aperture radar (MIMO-SAR) with six baselines is presented to validate the proposed algorithm.


2016 ◽  
Vol 2016 ◽  
pp. 1-14
Author(s):  
Hongbo Mo ◽  
Wei Xu ◽  
Zhimin Zeng

The multiple-input multiple-output (MIMO) technique can improve the high-resolution wide-swath imaging capacity of synthetic aperture radar (SAR) systems. Beamspace MIMO-SAR utilizes multiple subpulses transmitted with different time delays by different transmit beams to obtain more spatial diversities based on the relationship between the time delay and the elevation angle in the side-looking radar imaging geometry. This paper presents a beamspace MIMO-SAR imaging approach, which takes advantage of real time digital beamforming (DBF) with null steering in elevation and azimuth multichannel raw data reconstruction. Echoes corresponding to different subpulses in the same subswath are separated by DBF with null steering onboard, while echoes received and stored by different azimuth channels are reconstructed by multiple Doppler reconstruction filters on the ground. Afterwards, the resulting MIMO-SAR raw data could be equivalent to the raw data of the single-channel burst mode, and classical burst mode imaging algorithms could be adopted to obtain final focused SAR images. Simulation results validate the proposed imaging approach.


2019 ◽  
Vol 11 (5) ◽  
pp. 533 ◽  
Author(s):  
Aaron Diebold ◽  
Mohammadreza Imani ◽  
David Smith

The correlation-based synthetic aperture radar imaging technique, termed radar coincidence imaging, is extended to a fully multistatic multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) configuration. Within this framework, we explore two distinct processing schemes: incoherent processing of intensity data, obtained using asynchronous receivers and inspired by optical ghost imaging works, and coherent processing with synchronized array elements. Improvement in resolution and image quality is demonstrated in both cases using numerical simulations that model an airborne MIMO SAR system at microwave frequencies. Finally, we explore methods for reducing measurement times and computational loads through compressive and gradient image reconstruction using phaseless data.


Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3580 ◽  
Author(s):  
Jie Wang ◽  
Ke-Hong Zhu ◽  
Li-Na Wang ◽  
Xing-Dong Liang ◽  
Long-Yong Chen

In recent years, multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems, which can promote the performance of 3D imaging, high-resolution wide-swath remote sensing, and multi-baseline interferometry, have received considerable attention. Several papers on MIMO-SAR have been published, but the research of such systems is seriously limited. This is mainly because the superposed echoes of the multiple transmitted orthogonal waveforms cannot be separated perfectly. The imperfect separation will introduce ambiguous energy and degrade SAR images dramatically. In this paper, a novel orthogonal waveform separation scheme based on echo-compression is proposed for airborne MIMO-SAR systems. Specifically, apart from the simultaneous transmissions, the transmitters are required to radiate several times alone in a synthetic aperture to sense their private inner-aperture channels. Since the channel responses at the neighboring azimuth positions are relevant, the energy of the solely radiated orthogonal waveforms in the superposed echoes will be concentrated. To this end, the echoes of the multiple transmitted orthogonal waveforms can be separated by cancelling the peaks. In addition, the cleaned echoes, along with original superposed one, can be used to reconstruct the unambiguous echoes. The proposed scheme is validated by simulations.


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