MIMO‐SAR waveform separation based on inter‐pulse phase modulation and range‐Doppler decouple filtering

Meng, Cui; Xu, Jia; Xia, X.-G.; Li, Teng; Mao, Erke; Yang, Jian; Peng, Yingning

doi:10.1049/el.2013.0016

Cited by 44 publications

(21 citation statements)

References 5 publications

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“…However, for scenes with extended targets, the SAR image will be seriously blurred. To solve this problem, scientists and engineers have done a lot of beneficial research and experiments on antenna configuration and signal processing and have built solid foundation for the engineering realization of MIMO SAR [17][18][19][20][21]. After oscilloscope sampling, we get the baseband data of echoes via quadrature demodulation and obtain I and Q signals.…”

Section: Data Processingmentioning

confidence: 99%

MIMO SAR Using Orthogonal Coding: Design, Performance Analysis, and Verifications

Lin

Fan

Jiang

et al. 2015

International Journal of Antennas and Propagation

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Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is a promising technology in radar imaging which provides a better balance of azimuth resolution and swath width compared with traditional single-input single-output (SISO) SAR. It has the potential to help scientists and engineers to design ambitious SAR system with higher resolution and wider swath. This paper studies the principle of MIMO SAR using orthogonal coding waveform and then provides the performance analysis in resolution and swath width. By using orthogonal coding waveform, lower channel interference is obtained, which makes MIMO SAR achieve wider unambiguous range swath and lower azimuth ambiguity. Simulations are carried out by means of the system parameters of real spaceborne SAR platform. A ground-based MIMO SAR imaging system with up and down chirp modulation is also designed. The performances of MIMO SAR and SISO SAR are compared, and the validity and advantage of MIMO SAR are verified.

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Section: Data Processingmentioning

confidence: 99%

MIMO SAR Using Orthogonal Coding: Design, Performance Analysis, and Verifications

Lin

Fan

Jiang

et al. 2015

International Journal of Antennas and Propagation

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“…This contradiction may become serious, especially for the spacebore SAR due to the large imaging swath and underwater SAS due to low sound propagation speed. To solve this problem, multiple elevation beams (MEB) [3,4] technique, multiple phase center (MPC) [5,6] technique and multiple-input and multiple-output (MIMO) [7,8] technique have been adopted with multiple beams, T/R elements or transmitting waveforms. Nevertheless, these solutions may inevitably increase the hardware complexity and system expense, and these follow-on expenses may not be acceptable in some scenarios, e.g., underwater sonar imaging with limited loads.…”

Section: Introductionmentioning

confidence: 99%

Wideband underwater sonar imaging via compressed sensing with scaling effect compensation

Yan

Xia

et al. 2015

Sci. China Inf. Sci.

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By exploiting the sparsity of the imaging scene, compressed sensing (CS) imaging may provide an effective solution to cope with the tradeoff of high azimuth resolution and wide swath in synthetic aperture sonar imaging. However, existing CS imaging methods are based on narrowband signal model and the scaling effect on the echoes is normally omitted, which may seriously affect the ultimate image reconstruction performance. This paper establishes the wideband CS underwater sonar imaging model at first, where the scaling effect and Doppler frequency shift are jointly considered. Furthermore, two wideband CS imaging approaches are discussed in uniform scale-range space and velocity-range space, respectively. Besides, modified 1 -norm minimization algorithms are proposed for the scene reconstruction in velocity-range space. Finally, numerical experiments are provided to demonstrate the effectiveness of the proposed model and the reconstruction algorithms.

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“…To cope with the aforementioned challenge, we have proposed an inter-pulse phase modulation and range-Doppler decouple filtering in [11] to eliminate the cross-correlation noise among multiple orthogonal phase-coded waveforms in MIMO-SAR. Nevertheless, it needs high pulse repetition frequency to separate the multiple waveforms in Doppler frequency domain.…”

Section: Introductionmentioning

confidence: 99%

Multiple input and multiple output synthetic aperture radar multiple waveform separation based on oblique projection in same frequency coverage

Meng

Liu

et al. 2015

IET Radar, Sonar & Navigation

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In multiple input and multiple output synthetic aperture radar (MIMO-SAR) the unwanted cross-correlation output sexist inevitably in the superposed echoes of multiple transmitted orthogonal waveforms in the same frequency coverage, which may deteriorate the quality of the reconstructed SAR image because of the high synthetic integrated sidelobe level (SISL). In this study, a novel signal decomposition based on oblique projection (SDOP) method is proposed to suppress the cross-correlation outputs. At first, the superposed echo of each receiver is modelled as a linear-combined vector of transmitted multiple waveforms. Then, the echo of each transmitted waveform is obtained by signal decomposition on the combined vector via SDOP, respectively. Besides, two new metrics, that is, synthetics integrated sidelobe level ratio improved factor and integrated sidelobe level ratio loss factor, are also proposed to assess the separation performance. It is found that the cross-correlation can be effectively suppressed among multiple waveforms via low-complexity projection operators and the output signal noise ratio can be remarkably improved, accordingly. Finally, the numerical experiments are also provided to demonstrate the effectiveness of the proposed method.

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MIMO‐SAR waveform separation based on inter‐pulse phase modulation and range‐Doppler decouple filtering

Cited by 44 publications

References 5 publications

MIMO SAR Using Orthogonal Coding: Design, Performance Analysis, and Verifications

MIMO SAR Using Orthogonal Coding: Design, Performance Analysis, and Verifications

Wideband underwater sonar imaging via compressed sensing with scaling effect compensation

Multiple input and multiple output synthetic aperture radar multiple waveform separation based on oblique projection in same frequency coverage

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