2014
DOI: 10.1007/s11432-014-5233-2
|View full text |Cite
|
Sign up to set email alerts
|

MIMO-SAR waveforms separation based on virtual polarization filter

Abstract: The unwanted coupling exists inevitably among multiple orthogonal waveforms in a same frequency area for multiple-input and multiple-output synthetic aperture radar (MIMO-SAR). In this paper, a new polarized MIMO-SAR model is established with two transmitting antennas and multiple receiving antennas at first. Then, a virtual polarization filter (VPF) is proposed to separate superposed returns caused by multiple transmitted waveforms based on detection on the polarized parameters via particle swarm optimizer (P… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

0
10
0

Year Published

2015
2015
2021
2021

Publication Types

Select...
7

Relationship

6
1

Authors

Journals

citations
Cited by 9 publications
(10 citation statements)
references
References 14 publications
0
10
0
Order By: Relevance
“…Meanwhile, the cross-track interferometry synthetic aperture radar (XTI-SAR) is usually used for the digital elevation model (DEM) generation [16,17,18] in the side-looking application because the interferometry phases among cross-track multiple receivers are sensitive to the target’s height. Nevertheless, few studies can be found on GMTI for XTI-SAR, though many real systems with cross-baselines still only have strong demands on the GMTI [19,20,21,22,23,24,25,26,27,28]. For example, the airborne navigation or fire-control radars are normally mounted on the plane nose with a forward-looking array antenna, where the receivers are all distributed in the plane perpendicular to the flying track.…”
Section: Introductionmentioning
confidence: 99%
“…Meanwhile, the cross-track interferometry synthetic aperture radar (XTI-SAR) is usually used for the digital elevation model (DEM) generation [16,17,18] in the side-looking application because the interferometry phases among cross-track multiple receivers are sensitive to the target’s height. Nevertheless, few studies can be found on GMTI for XTI-SAR, though many real systems with cross-baselines still only have strong demands on the GMTI [19,20,21,22,23,24,25,26,27,28]. For example, the airborne navigation or fire-control radars are normally mounted on the plane nose with a forward-looking array antenna, where the receivers are all distributed in the plane perpendicular to the flying track.…”
Section: Introductionmentioning
confidence: 99%
“…The source number and direction of arrival (DOA) estimation are two important subjects in array signal processing [1,2]. Many algorithms for estimating these parameters have been proposed in the past decades [3][4][5][6][7]. The common approach for determining the source number is to use a certain information theoretic criterion [3,4] in an additive white Gaussian noise (AWGN) environment, e.g., the AIC and MDL criteria.…”
Section: Dear Editormentioning
confidence: 99%
“…The common approach for determining the source number is to use a certain information theoretic criterion [3,4] in an additive white Gaussian noise (AWGN) environment, e.g., the AIC and MDL criteria. Conventional DOA estimation algorithms can be roughly classified into two types, beamforming techniques and eigenstructure-based methods [4][5][6][7], such as the Capon, MUSIC and Root-MUSIC algorithms. In addition, the mCapon method [5] has been proposed to improve the resolution performance of the Capon algorithm by using an adjustable power parameter m.…”
Section: Dear Editormentioning
confidence: 99%
See 1 more Smart Citation
“…Multifunctional SAR with large-area static scene imaging and ground moving target indication (SAR/GMTI) has drawn much more attentions in recent past decades [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]. In the most of applications, not only the point moving targets but also the distributed moving targets are interested.…”
Section: Introductionmentioning
confidence: 99%