Fast Fourier-Based Implementation of Synthetic Aperture Radar Algorithm for Multistatic Imaging System

Abbasi, Mehryar; Shayei, Ali; Shabany, Mahdi; Kavehvash, Zahra

doi:10.1109/tim.2018.2875769

Cited by 40 publications

(18 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section, we augment the proposed method in [38] according to the terminology and system configuration used throughout this paper. In this study, the complete wideband MIMO array is modeled as a combination of multiple singletone single-input single-output (SISO) multistatic structures.…”

Section: A Enhanced Back Projection Algorithmmentioning

confidence: 99%

“…In this study, the complete wideband MIMO array is modeled as a combination of multiple singletone single-input single-output (SISO) multistatic structures. Using the well-known BPA [7], [36], [38], (6) can be reformulated to recover the reflectivity function p(x, y, z) from the received backscattered data s(x , y T , y R , k) as…”

Section: A Enhanced Back Projection Algorithmmentioning

confidence: 99%

“…This method provides high imaging precision by coherently accumulating the received signal from each transceiver pair at each wavelength, and can be used for arbitrary array configurations. However, its computational complexity, which can be approximated as O(N 5 log N ) [38], is still too high for 3-D MIMO-SAR imaging.…”

Section: A Enhanced Back Projection Algorithmmentioning

confidence: 99%

“…Although the back projection algorithm (BPA) [7], [30], [36], [37] can provide a straightforward solution for arbitrary multistatic array configurations, it suffers from the high computational load in high throughput applications utilizing large MIMO-SAR apertures and wideband sensors. In this paper, the proposed approach in [38] is augmented to improve the performance of the BPA in the SAR axis by solving the problem in the corresponding Fourier domain. The range migration algorithm (RMA) using Fourier-based inversion methods is the most efficient and widely used approach in conventional monostatic SAR imaging for both planar [6], [39] and cylindrical/spherical [29], [40] scanning geometries.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Development and Demonstration of MIMO-SAR mmWave Imaging Testbeds

2020

View full text Add to dashboard Cite

Multiple-input multiple-output (MIMO) radars and synthetic aperture radar (SAR) techniques are well researched and have been effectively combined for many imaging applications ranging from remote sensing to security. Despite numerous studies that apply MIMO concepts to SAR imaging, the design process of a MIMO-SAR system is non-trivial, especially for millimeter-wave (mmWave) imaging systems. Many issues have to be carefully addressed. Besides, compared with conventional monostatic sampling schemes or MIMO-only solutions, efficient image reconstruction methods for MIMO-SAR topologies are more complicated in short-range applications. To address these issues, we present highly-integrated and reconfigurable MIMO-SAR testbeds, along with examples of three-dimensional (3-D) image reconstruction algorithms optimized for MIMO-SAR configurations. The presented testbeds utilize commercially available wideband mmWave sensors and motorized rail platforms. Several aspects of the MIMO-SAR testbed design process, including MIMO array calibration, electrical/mechanical synchronization, system-level verification, and performance evaluation, are described. We present three versions of MIMO-SAR testbeds with different implementation costs and accuracies to provide alternatives for other researchers who want to implement their testbed framework. Several representative examples in various real-world imaging applications are presented to demonstrate the capabilities of the proposed testbeds and algorithms. INDEX TERMS Millimeter-wave (mmWave) radar, multiple-input multiple-output (MIMO) radar, synthetic aperture radar (SAR), frequency-modulated continuous-wave (FMCW), back projection algorithm (BPA), range migration algorithm (RMA), three-dimensional (3-D) imaging, testbed design, calibration.

show abstract

Section: A Enhanced Back Projection Algorithmmentioning

confidence: 99%

Section: A Enhanced Back Projection Algorithmmentioning

confidence: 99%

Section: A Enhanced Back Projection Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Development and Demonstration of MIMO-SAR mmWave Imaging Testbeds

2020

View full text Add to dashboard Cite

show abstract

“…In multistatic SAR, different receivers image from different angles, which can provide observation information from various angles in the imaging area, and achieve application by analyzing the information. In terms of imaging, some scholars have studied the imaging scene of multistatic SAR [12], and some scholars have proposed an imaging algorithm based on fast Fourier transform for multistatic SAR [13]. In the aspect of configuration design, scholars have studied how to use the transformation of geometric configuration to realize image reconstruction [14] and topology design of spaceborneairborne multistatic SAR [15].…”

Section: Introductionmentioning

confidence: 99%

An Antideceptive Jamming Method for Multistatic Synthetic Aperture Radar Based on Collaborative Localization and Spatial Suppression

Wang

Pei

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

In recent years, the research of multistatic synthetic aperture radar (SAR) has become a hot spot because of its great potentials in military and civil applications. However, it is inevitably disturbed by electronic countermeasures. In the multistatic SAR image, the false target caused by transmitting deceptive jamming leads to misjudgment of the image information. In this article, a new antideceptive jamming method for multistatic SAR is proposed. This method can locate the deceptive jammer and effectively suppress it. First of all, the echo model of multistatic SAR in the jamming environment is set up. Based on this model, the relationship expression for the location of jammer is derived. Then, we use the maximally stable extremal region method and the Euclideandistance-based method to detect and identify false target in the multistatic SAR image. By using the location information of false target, receivers, and transmitters, the expression of the jammer localization is solved to locate the jammer. Finally, the minimum variance distortionless response beamforming method and image mosaic method are used to effectively suppress the jamming. The simulation results show that the method is effective.

show abstract