Radar Cross Section Analysis of Small Group Target

Suenobu, Hiroshi; Tanaka, T.; Takikawa, Michio; Yoneda, Naofumi

doi:10.23919/ursi-emts.2019.8931454

“…Note that this frequency-domain RCS synthesis is similar to the array-factor-based algorithm discussed in [14], [15], where a numerically simulated complex-valued scattering pattern was used to synthesize the RCS of a cluster of multiple targets. The major merit of the image-based RCS synthesis presented in this article compared to the previous work is the availability of the spatial filtering which is a distinctive feature of generating the radar image, as presented in Section III-E.…”

Section: F Frequency-domain Synthesismentioning

confidence: 99%

“…A similar topic was treated in [14], [15], where an RCS pattern of a single metallic aircraft model simulated using a numerical electromagnetic solver was used to synthesize the RCS of a scene containing multiple targets with identical shape. In this previous research work, a complex-valued backscattering pattern of a single target was replicated with multiplication of an appropriate phase factor of the assumed arrangement, and the modified replicas are coherently summed to synthesize the RCS of the multiple targets.…”

Section: Introductionmentioning

confidence: 99%

Image-Based Radar Cross-Section Synthesis for a Cluster of Multiple Static Targets

Watanabe¹

2022

Preprint

0

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*This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. In this article, we propose a novel image-based method for radar cross-section (RCS) prediction of a cluster of multiple static targets by synthesizing replicas of an original radar image. In this approach, we first measure the near-field backscattering of a target and reconstruct a corresponding radar image. Then, modified copies of this image with rotation, translation, and spatial filtering, are generated according to the predefined desired arrangement, and they are coherently summed to create a single synthesized image in which all scattering contributions contained in the modified images are virtually included. Finally, the synthesized image is utilized to predict the far-field RCS of the multiple targets, based on the theory of image-based near-field-to-far-field transformation (NFFFT). By employing the proposed algorithm, we can avoid building multiple test targets, resulting in the reduction of the production costs of them. Moreover, we can easily test several different experimental layouts of the multiple targets without repeating a real measurement. Numerical simulations and experiments are provided to demonstrate the validity of the proposed image-based RCS synthesis.

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“…Digital Object Identifier xxxxx/xxxxx [14], [15], a scene to be measured is not necessarily constituted by a single object, and one may need to evaluate the RCS of a cluster of multiple targets. In this case, different problems arise; that is, costs for manufacturing multiple test objects and effort to try several experiments under different arrangements of the targets.…”

Section: Introductionmentioning

confidence: 99%

“…A similar topic was treated in [14], [15], where an RCS pattern of a single metallic aircraft model simulated using a numerical electromagnetic solver was used to synthesize the RCS of a scene containing multiple targets with identical shape. In this previous research work, a complex-valued backscattering pattern of a single target was replicated with multiplication of an appropriate phase factor of the assumed arrangement, and the modified replicas are coherently summed to synthesize the RCS of the multiple targets.…”

Section: Introductionmentioning

confidence: 99%

Image-Based Radar Cross Section Synthesis for a Cluster of Multiple Static Targets

Watanabe

¹

2023

IEEE Trans. Instrum. Meas.

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“…Digital Object Identifier xxxxx/xxxxx [14], [15], a scene to be measured is not necessarily constituted by a single object, and one may need to evaluate the RCS of a cluster of multiple targets. In this case, different problems arise; that is, costs for manufacturing multiple test objects and effort to try several experiments under different arrangements of the targets.…”

Section: Introductionmentioning

confidence: 99%

Image-Based Radar Cross-Section Synthesis for a Cluster of Multiple Static Targets

Watanabe¹

2022

Preprint

0

View full text Add to dashboard Cite

*This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. In this article, we propose a novel image-based method for radar cross-section (RCS) prediction of a cluster of multiple static targets by synthesizing replicas of an original radar image. In this approach, we first measure the near-field backscattering of a target and reconstruct a corresponding radar image. Then, modified copies of this image with rotation, translation, and spatial filtering, are generated according to the predefined desired arrangement, and they are coherently summed to create a single synthesized image in which all scattering contributions contained in the modified images are virtually included. Finally, the synthesized image is utilized to predict the far-field RCS of the multiple targets, based on the theory of image-based near-field-to-far-field transformation (NFFFT). By employing the proposed algorithm, we can avoid building multiple test targets, resulting in the reduction of the production costs of them. Moreover, we can easily test several different experimental layouts of the multiple targets without repeating a real measurement. Numerical simulations and experiments are provided to demonstrate the validity of the proposed image-based RCS synthesis.

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Radar Cross Section Analysis of Small Group Target

Cited by 3 publications

References 0 publications

Image-Based Radar Cross-Section Synthesis for a Cluster of Multiple Static Targets

Image-Based Radar Cross-Section Synthesis for a Cluster of Multiple Static Targets

Image-Based Radar Cross Section Synthesis for a Cluster of Multiple Static Targets

Image-Based Radar Cross-Section Synthesis for a Cluster of Multiple Static Targets

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