ISAR imaging of a windmill - measurement and simulation

Li, Chenchen; Yang, Shi-Nine; Líu, Hao

doi:10.1109/eucap.2014.7145513

Cited by 3 publications

(4 citation statements)

References 6 publications

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“…10(b) shows the simplified FEKO simulation model for the windmill. The scattering phenomenology of the windmill has already been discussed in detail in [17] and will not be repeated here.…”

Section: A Windmillmentioning

confidence: 97%

“…In-situ measurement is made at a windmill in Cedar Park, Texas [17]. The eighteen-blade windmill has a rotor diameter of approximately 5 m. Measurement is done at a 45° elevation angle from the radar perspective at a distance of 25 m to the hub.…”

Section: A Windmillmentioning

confidence: 99%

“…Understanding the detailed radar scattering phenomenology of wind turbines is therefore an important step toward assessment and mitigation. Significant efforts have been devoted in the electromagnetics community to simulating, measuring, and analyzing the radar signatures of wind turbines [5]- [17]. To date, the most complete in-situ measurement data set was collected by the Air Force Research Laboratory in 2006 of a wind farm located in Fenner, NY [5,6].…”

Section: Introductionmentioning

confidence: 99%

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In-Situ ISAR Imaging of Wind Turbines

Yang

Líu

2016

IEEE Trans. Antennas Propagat.

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Measurement and processing methodologies are developed to capture the in-situ inverse synthetic aperture radar (ISAR) image of an operating wind turbine. In-situ measurement data of a small three-blade wind turbine are collected using an ultra-wideband (UWB) radar, and the measured signatures are compared to simulation results based on physical optics. The backscattering phenomenology is examined in the sinogram, spectrogram, and ISAR image domains. It is shown that the resulting ISAR images provide revealing geometrical insight into the blade scattering phenomenology that is not as apparent in either the range profile or Doppler spectrogram alone. Subsequently, the same methodologies are applied to generate the in-situ ISAR imagery of an 18-blade windmill and a 1.7 MW utility-class wind turbine.

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“…10(b) shows the simplified FEKO simulation model for the windmill. The scattering phenomenology of the windmill has already been discussed in detail in [17] and will not be repeated here.…”

Section: A Windmillmentioning

confidence: 97%

Section: A Windmillmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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In-Situ ISAR Imaging of Wind Turbines

Yang

Líu

2016

IEEE Trans. Antennas Propagat.

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“…However, carrier-free UWB sensors can compensate for these shortcomings because of their advantages such as high strong anti-interference capability [1], distance resolution [2], low power consumption [3], good electromagnetic penetration [4], and insensitivity to light and climate factors. Carrier-free UWB sensors have been widely used in some fields, such as human movement recognition [5], ground-penetrating mining [6], micro-Doppler [7], medical diagnosis [8], underwater detection [9], SAR imaging [10], network communications [11], and navigation [12]. Existing carrier-free UWB sensor target recognition is mainly applied to human movement recognition and gesture recognition.…”

Section: Introductionmentioning

confidence: 99%

Carrier-Free Ultra-Wideband Sensor Target Recognition in the Jungle Environment

Li,

Zhang,

Zhu

et al. 2024

Remote Sensing

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Carrier-free ultra-wideband sensors have high penetrability anti-jamming solid ability, which is not easily affected by the external environment, such as weather. Also, it has good performance in the complex jungle environment. In this paper, we propose a jungle vehicle identification system based on a carrier-free ultra-wideband sensor. Firstly, a composite jungle environment with the target vehicle is modeled. From this model, the simulation obtains time-domain echoes under the excitation of carrier-free ultra-wideband sensor signals in different orientations. Secondly, the time-domain signals are transformed into MTF images through the Markov transfer field to show the statistical characteristics of the time-domain echoes. At the same time, we propose an improved RepVGG network. The structure of the RepVGG network contains five stages, which consist of several RepVGG Blocks. Each RepVGG Block is created by combining convolutional kernels of different sizes using a weighted sum. We add the self-attention module to the output of stage 0 to improve the ability to extract the features of the MTF map and better capture the complex relationship between characteristics during training. In addition, a self-attention module is added before the linear layer classification output in stage 4 to improve the classification accuracy of the network. Moreover, a combined cross-entropy loss and sparsity penalty loss function helps enhance the performance and accuracy of the network. The experimental results show that the system can recognize jungle vehicle targets well.

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On simulating the high-resolution radar image of a wind turbine

Líu

2016

2016 10th European Conference on Antennas and Propagation (EuCAP)

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ISAR imaging of a windmill - measurement and simulation

Cited by 3 publications

References 6 publications

In-Situ ISAR Imaging of Wind Turbines

In-Situ ISAR Imaging of Wind Turbines

Carrier-Free Ultra-Wideband Sensor Target Recognition in the Jungle Environment

On simulating the high-resolution radar image of a wind turbine

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