Higher-Order Moving Target Detection for Rotating Scanning Synthetic Aperture Interferometric Radiometer

Chen, Jianfei; Zhang, Sheng; Zhu, Xiao‐Wei

doi:10.2528/pierl18112804

Cited by 2 publications

(2 citation statements)

References 29 publications

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“…The plane OXY is parallel to the plane oxy, and the distance between the two planes is R. The radiation source S is dispersed into N small parts. The distances between the n-th radiation source S n and antennas c and l are R c n and R l n , respectively [13]. According to [16], the visibility function of the antenna can be expressed as:…”

Section: Data Set Acquisition and Trainingmentioning

confidence: 99%

Millimeter Wave Image Super Resolution Using Multichannel Depth Convolution Neural Network

Peng¹,

Chen²,

Liu³

2022

PIER M

Self Cite

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Benefit from the high resolution, penetrating and all-weather advantages of millimeterwave (MMW) imaging, MMW imaging plays an important role in remote sensing, security inspection, navigation, etc. Among the MMW imaging systems, synthetic aperture imaging radiometer (SAIR) utilizes aperture synthetic technology to achieve higher imaging resolution, but the perception information is insufficient, resulting in poor image quality. To improve the image quality of passive SAIR MMW images effectively, we propose a novel multichannel depth convolutional neural network (MDCNN) in this paper. Aiming at the characteristics of original MMW images with more noise in low-frequency information and fewer features in high-frequency information, wavelet transform is incorporated into the MDCNN to obtain the high-and low-frequency components first. Then, dense residual block and skip connection technology are adopted to denoise and enhance target information in the four independent channels respectively. Finally, high-quality MMW images are synthesized by inverse wavelet transform. The simulation results show that the reconstructed images of MDCNN have better image quality (such as image contour and texture details) than other deep learning-based methods.

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Section: Data Set Acquisition and Trainingmentioning

confidence: 99%

Millimeter Wave Image Super Resolution Using Multichannel Depth Convolution Neural Network

Peng¹,

Chen²,

Liu³

2022

PIER M

Self Cite

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show abstract

“…Liu [ 6 ] demonstrated that the root-mean-square error of reconstructed images with targets with rapid brightness temperature (BT) changes, such as tropical cyclones (TCs), was closely related to observation frequency and imaging period. Chen [ 7 ] proposed a method for detecting higher-order moving targets using a rotating scanning SAIR (RS-SAIR) equipped with a linear sparse array. Yang and Hu [ 8 ] utilized the kernel method to predict the observation background by designing a new robust loss function, and a constant false alarm rate (CFAR) detector was used to detect targets.…”

Section: Introductionmentioning

confidence: 99%

Target Detection for Synthetic Aperture Radiometer Based on Satellite Formation Flight

Deng

Wang

Dai

et al. 2023

Sensors

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Synthetic aperture interferometers formed by satellite formations have been adopted to improve spatial resolution. Due to the limited number of satellites and limited integrated time, the use of sparse baselines can result in distorted reconstructed images, which will generate false targets or miss true targets. When detecting a target on the Earth from a geostationary orbit, the target usually occupies only one pixel, and it is almost submerged by noise. Considering the slow-varying characteristics of the observation area, combined with historical observation data and the motion characteristics of the target itself, a target detection method based on multi-frame snapshot images is proposed. Firstly, the observation background is estimated using multi-frame historical data, and background elimination is used to suppress the background noise. Then, potential targets are selected using the local brightness temperature characteristics of the targets. Lastly, the target motion tracks are applied to erase false targets and correct the positions of missed targets. Simulation experiments have been conducted, and the false alarm rate and the missing alarm rate are counted for randomly distributed targets.

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Higher-Order Moving Target Detection for Rotating Scanning Synthetic Aperture Interferometric Radiometer

Cited by 2 publications

References 29 publications

Millimeter Wave Image Super Resolution Using Multichannel Depth Convolution Neural Network

Millimeter Wave Image Super Resolution Using Multichannel Depth Convolution Neural Network

Target Detection for Synthetic Aperture Radiometer Based on Satellite Formation Flight

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