Recently, extensive convolutional neural network (CNN)-based methods have been used for real-time remote sensing image processing system. However, the huge storage requirement for model and input image bring a great c...
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Convolutional Neural Network (CNN) is an algorithm widely used in the field of deep learning. Due to the large number of intensive parallel data operations, the use of CPU to implement the CNN serially consumes too mu...
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Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. real-time signal and information processor is an important module for real-time positioning, imaging, detectio...
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Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. real-time signal and information processor is an important module for real-time positioning, imaging, detection and recognition of targets. With the development of ultra-wideband technology, synthetic aperture technology, signal and informationprocessingtechnology, the radar coverage, detection accuracy and resolution have been greatly improved, especially in terms of one-dimensional (1D) high-resolution radar detection, tracking, recognition, and two-dimensional (2D) synthetic aperture radar imaging technology. Meanwhile, for the application of radar detection and remote sensing with high resolution and wide swath, the amount of data has been greatly increased. Therefore, the radar is required to have low-latency and real-timeprocessing capability under the constraints of size, weight and power consumption. This paper systematically introduces the new technology of high resolution radar and real-time signal and informationprocessing. The key problems and solutions are discussed, including the detection and tracking of 1D high-resolution radar, the accurate signal modeling and wide-swath imaging for geosynchronous orbit synthetic aperture radar, and real-time signal and informationprocessing architecture and efficient algorithms. Finally, the latest research progress and representative results are presented, and the development trends are prospected.
This study presents a novel super-resolution directions of arrival (DOA) estimation method for mechanical scanning radar by using the advanced compressive sensing algorithm. This method is implemented by constructing ...
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Most existing algorithms in high-resolution range profile recognition focus on the closed set cases, where the test sample is from a known class. However, a sample could be drawn from unknown classes in realistic scen...
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Polarimetric information is of great importance for radar target recognition. Conventional polarimetric features are hand-designed based on scattering mechanism. In this study, a novel polarimetric target recognition ...
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Multi-scale object detection in optical remote sensing imagery is a challenging task due to the varied object scales. Existed state-of-art object detection methods have achieved significant growth. However, most of th...
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ISBN:
(数字)9781728163741
ISBN:
(纸本)9781728163758
Multi-scale object detection in optical remote sensing imagery is a challenging task due to the varied object scales. Existed state-of-art object detection methods have achieved significant growth. However, most of the methods are based on default anchors, which need to be predefined. The multi-scale object detection accuracy still needs to be improved, especially for small and dense objects. To improve the robustness of the detection algorithm and the performance of multi-scale object detection, a novel anchor-free multi-scale object detection method Feature Enhanced CenterNet is proposed in this paper. First, we use the “encoder-decoder” structure and introduce horizontal connections to enhance feature representation capabilities. Second, an context-aware up-sampling method is proposed to obtain feature maps with suitable scale. To demonstrate the performance of the proposed method, we perform abundant experiments on the public remote sensing datasets. The experimental results demonstrate the robustness and effectiveness of the proposed method.
The architecture and processing algorithm of mainlobe interference suppression method is described for nulling the signal from mainlobe electronic jammer and multiple sidelobe electronic jammers while maintaining mono...
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This study analyses the radar fluctuating target detection in G0-distributed clutter using dynamic programming - track before detect (DP-TBD) algorithm. G0-distributed clutter is often used to fit the complex circumst...
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Target detection and recognition are two important parts in image processing. As it is known to authors, target detection in synthetic aperture radar (SAR) image is usually processed on two-dimension, which is more co...
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