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检索条件"任意字段=Proceedings of the 1999 Signal and Data Processing of Small Targets"

共 904 条记录，以下是1-10 订阅

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Machine learning classifier for marine radar small targets based on normalization features 16

Machine learning classifier for marine radar small targets b...

引用

16th International Conference on signal processing Systems, ICSPS 2024

作者： Zhao, Zi-Jian Shui, Peng-Lang National Key Laboratory of Radar Signal Processing Xidian University China

ISBN: (纸本)9781510689251

targets on the sea surface are of great concern, especially the classification of small targets, which is crucial for marine safety. Therefore, we propose a machine learning classifier for marine radar small targets based on normalization features, which can effectively classify targets with small radar cross section (RCS) and signal-to-clutter ratio (SCR) on the sea surface. We standardize the radar parameters because different radars have different system parameters, resulting in limited generalization ability of the trained classifier. We extract 9 features from multiple dimensions of the signal such as time domain, frequency domain and time-frequency domain and then classify targets using decision tree (DT) classifier, K-nearest neighbors (KNN) classifier, bootstrap aggregation (Bagging) classifier and adaptive boosting (AdaBoost) classifier. Experimental validation is performed on publicly available IPIX, self-measured radar data and data provided by the South African Council for Scientific and Industrial Research (CSIR), which contains four types of targets: floating ball, floating boats, low-altitude unmanned aerial vehicles (UAVs) and moving speedboats, and the results of the experiments show that the proposed classifier achieves a correct classification accuracy of 0.8537. © 2025 SPIE.

关键词： Marine radar

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Improvement of small Target Detection Algorithm Based on SSD 2

Improvement of Small Target Detection Algorithm Based on SSD

引用

2nd International Conference on signal processing and Intelligent Computing, SPIC 2024

作者： Li, Yuzhi Li, Fang Zhou, Xiaolin Yin, Xiangyang Li, Shuhui Dai, Jinchi Zhang, Ce Shenyang Ligong University Shenyang China Emergency Management Bureau Rizhao China North China Electric Power University Beijing China

ISBN: (纸本)9798350368888

To address the issues of imbalanced target distribution within the dataset and the deficiency of high-level semantic information in the lower-level feature maps for small target detection, this paper proposes a small target detection algorithm grounded in feature fusion. The algorithm builds upon the SSD framework. To enhance the detection background for small targets, a data augmentation technique is employed, bolstering the model's generalization capacity for small and medium-sized targets. To augment the semantic information in the lower-level feature maps, a feature fusion module is incorporated, injecting high-level semantic data into the low-level feature map. Comparative experiments conducted on the dataset demonstrate the algorithm's effectiveness, showing improved overall detection performance and enhanced accuracy for small and medium-sized targets. © 2024 IEEE.

关键词： data enhancement deep learning feature fusion target detection

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Improving the signal-to-Clutter Ratio in Sub-THz Radar Using the Radon Transform

Improving the Signal-to-Clutter Ratio in Sub-THz Radar Using...

引用

International Radar Symposium (IRS)

作者： Harris, Samuel Kumar, Dillon Pirkani, Anum Stove, Andy Hoare, Edward Robertson, Duncan A. Gashinova, Marina Univ Birmingham Sch Elect Elect & Syst Engn Birmingham W Midlands England Univ St Andrews SUPA Sch Phys & Astron St Andrews Fife Scotland

ISBN: (纸本)9798350371109;9788395602092

This paper details the use of the Radon transform for improving small target detection in a marine environment by radar. The data used were collected using a 150 GHz radar that stared at anchored targets in a wave tank which simulated maritime conditions. After transforming range-time profiles of the data, a method was developed in Radon space to easily distinguish between the normative form of the sea clutter and the anomalous forms of the targets, after which the normative form is reduced. The proposed processing technique shows consistent improvements of 10-12 dB in the signal-to-clutter ratio.

关键词： Radon Transform Anomaly detection Radar Sea Clutter Sea Surface Simulation

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FBI-Net: Frequency Band Integration Network for Infrared small Target Segmentation

FBI-Net: Frequency Band Integration Network for Infrared Sma...

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2025 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Xin, Biqiao Li, Qiang Mao, Qianchen Wang, Jinbao Wang, Bingshu School of Software Northwestern Polytechnical University Xi'an China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

ISBN: (纸本)9798350368741

small targets in infrared imagery exhibit challenging characteristics due to their minimal semantic information and the extremely imbalanced distribution between the targets and the background. In this paper, we propose a frequency band integration network to extract salient features of infrared small targets in both the spatial and frequency domains. To excavate the high-frequency features of the small targets, we propose a frequency decoupling-fusion module. To decrease the semantic loss that occurs in deep networks, we propose a semantic injection mechanism to assist in retaining critical information from shallow layers. Experimental results show that our proposed method reaches higher prediction accuracy and robustness in the infrared small target segmentation task compared with other state-of-the-art approaches. © 2025 IEEE.

关键词： Feature Fusion Infrared small Target Segmentation Semantic Injection Wavelet Transformation

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Research on Complex Street View Detection Algorithm Based on YOLOv8 2

Research on Complex Street View Detection Algorithm Based on...

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2nd International Conference on signal processing and Intelligent Computing, SPIC 2024

作者： Du, Haiyang Liu, Jun Shenyang Ligong University School of Automation and Electrical Engineering Shenyang China

ISBN: (纸本)9798350368888

The current street scene is becoming more and more complex, with high pedestrian and vehicular traffic and a large number of targets. Aiming at the problems that the accuracy of the current complex street scene-oriented detection algorithms is not satisfactory and the leakage rate of small targets is unstable, the intelligent detection algorithm YOLOv8s- for complex street scenes is proposed, aiming at the intelligent detection of multi-targets in daily street scenes. This study is based on the target detection model of YOLOv8s, proposing a C2f-DCNv2 module that can sample features flexibly;adding a small target detection layer in the head;and using the Shape IoU loss function. The improved algorithm improves the precision, recall, and average accuracy by 2.2%, 3.6%, and 5.0%, respectively, compared with the initial algorithm, and these experimental data validate that this study can have a good performance when targeting the detection task of complex street scenes. © 2024 IEEE.

关键词： deformable convolution shape-IoU small target detection street view detection YOLOv8

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Long-time Adaptive Coherent Detection of small targets in Sea Clutter using Inversion of Block Tridiagonal Covariance Matrices 15

Long-time Adaptive Coherent Detection of Small Targets in Se...

引用

15th International Conference on signal processing Systems, ICSPS 2023

作者： Zhang, Xiaojun Xue, Yufan Shui, Penglang National Key Laboratory of Radar Signal Processing Xidian University China

ISBN: (纸本)9781510675056

Low-velocity small target detection in maritime surveillance radars is always a challenging task. Low signal-to-clutter ratio requires long-time coherent integration to obtain enough gain of target returns. However, long-time coherent integration encounters insufficient secondary data due to the spatial inhomogeneity of sea clutter. In this paper, considering the decorrelation time of speckle component of sea clutter short up to a dozen of milliseconds, the spherical invariant random vector (SIRV) model with block tridiagonal speckle covariance matrix and the inverse Gamma distributed texture is proposed to model sea clutter sequences in several tenths of a second. In this model, a long-time adaptive generalized likelihood ratio test with linear threshold detector (GLRT-LTD) is constructed. Owing to the block tridiagonal structure of speckle covariance matrices, the adaptive detection requires much less reference cells for speckle covariance matrix estimation and much lower computational cost for its inversion. The proposed detector is verified by an X-band CSIR radar database with low-velocity small boats as test targets. The experimental result shows that it obtains competitive detection performance in comparison with the state-of-the-art detectors. © 2024 SPIE.

关键词： Covariance matrix

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Sixteenth International Conference on signal processing Systems, ICSPS 2024

Sixteenth International Conference on Signal Processing Syst...

引用

16th International Conference on signal processing Systems, ICSPS 2024

ISBN: (纸本)9781510689251

The proceedings contain 197 papers. The topics discussed include: variational modal decomposition based on whale optimization algorithm for vital signs detection of FMCW radar;sea surface small target detection using tri-median normalized doppler spectrum feature;a physical cluster-based passive scatterer detection method in ISAC systems;on detection of moving weak targets using MIMO continuous active sonar and Doppler filtering;design of optical testing turntable data acquisition system based on LabVIEW;AOA /TDOA location technology of weak satellite signal based on satellite-ground cooperation;bearing-crossing localization technology for UAV target based on signal characteristics;and separation and localization of multiple bat signals using frequency domain beamforming and dual-array-localization method.

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small animal intrusion detection based on RAFT

Small animal intrusion detection based on RAFT

引用

2024 International Conference on Image, signal processing, and Pattern Recognition, ISPP 2024

作者： Li, Xiuguang He, Ninghui Sha, Weiyan Zhou, Xiu Ma, Bo Liu, Rui State Grid Ningxia Electric Power Co. Ltd. Electric Power Research Institute Ningxia Hui Autonomous Region Yinchuan City750001 China Beijing Smartchip Microelectronics Technology Company Limited BeiJing City100000 China

ISBN: (纸本)9781510680425

Due to the variety, size and shape of the invasive animals in substation, the general target detection and case segmentation tasks are often faced with the problems of fewer data and lack of *** flow estimation can accurately detect the boundary of the moving object through the change of optical flow during the moving process of the *** can effectively detect boundaries for small animals moving at low ***, RAFT for small animal intrusion detection can not only effectively eliminate the interference of non-invasive objects, but also cancel the range of intrusion targets, and improve the generalization ability of moving object intrusion *** experimental results show that the detection effect is good for small invasive animals with low speeds. © 2024 SPIE.

关键词： Invertebrates

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Research and Implementation of Radar signal processing Algorithm for FPGA-Based DBF System

Research and Implementation of Radar Signal Processing Algor...

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2023 IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications, IMWS-AMP 2023

作者： Chen, Shuqiong Xu, Wenwen Xu, Dalong Wang, Hao Cao, Jianyin Nanjing University of Science and Technology 200 Xiaolingwei Street Nanjing210094 China

ISBN: (纸本)9798350308761

In order to address the issue of low energy echoes from 'low, slow, small' targets, this paper investigates a signal processing system with FPGA as the core architecture. The real-time signal processing for 64 channels and wideband-narrowband pulse echoes are achieved in this paper. Besides, DBF is utilized in the elevation dimension, providing advantages such as a small blind zone, the ability to detect and track targets at various distances, as well as simultaneous formation of multiple beams. This real-time radar processing system, compared to traditional FPGA+DSP architecture phased-array radars, offers advantages of high-speed data transmission, high parallelism, high stability, and high reliability. © 2023 IEEE.

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A small target detection algorithm for aerial image with improved YOLOv5 3

A small target detection algorithm for aerial image with imp...

引用

3rd International Conference on Electronic Information Engineering, Big data, and Computer Technology, EIBDCT 2024

作者： Xue, Xianli Jiao, Weidong Zhang, Siyuan Qu, Wenkang Tianjin Key Laboratory of Intelligent Signal and Lmage Processing Civil Aviation University of China TIANJIN300300 China

ISBN: (纸本)9781510680449

The problem of complex backgrounds, dramatic changes in the scale of objects and the presence of a large number of dense small targets in the UAV aerial images. In this study, a detection algorithm for small targets is proposed based on the YOLOv5s algorithm. Firstly, a new BottleNeck: C3LK module is designed for the C3 module using depthwise separable convolution to construct a large convolutional kernel on the YOLOv5 backbone network, which improves the ability to capture global information and compensates for the lack of local information for detecting small targets. Secondly, a small target detection layer and two feature fusion layers are added. At the same time, In order to better detect objects of different scales in complex backgrounds, a module for multi-scale feature extraction is designed by combining dilated convolution and attention mechanism. The experimental results show that the proposed algorithm improved 5.4% over YOLOv5s in terms of mAP@0.5 and over YOLOv7-tiny. The method meet the requirement of real-time detection in aerial image small target detection, and improve the detection performance in small target scenes. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Feature extraction

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