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

共 764 条记录，以下是61-70 订阅

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A Cascade-filtered Adaptive CFAR Detector in Low small Target Detecting

A Cascade-filtered Adaptive CFAR Detector in Low Small Targe...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Leibo Ni Wenwen Xu Hao Wang Fengze Zhang Dalong Xu Jianyin Cao Nanjing University of Science and Technology Nanjing China Nanhu Laboratory Jiaxing China Changchun University of Science and Technology Changchun China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

In the context of detecting low-flying small targets in urban high-rise environments, the targets are often obscured by large clutter reflectors or non-uniform clutter regions. This paper proposes a cascaded filtering adaptive constant false alarm rate (CFAR) detector. This method consists of two cascaded detectors. Units judged as "target present" by the first stage are filtered out in the second stage. Compared to single-stage detectors, this method effectively integrates the performance advantages of multiple CFAR techniques. This makes it suitable for more complex detection environments. Based on measured data and Monte Carlo simulation results, the cascaded filtering CFAR detector has a high detection rate in multi-target environments and a low false alarm rate in non-uniform clutter edge environments.

关键词： Monte Carlo methods Fluctuations Filtering Radar measurements Image edge detection Simulation Detectors data processing Clutter

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Learning DCT Subband using Kolmogorov-Arnold Network for Infrared small Target Detection

Learning DCT Subband using Kolmogorov-Arnold Network for Inf...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Zekai Zhang Yingrui Zhao Shichao Zhou Zihui Yang School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Deep learning-based infrared small target detection (IRSTD) methods typically exploit spatial domain cues to infer dim and weak infrared targets. However, relying solely on spatial domain information is sub-optimal due to the lack of structure and texture details of the target. Alternatively, we learn frequency priors to enhance targets in frequency domain, and propose a Frequency Domain Enhanced Network (FDENet). It contains a frequency domain discrete cosine transform enhancement (FDE) module with KAN-inspired DCT learning mechanism. Specifically, the FDE module uses multiple univariate nonlinear functions to combine continuous multivariate functions to directly map frequency-aware cues without spatial features. It then aligns the frequency-aware cues and with the spatial features to capture dimly weak targets. Generalization experiments and comparative studies on two real-world infrared single-frame image datasets fully demonstrate the effectiveness of our method.

关键词： Learning systems Frequency-domain analysis Object detection Feature extraction data processing Discrete cosine transforms

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Research on Complex Street View Detection Algorithm Based on YOLOv8

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

引用

signal processing and Intelligent Computing (SPIC), International conference on

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

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

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.

关键词： Performance evaluation Accuracy Pedestrians Shape Urban areas signal processing algorithms Object detection Real-time systems Mobile handsets Detection algorithms

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Subspace Projection Algorithm based on Code Agile Waveform for Folded Clutter Suppression

Subspace Projection Algorithm based on Code Agile Waveform f...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Zihao Liu Huayu Fan Zhaopeng Cao Lixiang Ren Quanhua Liu Erke Mao Radar Research Lab Beijing Institute of Technology Beijing China Key Laboratory of Electronic and Information Technology in Satellite Navigation Beijing Institute of Technology Beijing China Yangtze Delta Region Academy of Beijing Institute of Technology Beijing China Chongqing Innovation Center of Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

The Internal Clutter Motion (ICM) results in an expansion of the clutter Doppler spectrum. With conventional waveforms, the presence of range ambiguity causes short-range strong clutter with ICM to be folded into the long-range interval. The folded clutter, along with Doppler expansion, submerges low-speed small targets, significantly affecting the target detection performance of ground-based early warning radar. Agile waveforms improve the distinguishability of echoes from different range intervals by varying the waveform parameters between pulses, enhancing the degree of signal processing. Therefore, this paper proposes a subspace projection algorithm based on code agile waveform to suppress the folded clutter with ICM. First, the clutter subspace is constructed using the echo model of the code agile waveform and the distribution characteristics of clutter in the range-Doppler domain. Next, subspace projection is applied to each range interval, with iterative processing between intervals to achieve folded clutter suppression. Finally, the joint mismatch filtering and Pulse Doppler (PD) processing is performed to realize coherent accumulation in each range interval. The simulations and processing results of real measured data demonstrate the effectiveness of the proposed algorithm in suppressing folded clutter and improving the detection performance of small targets at long-ranges and low-speeds.

关键词： Codes Filtering Radar clutter signal processing algorithms Radar detection signal processing data models Doppler effect Clutter Projection algorithms

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Underwater Multiple targets Tracking Using Multi-Bernoulli Filter and Improved data Association

Underwater Multiple Targets Tracking Using Multi-Bernoulli F...

引用

IEEE International conference on Information Communication and signal processing (ICICSP)

作者： Jiawei Gou Xionghou Liu Yixin Yang Chao Sun Ruijie Zhang Qifeng Bao Shaanxi Key Laboratory of Underwater Information Technology School of Marine Science and Technology Northwestern Polytechnical University Shaanxi Xian China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

Traditional multi-target tracking methods using Random Finite Set (RFS) theory mainly generate trajectories by using label RFS or performing data association after RFS filtering. For the case of target trajectories intersect, the too small distance between adjacent targets (i.e. targets are in close proximity) can cause label confusion or association errors, making it challenging for these methods to generate accurate trajectories. To solve this problem, we propose a target tracking method that integrates the multi-target multi-Bernoulli (MeMBer) filter and the improved data association. The MeMBer filter is used to obtain the target state estimations before data association. To avoid association errors when targets are in close proximity, we make the following improvements based on the nearest-neighbor data association method. When multiple targets are far from each other, we directly use the existing nearest-neighbor method to generate trajectories; when multiple targets are in close proximity, we treat the trajectory predictions of the last time step as the current trajectories, therefore avoiding data association errors. The simulation results demonstrate that the proposed method effectively solves the problem of inaccurate trajectory estimation during the intersection of target trajectories.

关键词： Radio frequency Target tracking Monte Carlo methods Simulation signal processing Information filters Filtering theory Trajectory State estimation Clutter

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A multi-layer simulation technique for modeling large and small-scale scattering in radar sounder data 28

A multi-layer simulation technique for modeling large and sm...

引用

conference on Image and signal processing for Remote Sensing XXVIII

作者： Cortellazzi, Marco Thakur, Sanchari Sbalchiero, Elisa Bruzzone, Lorenzo Univ Trento Dept Informat Engn & Comp Sci Sommarive 5 I-38123 Trento Italy

ISBN: (纸本)9781510655386;9781510655379

Radar sounders (RS) provide information on subsurface targets for planetary investigations. Several simulation techniques have been developed to support the RS design and the data interpretation. Each technique has different properties and modeling capabilities, achieving different trade-offs between accuracy and computational requirements. The state-of-the-art RS simulation techniques include: i) numerical methods, such as the Finite-Difference Time-Domain (FDTD) technique, which allows the modelling of small-scale scattering phenomena at the cost of high computational requirements;ii) facet modeling and ray-tracing based methods, such as the multi-layered coherent RS (MCS) technique, which requires less computational resources than FDTD, allowing the modeling of large-scale scattering phenomena. Recently an integrated simulation methodology has been presented, for simulating small-scale scattering phenomena in large scenarios. However, this methodology was designed for modeling only surface scattering. In this paper, we propose a method that extends the capabilities of the integrated methodology to model both large and small-scale roughness in a multi-layer scenario. The proposed method uses the FDTD technique to evaluate the effects associated with small-scale roughness in terms of i) scattering phenomena associated with the layers and ii) power losses associated with the signal transmitted through a rough layer. To recursively apply scattering and transmission to multiple layers of the subsurface, a coherent ray-tracing method is used. We experimentally assessed the effectiveness of the proposed methodology on three-layer models by integrating the effect of roughness imposed on the layers and in transmission through them.

关键词： Radar sounder planetary exploration simulations FDTD ray-tracing coherent simulator RIME SRS

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Experimental evaluation of Supervised Reciprocal Filter Strategies for OFDM-radar signal processing

Experimental evaluation of Supervised Reciprocal Filter Stra...

引用

IEEE Radar conference (RadarConf)

作者： Rodriguez, Javier Trujillo Colone, Fabiola Lombardo, Pierfrancesco Sapienza Univ Rome Dept Informat Engn Elect & Telecommun DIET Rome Italy

ISBN: (纸本)9781665436694

In this paper, we present an experimental evaluation of recently proposed Supervised Reciprocal Filter approaches for the compression of OFDM-radar signals. The range-Doppler map is usually evaluated using a suboptimal batches algorithm, after fragmenting the signal in batches with length equal to the OFDM symbol. Using "OFDM fragmentation" requires symbol synchronization and sets constraints on the non-ambiguous Range-Doppler area of targets that can be detected with limited signal-to-Noise Ratio (SNR) loss. Supervised Reciprocal Filters have been recently proposed to operate with batches of longer lengths than the OFDM symbol without requiring any synchronization. In this paper we extend the study to include the case of batches equal to a fraction of the OFDM symbol, which provides higher flexibility to adapt the processor to the range-Doppler scenario of interest. These filters have been shown to contain the large SNR losses obtained with a direct application of the Reciprocal Filter (RF) with the non-OFDM fragmentation. Moreover, they have been shown theoretically to preserve the benefits of the RF over the Matched Filter (MF) against the clutter-limited scenarios. To assess the performance of the Supervised Filter against a real scenario, an acquisition campaign has been carried out using the Sapienza experimental passive radar along the coast north of Rome, against a maritime traffic scenario, including non-cooperative vessels, as well as a cooperating small boat equipped with differential GPS positioning registration tools. The effectiveness of the proposed approaches is validated by applying them to experimental data from a PBR application exploiting DVB-T transmissions.

关键词： signal to noise ratio

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Design and Implementation Considerations for a 3D Beamformer on State-of-the-Art Multicore Processors

Design and Implementation Considerations for a 3D Beamformer...

引用

OCEANS conference

作者： Narayanan, Prakash M. Gopal, Vijay G. Rajesh, R. DRDO Naval Phys & Oceanog Lab Kochi Kerala India CUSAT Kochi Kerala India

ISBN: (纸本)9781665418218

Underwater targets have become increasingly difficult to be detected by sonars. Improvement in ship and submarine design technology have made it less noisy, and hence difficult to detect. And there is a proliferation of small Autonomous Underwater Vehicles (AUVs) for conducting surveillance operations, and recently, also for carrying out offensive missions. AUV are more difficult to detect compared to a submarine. This has resulted in sonar designers to search for options to improve the detection capabilities of sonars. However, there exist little options for sonar designers to improve the detectability of such underwater objects. Sonar designers have resorted to bigger arrays to improve the detection, by improving the directive gain of the array resulting in huge data to be handled by the signal processors. Improvement in processing technology has made available enough resources to handle the multitude of data thus generated. The processor technology in turn brings its own issues to be handled. The signal processor designer must take care the architectural details of the processor as well as its memory architecture to get maximum through put. The paper presents different approaches to implementation for a multicore processor. The approaches are based on OpenMP and POSIX thread. In the thread-based approach different types of stride of data are considered. The results show that the pthread based implementation with stride carefully chosen to avoid the memory conflicts results in high processor utilization. A higher block size enables the memory controller to keep the computational resources from starving for data, there by getting better utilization.

关键词： signal processing Array processing Beamformers Multicore device optimizations

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DCUNet: Deformable Convolutional UNet for Multi-frame Infrared small Target Super-resolution

DCUNet: Deformable Convolutional UNet for Multi-frame Infrar...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Yuanxin Huang Xiyang Zhi Wenbin Chen Xiaoyang Liang Zhipeng Wang Wei Zhang Research Center for Space Optical Engineering Harbin Institute of Technology Harbin China Institute of Remote Sensing Satellite China Academy of Space Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

The objective of infrared multi-frame super-resolution for small targets is to enhance the target's resolution by leveraging complementary information from multiple frames. However, the presence of motion variations and scale changes in infrared small targets introduces discontinuities in information between frames, posing challenges for super-resolution. To address the above challenges, we propose a multi-frame infrared small target super-resolution network based on deformable UNet. Specifically, the network takes multi-frame sequential infrared images as input and divides the input into reference frames and current frames. It utilizes deformable convolutions to align the frames to enhance the target features of the current frame. Additionally, the encoding structure of the UNet network is employed to extract multiscale features from the sequential images. By leveraging skip connections and a decoding structure, the network achieves the enhancement of target detail information and the fusion of multiscale features, ultimately outputting the super-resolved image. We conducted experiments on the IRDST and NUDT-MIRSDT datasets, and the results validate the practicality of our designed network.

关键词： Image segmentation Head Convolution Motion segmentation Superresolution Feature extraction Robustness Decoding Spatial resolution signal resolution

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Sea Surface small Target Tracking Method with Integrated Dynamic Wave Prediction Information

Sea Surface Small Target Tracking Method with Integrated Dyn...

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signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Zixuan Li Biao Jin Kangsheng Sun Chao Liu Ocean College Jiangsu University of Science and Technology Zhenjiang China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Tracking small targets on the sea surface has always been a challenging issue in the field of maritime target monitoring. Traditional methods typically rely on specific dynamic equations to establish the motion state model of the target (such as CV, CA, and CT models or their combinations), which struggle to accurately represent the motion states of small targets under complex sea conditions. We propose a method that incorporates deep learning to predict the dynamic fluctuations of sea waves, integrating real-time wave state information into the target state model. This method, which fuses sea wave dynamic prediction information, aims to improve the tracking of small sea surface targets. Firstly, we simulate various sea conditions based on the Elfouhaily wave spectrum to establish a database of small target motion trajectories on the sea surface. Then, we employ an LSTM network with a dual-stage attention mechanism to predict wave heights, which are subsequently fed into the state transition model. We utilize the Extended Kalman Filter for tracking. Simulation results demonstrate that with the assistance of sea wave dynamic prediction information, the proposed method enhances target tracking accuracy by approximately 14% compared to traditional methods.

关键词： Sea surface Target tracking Surface waves Dynamics Predictive models Mathematical models Trajectory Kalman filters Vehicle dynamics Long short term memory

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