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17th IEEE International Conference on signal processing, ICSP 2024

作者： Li, Yanshan Zong, Hailin He, Suixuan Wei, Miaomiao Shenzhen University Institute of Intelligent Information Processing Guangdong Key Laboratory of Intelligent Information Processing Shenzhen China

ISBN: (纸本)9798350387384

Spatio-temporal relationships play an important role in group activity recognition. The spatio-temporal relationships are complex and varied, containing relationships between individuals, between individuals and subgroups, and between subgroups. However, there is no unified method for measuring these multidimensional spatio-temporal relationships. Therefore, this paper proposes a set of metric methods for multidimensional spatio-temporal relationships based on geometric algebra, including the metric method based on positional features and the metric method based on appearance features. And this paper proposed a deep network for video group activity recognition based on multidimensional spatio-temporal relationships. The experimental results show that the proposed algorithm can effectively improve the accuracy of group activity recognition. © 2024 IEEE.

关键词： Algebra

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Aircraft type recognition in 3D-view optical image with contour segmentation

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Multimedia Tools and Applications 2024年第18期83卷 54495-54520页

作者： Liang, Zhixiang Li, Yanshan Yu, Rui Zhang, Kaihao Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518061 China Institute of Intelligent Information Processing Shenzhen University Shenzhen518061 China College of Engineering and Computer Science Australian National University Canberra Australia

Aircraft type recognition has been researched deeply for plenty years on remote sensing and radar signal processing fields because of military needs. However, with the rapid development of UAV visualization technology in recent years, the advanced optical sensors on high-altitude drones are able to capture high-definition aircraft images of various aircraft flight postures, which brings aircraft type recognition into a brand-new research field. Different from remote sensing images, images with aircrafts in flight have larger intra-class difference caused by flight posture variation, which is 3D-view and more challenging for aircraft type recognition. Facing the new challenges, we propose a aircraft type recognition framework in 3D-view optical images. The framework consists of two stages: a coarse stage for aircraft contour segmentation and a fine stage for aircraft contour template matching. At the coarse stage, we propose a instance segmentation network CP-Deepsnake with a novel loss function CP loss which improves the accuracy of extracted aircraft contours by supervising the global distribution of contour points during contour deformation. At the fine stage, we utilize contour template matching to realize aircraft type recognition in 3D-view images. Based on IDSC contour feature descriptor, we propose a fast contour template matching approach with a new matching evaluation criterion and establish an aircraft contour template database for aircraft contour template matching. To train and test our aircraft type recognition framework, we build two datasets with 3D-view aircraft images of 10 aircraft types. Experiments show that our method achieves considerable recognition accuracy on the aircraft type testing dataset. Besides, we evaluate the proposed CP-Deepsnake network on two challenging instance segmentation public datasets SBD and KINS, where it compares favorably against state-of-the-art methods, which means our CP-Deepsnake network can be extended to more ins

关键词： Aircraft

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High-Precision DOA Estimation Method Based on Synthetic Aperture Technique

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Journal of Beijing institute of Technology 2024年第2期33卷 111-118页

作者： Yongjia Dou Guangcai Sun Yuqi Wang Mengdao Xing National Key Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China School of Communication and Information Engineering Xi’an University of Science and TechnologyXi’an 710054China

The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to *** this paper,a method for DOA estimation based on a motion platform is proposed to achieve high-precision DOA estimation by utilizing past and present *** concept of synthetic aperture is introduced to construct a linear DOA estima-tion model.A DOA fine-tuning method based on the linear model is proposed to eliminate the lin-ear DOA variation,achieving a non-coherent accumulation of DOA ***,the baseband modulation and the phase modulation caused by the range history are compensated to achieve the coherent accumulation of all the DOA *** results show that the proposed method can significantly improve the DOA estimated accuracy at low signal-to-noise ratios(SNR).

关键词： synthetic aperture direction-of-arrival(DOA)estimation coherent accumulation

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Satellite Component Segmentation Based on Symmetry Loss and Edge Perception 17

Satellite Component Segmentation Based on Symmetry Loss and ...

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17th IEEE International Conference on signal processing, ICSP 2024

作者： Chen, Luyao Yang, Chaolei Shi, Zhaohui Wang, Kaiming Li, Yanshan Institute of Intelligent Information Processing Shenzhen University Shenzhen China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China

ISBN: (纸本)9798350387384

Component segmentation is a crucial task in satellite recognition and tracking, focusing on separating the target from the background and segmenting its internal components for detailed structural analysis. Nevertheless, this task faces significant challenges due to viewpoint variations, illumination changes, and noise interference. To address these challenges, we first propose an improved multi-task network based on U-Net for three-class segmentation, binary segmentation, and edge detection of satellite. The proposed multi-task segmentation framework enables the network to perform fine-grained segmentation of complex satellite structures under varying illumination and viewpoints, thus enhancing the model's robustness. In the edge detection task, we introduce an edge-aware network that extracts multi-scale edge features using a multi-scale convolutional network, which improves the separability of different components. Additionally, we propose a symmetry regularization loss that leverages the satellite's structural symmetry to guide segmentation and improve performance. Experiments demonstrate the efficacy of our method for the satellite component segmentation task. © 2024 IEEE.

关键词： Deep learning

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Positioning Error Compensation via Channel Knowledge Map for UAV Communication

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IEEE Internet of Things Journal 2025年第11期12卷 16977-16989页

作者： Zhang, Chiya Wang, Ting He, Chunlong Harbin Institute of Technology School of Electronic and Information Engineering Shenzhen518055 China Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen518060 China

When Unmanned Aerial Vehicles (UAVs) perform high-precision communication tasks, such as searching for users and providing emergency coverage, positioning errors between base stations and users make it challenging to deploy trajectory planning algorithms. To address these challenges caused by position errors, a framework was proposed to compensate it by Channel Knowledge Map (CKM), which stores channel state information (CSI). By taking the positions with errors as input, the generated CKM could give a prediction of signal attenuation which is close to true positions. Based on that, the predictions are utilized to calculate the received power and a PPO-based algorithm is applied to optimize the compensation. After training, the framework is able to find a strategy that minimize the flight time under communication constraints and positioning error. Besides, the confidence interval is calculated to assist the allocation of power and the update of CKM is studied to adapt to the dynamic environment. Simulation results show the robustness of CKM to positioning error and environmental changes, and the superiority of CKM-assisted UAV communication design. © 2025 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Wideband MIMO radar Waveform Design Method For Amplitude-Phase Joint Optimization Under Low PAR Constraint 2

Wideband MIMO Radar Waveform Design Method For Amplitude-Pha...

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2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Wu, Yue Jiu, Bo Xu, Danlei Liu, Ruofan Liu, Hongwei Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Xidian University Institute of Information Sensing Xi'an China

ISBN: (纸本)9798331515669

We consider the design of wideband multiple-input multiple-output (MIMO) radar waveforms to approximate the desired beampattern. radar waveform design is usually challenged by the constants modulu constraint, however, with the improvement of hardware performance,low peak-to-average ratio(PAR) waveforms are acceptable in modern radar systems, for this reason, we allow the waveform mode value to fluctuate in a certain range and obtain the low PAR waveform by alternating phase and amplitude optimization of the waveforms. Comparison with the constant modulus waveform obtained by other methods at normalized energy shows that our designed waveforms have a better approximation of the desired beampattern. © 2024 IEEE.

关键词： MIMO radar

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Pulse train coding design for MIMO radar against interrupted sampling repeater jamming with Doppler frequency shifts 2

Pulse train coding design for MIMO radar against interrupted...

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2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Wu, Hao Zheng, Hao Zhang, Yinghui Yan, Junkun Inner Mongolia University College of Electronic Information Engineering Hohhot China Inner Mongolia University Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing Hohhot China Xidian University National Key Laboratory of Radar Signal Processing Xian China

ISBN: (纸本)9798331515669

Intercepting and repeatedly retransmitting radar signals, interrupted sampling repeater jamming (ISRJ) generates higher power false signals that can seriously affect radar operation. To combat this interference, a scheme for countering ISRJ with Doppler frequency shifts by designing a multiple input multiple output (MIMO) radar with pulse train encoding and decoding is proposed. On the one hand, the scheme can suppress the pulse compression sidelobes of the target and ISRJ with Doppler frequency shifts. On the other hand, a detection matrix is designed to identify spurious peaks formed by interfering signals. Finally, the proposed scheme can accurately obtain target and jamming information in the environment while satisfying the constant mode (CM) constraints. © 2024 IEEE.

关键词： MIMO radar

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Joint Secure Transmit Beamforming Designs for Physical Layer Security in MIMO-ISAC System 2

Joint Secure Transmit Beamforming Designs for Physical Layer...

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2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Guo, Sitong Zheng, Hao Zhang, Yinghui Yan, Junkun Inner Mongolia University College of Electronic Information Engineering Hohhot China Inner Mongolia University Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing Hohhot China Xidian University National Key Laboratory of Radar Signal Processing Xian China

ISBN: (纸本)9798331515669

This article concentrates on the physical layer security (PLS) towards an integrated sensing and communication (ISAC) system, which communicates with legitimate communication users (CUs) and detects the single sensing target, which is considered to be eavesdropper because it might intercept the transmitting message from the base station to CUs. The joint transmitting beamforming for secure communication and sensing is designed to maximize the sum secrecy rate (SR) of system under the constraints of quality-of-service of CUs, the signal-to-Noise Ratio (SNR) of sensing and the power budget of the system. The optimal solution is obtained by the semidefinite relaxation and successive convex approximation algorithms. The availability of the beamforming design in ensuring the SR of the ISAC system is showed by Simulation results. © 2024 IEEE.

关键词： Budget control

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Persymmetric adaptive polarimetric detection of subspace range-spread targets in compound Gaussian sea clutter

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Journal of Systems Engineering and Electronics 2024年第1期35卷 31-42页

作者： XU Shuwen HAO Yifan WANG Zhuo XUE Jian National Key Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China Xi’an Electronic Engineering Research Institute Xi’an 710100China Beijing Institute of Radio Measurement Beijing 100039China School of Communications and Information Engineering Xi’an University of Posts and TelecommunicationsXi’an 710121China

This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea *** sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters,and the target is modeled as a subspace rangespread target *** persymmetric structure is used to model the clutter covariance matrix,in order to reduce the reliance on secondary data of the designed *** adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test(GLRT),Rao test,and Wald *** the proposed detectors have constant falsealarm rate property with respect to the clutter texture,the speckle covariance *** results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments,and the proposed GLRT detector has the best detection performance under different parameters.

关键词： sea clutter adaptive polarimetric detection compound Gaussian model subspace range-spread target persymmetric structure

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A Small-sample Trajectory Classification Algorithm via Bayesian Program Learning 17

A Small-sample Trajectory Classification Algorithm via Bayes...

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17th IEEE International Conference on signal processing, ICSP 2024

作者： Li, Yanshan Yao, Ruoqiang Shenzhen University Institute of Intelligent Information Processing Shenzhen518060 China Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen518060 China

ISBN: (纸本)9798350387384

Trajectory classification algorithms are widely used in fields such as behavior recognition, anomaly detection and monitoring, and video content analysis. To overcome the issues of traditional trajectory classification algorithms that require large supporting data and continuous model updates to ensure effectiveness, we take inspiration from the concept learning approach proposed by Brenden et al. We simulate how humans learn rich concepts from a single hand-drawn sample and propose a Bayesian program learning-based trajectory classification algorithm. This algorithm first builds concepts from a set of hand-drawn trajectories and then classifies trajectory data based on these constructed concepts. Experimental results show that our algorithm outperforms traditional single-sample learning algorithms in trajectory classification tasks and also shows superior performance over traditional single-sample learning algorithms when the dataset includes noisy data. © 2024 IEEE.

关键词： Contrastive Learning

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