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arXiv 2024年

作者： Li, Yang Tan, Wenyi Wang, Tingrui Liang, Xinkai Pan, Quan School of Automation Northwestern Polytechnical University Xi’an710072 China Laboratory of Science and Technology on Complex System Control and Intelligent Agent Cooperation Beijing China

To achieve attacks on object detection in the physical world, many existing studies focus on adversarial camouflage generation techniques, which involve applying adversarial textures onto the surface of the target. However, the neural renderers used in previous works cannot realistically simulate the physical world, and most texture rendering processes are implemented on 2D images, without fully considering the influence of the structural information of 3D models on texture overlay. To address these challenges, we introduce a novel neural rendering approach specifically tailored for adversarial camouflage within a versatile 3D rendering framework. Our method, named Flexible Physical-camouflage Attack (FPA), goes beyond traditional techniques by faithfully simulating lighting conditions, material variations of the camouflage, the angle and distance between the target and the camera, ensuring a nuanced and realistic representation of textures on a 3D target. To achieve this, we employ a generative approach that learns adversarial patterns from a diffusion model. This involves combining specially designed adversarial loss, smoothness loss, non-printable score loss, and concealment constraint loss to ensure the adversarial, printability, and concealable nature of camouflage in the physical world. Furthermore, we showcase the effectiveness of the proposed camouflage in sticker mode, demonstrating its ability to cover the target without compromising adversarial information. Through empirical and physical experiments, FPA exhibits strong performance in terms of attack success rate and transferability. Additionally, the designed sticker-mode camouflage, coupled with a concealment constraint, adapts to the environment, yielding diverse styles of texture. Our findings highlight the versatility and efficacy of the FPA approach in adversarial camouflage applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Camouflage

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Path Planning for Anti-Ship Missile Using Tangent Based Dubins Path

Path Planning for Anti-Ship Missile Using Tangent Based Dubi...

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International Conference on intelligent Autonomous systems (ICoIAS)

作者： Long Cheng Hao Lu Teng Lei Jun Chen School of Electronics and Information Northwestern Polytechnical University Xi’an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

Path planning is a significant component to achieve successful operation of anti-ship missile in dynamic battlefield environment. A threat-free path planning algorithm based on geometric tangent Dubins path is proposed in this paper. First, the constraints need to be satisfied for threat-free path planning are presented, and the problem model of missile path planning is constructed. Then, the geometric tangent between two threat circles is taken advantage of guiding the missile to avoid the threat, and the basic turn and straight line path is generated based on Dubins path. At last, the adaptability of the proposed algorithm in complex battlefield environment is verified by simulations. The results show that the Dubins path avoidance method based on geometric tangent can meet the requirements of flight path, obstacle avoidance and real-time planning, which make it have a strong application prospect.

关键词： Missiles Path planning Collision avoidance Planning Radar detection Turning Real-time systems

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Topology Optimization Design of LEO Satellite Network

Topology Optimization Design of LEO Satellite Network

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第三十八届中国控制会议

作者： Jian Tai Junting Lv XiANDe Wu Ting Song Qiang Zhang Yanbing Xiang Jun Sun College of Aerospace and Civil Engineering Harbin Engineering University Shanghai Key Laboratory of Space Intelligent Control Technology Beijing Institute of Spacecraft System Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory

This paper establishes a satellite network topology optimization model based on satellite orbital dynamics, establishes constraints from two aspects of satellite geometric visibility and satellite elevation constraints in the concept of inter-satellite links, and finally solves the above optimization problems by using simulated annealing algorithm, and presents a time-varying satellite network topology optimization method. In the actual simulation, we give a satellite network with multiple satellites and optimize it. The optimal solution of the network configuration is obtained, and a shortest inter-satellite transmission path from signal start star to signal termination star based on time-varying is solved. For this inter-satellite link, the connectivity of inter-satellite link and the fault tolerance of satellite network are analyzed, which proves the feasibility and validity of the optimization method.

关键词： LEO satellite network topology optimization inter-satellite link simulated annealing algorithm

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Multi-Source Dynamic Time Series Data Processing Method Based on Comprehensive Weighted Fusion 12

Multi-Source Dynamic Time Series Data Processing Method Base...

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12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2022

作者： Geng, Huapin Yuan, Feimeng Suo, Bin Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China Beijing Electro-mechanical Engineering Institute Beijing China School of Mathematics Southwest Jiaotong University Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9781839538360

Aiming at the fusion problem of multi-source heterogeneous dynamic data sources, based on the subjective and objective comprehensive weighting idea, an efficient multi-source dynamic data fusion algorithm is proposed. First, the outlier detection method based on linear regression model is used to preprocess the multi-source dynamic time series data. Then, determine the weight of the dynamic data. The prior weight of the data source is determined by the AHP method, cyclic scoring method, etc., and the posterior weight is determined according to the similarity between the time series data. Based on the Euclidean distance, a similarity measure between different data sources and a similarity measure between different dynamic data samples are constructed respectively. The former is used for the fusion of dynamic data standard deviation expectations, and the latter is used for the fusion of mean expectations. Finally, the comprehensive weight of each dynamic time series of each data source is obtained, and the comprehensive weighted fusion method is used to obtain the expected value and standard deviation of the dynamic response. The analysis of the calculation example shows that the proposed algorithm has higher computational efficiency than the method that treats dynamic data as several discrete static data. © 2022 IEEE.

关键词： Data fusion

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Distributed Multi-Sensor Multi-View Fusion of PHD Filter for Maneuvering Targets

Distributed Multi-Sensor Multi-View Fusion of PHD Filter for...

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IEEE International Conference on Radar

作者： Cong Peng Lei Chai Wei Yi Linxiu Chen School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781665468893

This paper addresses the problem of maneuvering multi-target tracking by a network of sensors having different and limited fields of view (FoV s). Each local sensor runs the Gaussian Mixture Probability Hypothetical Density (GMPHD) filter. Due to the target maneuver, based on a single motion model, severe tracking performance degradation can be observed. We propose to use multi-model (MM) method to realize the adaptation to motion characteristic so as to overcome maneuverability of targets. Then considering FoV s of sensors in the network are different and limited, the standard weighted arithmetic average (WAA) fusion is no longer applicable and leads to an underestimation of the target number. Therefore, we use state-dependent WAA (SD-WAA) fusion rule, which performs the WAA in a more robust way by calculating a set of state-related fusion weights. Numerical experiment is designed to demonstrate the efficacy of the proposed method.

关键词： Degradation Adaptation models Target tracking Fuses Radar Sensor fusion Sensor phenomena and characterization

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WATNet: A Wavelet-Aware Lightweight Hybrid Model for Fast Low-Light Enhancement 7

WATNet: A Wavelet-Aware Lightweight Hybrid Model for Fast Lo...

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7th Asian Conference on Artificial Intelligence technology, ACAIT 2023

作者： Wang, Qiangqiang Huang, Peiliang Li, Lei Han, Longfei Anhui University AHU-IAI Ai Joint Laboratory Hefei China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei China Northwestern Polytechnical University School of Automation Xi'an China Science And Technology On Complex System Control And Intelligent Agent Cooperation Laboratory Beijing China Beijing Technology And Business University Beijing China University of Science And Technology of China School of Information Science And Technology Hefei China

ISBN: (纸本)9798350359145

Low-light enhancement task is an essential component of computer low-level visual tasks, which involves processing images captured under dim lighting conditions to make them appear as if they were taken under normal illumination. Currently, deep neural networks have become the mainstream approach for image processing. However, recent works have devoted considerable efforts to designing high-performance models, which often come with high computational complexity and inference time, making real-time processing unfeasible. We observed that some convolutional methods are due to the need for deep layers which results in a large number of parameters. Moreover, enhancing details and removing noise in low-light images remains an open challenge. In order to solve the above problems, we propose a lightweight baseline that combines CNN and sparse grid attention transformer blocks to enable the model to capture a global receptive field at an early stage. Specifically, we propose a High-Frequency Wavelet-aware Block(HFWB) that focuses on processing high-frequency information in the wavelet domain to refine details and suppress noise. With a processing time of only 10.6ms, the performance of our model outperforms that of the current state-of-the-art lightweight models on benchmark low-light datasets. Compared to state-of-the-art models in the LOL dataset, our model achieves a reduction in inference time of over 90% and requires only about 1% of the FLOPS. © 2023 IEEE.

关键词： Deep neural networks

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A New Method of EMI Estimation among Low Altitude Aircrafts on Sea Surface

A New Method of EMI Estimation among Low Altitude Aircrafts ...

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IEEE International Conference on Computational Electromagnetics (ICCEM)

作者： Yanyan Wang Kangkang Gao Jiangnan Xing Tao Jiang Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China College of Information and Communication Engineering Harbin Engineering University Harbin China

ISBN: (数字)9781728134482

ISBN: (纸本)9781728134499

There is a certain amount of RF facilities on the low-altitude aircrafts that could cause electromagnetic interference within the platform, the electromagnetic interference between platforms is the key to influence the electromagnetic compatibility of aircraft platform. Specific systems have been developed to provide collision avoidance and early warning schemes for potential physical collisions between aircraft. With the increase in the number of ground and air vehicles and the radiation power of radio frequency equipment, the marine electromagnetic environment is deteriorating day by day. There is no effective solution to the electromagnetic "collision" among aircrafts that caused by electromagnetic interference, which is needed to be solved. This paper draws lessons from the idea that physical collision between aircrafts can be predicted and analyzed by using space trajectory model and avoided collision, then proposed aircraft navigation trajectory equation, the forecast analysis of the location of the vehicle at any time, heading, speed and acceleration information, using airborne electromagnetic emission equipment antenna model, calculated the sea low-flying aircraft airborne radio system of electromagnetic radiation, the use of the electronic equipment receiving antenna gain and receiver sensitivity, combined with the value of standard, the interference matrix which can describe the degree of electromagnetic radiation hazard between single machine and multiple machine is established. In this paper, the theoretical model of aircraft trajectory dynamics is seamlessly transformed into the electromagnetic collision field of low-altitude aircraft. Based on the dynamic evaluation method of electromagnetic interference level, the risk analysis of electromagnetic collision probability of aircraft is carried out, which can provide powerful technical support for solving electromagnetic interference problem of aircraft, which has important reference value for design, tes

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Zero-shot Learning Based on Semantic Embedding for Ship Detection

Zero-shot Learning Based on Semantic Embedding for Ship Dete...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Zihan Zhang Jiajia Zhoa Xinkai Liang School of Electronics and Information Northwestern Polytechnical University Xi’an Shaanxi China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing China

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

Zero-shot detection (ZSD) is a hot topic, which can detect unseen object without training on it. This new approach rises several challenges, e.g., the imbalance between positive and negative data, ambiguity between background and unseen classes, and how to align visual feature and semantic concept. In this paper, we apply an end-to-end zero-shot network to fulfil ZSD, where polarity loss is utilized to train detection model. polarity loss puts more importance on difficult data to reduce class imbalance and can maximize the difference between positive and negative predictions. Then, we use a semantic embedding method that use word vectors in both classification and regression subnets to better align visual features and semantic features. Finally, we use MS-COCO dataset as seen classes to train detection model, then we transfer the model for our own to detect warship object. Our model performs good on unseen classes and test accuracy of using polarity loss is apparently higher than that of using focal loss.

关键词： Semantics Visualization Vocabulary Training Feature extraction Object detection Measurement

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Research on the Radio Frequency Simulation Method for Wide-band Radar complex Target based on Physical Optics and Physical Diffraction Theory

Research on the Radio Frequency Simulation Method for Wide-b...

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2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Guijier, DIao Hong, Ni Tianming, Zhan Yajing, Zhang Liang, Yang Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electro-mechanical Engineering Institute Beijing China Beijing Aerospace Smart Manufacturing Technology Development Co.Ltd. Beijing China Datang Mobile Communication Equipment Co. Ltd. Datang Telecom Group Beijing China

ISBN: (纸本)9781728123455

A radio frequency (RF) simulation technique based on high frequency hybrid method is proposed for complex target. Firstly, the radar cross section (RCS) of the target is obtained by vector addition of facets scattering field and wedges scattering field that are calculated respectively by physical optics (PO) method and physical theory of diffraction (PTD). Then, scattering centers of the target are extracted based on multi scattering center theory, and the radar echo signal is simulated through radio frequency simulation system (RFSS). This technique could improve the fidelity of radar signal simulation and the confidence of RF simulation test. At last, simulation results validate the technique. © 2019 IEEE.

关键词： Physical optics

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Edge-guided image estimation for array Gm-APD Lidar in smoky environment using multi-scale depth images 6

Edge-guided image estimation for array Gm-APD Lidar in smoky...

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6th Optics Young Scientist Summit, OYSS 2023

作者： Zhang, Yinbo Li, Sining Sun, Jianfeng Jiang, Peng Zhang, Hailong Liu, Zhihui Zhu, Yuebing National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute of Harbin Institute of Technology Henan Zhengzhou450000 China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China Sichuan Jiuzhou Electrical Group Company Limited Sichuan Mianyang621000 China

ISBN: (纸本)9781510672642

Limited statistical frame number and strong backscatter interference from smoke result in a photon-starved regime, severely limiting the depth imaging capability of array Gm-APD lidar in smoky environment. Here, we propose a depth image estimation algorithm that can significantly improve the integrity of targets in dense smoke environments when signal photons are starved. At the signal level, the algorithm improves the accuracy of extracting signal photons by constructing multi-scale superpixels. At the image level, using edge information of depth images at different scales to guide and fill the original scale depth image achieves efficient noise reduction and improves target integrity. It has been successfully demonstrated under different attenuation lengths and statistical frame numbers. Compared with other state-of-the-art methods, the proposed algorithm has maximum target recovery and structural similarity, especially for the attenuation length (AL) is 3.6 and statistical frame number is 1500 (imaging time is 75ms). This study is of great significance for the fast depth imaging of dynamic targets by array Gm-APD lidar in dense smoke environments. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Optical radar

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