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An improved RD algorithm of curved trajectory bistatic SAR based on Chebyshev polynomials 基于切比雪夫多项式的曲线轨迹双基地SAR改进RD算法
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631571
Xiyi Xu, Ge-wei Tan, Biao Li
{"title":"An improved RD algorithm of curved trajectory bistatic SAR based on Chebyshev polynomials","authors":"Xiyi Xu, Ge-wei Tan, Biao Li","doi":"10.1117/12.2631571","DOIUrl":"https://doi.org/10.1117/12.2631571","url":null,"abstract":"According to the requirements of high resolution real time imaging of curved trajectory Bistatic Synthetic Aperture Radar (BiSAR), an improved RD algorithm is proposed in this paper. Firstly, the slant range of curved BiSAR is established by Chebyshev polynomials. Secondly, linear range cell migration (LRCM) and Doppler linear phase are compensated, and the high order approximate two-dimensional spectrum of echo signal is obtained by the method of series inversion (MSR) and Chebyshev decomposition. Finally, the focused image is obtained by matched filtering and phase compensation. By using Chebyshev polynomials to approximate slant range and spectral phase, the focus quality of BiSAR data is improved. Experimental results show that the algorithm can effectively compensate the motion error caused by three-dimensional acceleration and improve the imaging quality of the long distance edge point targets.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131255347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimal respiratory waveform selection based on range-multiple beams using a MIMO radar 基于距离多波束的MIMO雷达呼吸波形优化选择
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631414
WanHua Wu, Zhaocheng Yang
{"title":"Optimal respiratory waveform selection based on range-multiple beams using a MIMO radar","authors":"WanHua Wu, Zhaocheng Yang","doi":"10.1117/12.2631414","DOIUrl":"https://doi.org/10.1117/12.2631414","url":null,"abstract":"In this paper, we propose an optimal respiratory waveform selection algorithm based on range-multiple beams using a 77GHz frequency modulated continuous wave (FMCW) multiple-input-multiple-output (MIMO) radar. Generally speaking, the human chest is a multi-scattering target and the optimal monitoring position changes in a small range during breathing movement. According to this motion feature, we roughly locate the target in the range-angle candidate box based on range fast Fourier transform (FFT) and Capon direction of arrival (DOA) algorithm, respectively. Additionally, the fixed beamforming is utilized to algin the detected target site which can reduce the interference of clutter and enhance the signal-to-noise ratio (SNR). Then, the extended differential and cross-multiply (DACM) algorithm is further applied for phase unwrapping and the optimal respiratory waveform is extracted based on the features of respiratory periodicity. Ultimately, the respiratory rate is estimated by the frequency-time phase regression (FTPR) algorithm. Experiments with and without interference are conducted and the results show that the proposed algorithm can obtain accurate respiratory rate with mean square errors (MSE) 0.6862 breath2/min compared with the reference vital signs data.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"36 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120870864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DBSCAN-based energy consumption pattern clustering identification method for 5G base-station 基于dbscan的5G基站能耗模式聚类识别方法
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631595
Lijun Zhong, Minda Shi, Zhenyu Huang, Peizhe Xin, Jing Jiang, Guocheng Li, Jun Lu
{"title":"DBSCAN-based energy consumption pattern clustering identification method for 5G base-station","authors":"Lijun Zhong, Minda Shi, Zhenyu Huang, Peizhe Xin, Jing Jiang, Guocheng Li, Jun Lu","doi":"10.1117/12.2631595","DOIUrl":"https://doi.org/10.1117/12.2631595","url":null,"abstract":"To fully understand the energy consumption characteristics of 5G base-station, a DBSCAN-based energy consumption pattern clustering identification method is proposed for 5G base-station. Firstly, this paper analyzes the daily-curve characteristics of power consumption behavior in typical application scenarios of 5G base-station for further pattern clustering identification. Then, the proposed pattern clustering identification method is depicted based on DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering decision, which is composed of the feature extraction for power consumption daily-curve of 5G base-station. Finally, the experiment is implemented using actual operation data of 5G base-station as data source. The experiment results illustrate that the proposed method can effectively identify the clustering characteristics of the energy consumption behavior for 5G base-station.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126852604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A low SNR spectrum-correlated detect method of PCM-FM signal in high dynamic situation 一种高动态环境下PCM-FM信号的低信噪比谱相关检测方法
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631488
Kexin Jia, Yuxia Xin
{"title":"A low SNR spectrum-correlated detect method of PCM-FM signal in high dynamic situation","authors":"Kexin Jia, Yuxia Xin","doi":"10.1117/12.2631488","DOIUrl":"https://doi.org/10.1117/12.2631488","url":null,"abstract":"Considering Pulse Code Modulation-Frequency Modulation (PCM-FM) signal detect in high dynamic and low Signalto- Noise Ratio(SNR) situation，a low SNR spectrum-correlated detect method that is not sensitive to high dynamic situation is proposed. Firstly, this method uses the power spectrum of the known PCM-FM signal to match the power spectrum of the receiving signal, searches for the maximum filter output within the doppler frequency range, and constructs the detect statistics. Then, this method uses the probability of false alarm to compute detect threshold, and compares with the detect statistics to determine whether PCM-FM signal exists. The simulation result shows that the proposed method can detect PCM-FM signal quickly with high probability in high dynamic and low SNR situation.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121210532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An improved non-local means algorithm based on difference hash algorithm 基于差分哈希算法的改进非局部均值算法
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631454
Xintong Zou, Chunjian Hua, Jinke Ma
{"title":"An improved non-local means algorithm based on difference hash algorithm","authors":"Xintong Zou, Chunjian Hua, Jinke Ma","doi":"10.1117/12.2631454","DOIUrl":"https://doi.org/10.1117/12.2631454","url":null,"abstract":"Aiming at the inaccuracy of Non-Local Means (NLM) algorithm for measuring the similarity of neighborhood blocks, an improved Non-Local Means denoising algorithm based on Difference Hash (dHash) algorithm and Hamming distance is proposed. The traditional algorithm measures the similarity between neighborhood blocks by Euclidean distance, so the ability to preserve edges and details is weak, which leads to the blurred and distorted images after filtering. To this end, the Difference Hash algorithm containing the gradient information is introduced, the difference hash images are generated from neighborhood blocks, and the Hamming distance of the difference hash images is calculated to measure the similarity of the neighborhood blocks. Finally, the Euclidean distance is improved. Experiment results show that the proposed method can preserve edges and details while denoising the low-noise images. Compared with other improved algorithms, the running speed of the proposed algorithm is also greatly improved, which has a certain application value.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115431759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Influenza virus detection technology based on organic electrochemical transistor 基于有机电化学晶体管的流感病毒检测技术
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631378
Nan Li, Xiangxi Lou, Beini Chen, Jianhui Gu, Bo Liang, Tianyu Li
{"title":"Influenza virus detection technology based on organic electrochemical transistor","authors":"Nan Li, Xiangxi Lou, Beini Chen, Jianhui Gu, Bo Liang, Tianyu Li","doi":"10.1117/12.2631378","DOIUrl":"https://doi.org/10.1117/12.2631378","url":null,"abstract":"Influenza results in massive casualties and property loss each year due to the high infectivity and multiple variation of its virus. Thus, early diagnosis of influenza viruses plays a crucial role, however rapid an on-site detection can hardly be achieved currently. Organic electrochemical transistor (OECT) has the characteristics of high sensitivity, fast response speed and good biocompatibility, and has been widely used in the detection of DNA and protein. In this work, we developed an OECT-based influenza virus sensor. Through the detection of HA peptide antigens, it shows that the sensor has a detection limit of less than 10-9M.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124825719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on task allocation of multi-UAVs based on improved Particle Swarm Optimization algorithm 基于改进粒子群算法的多无人机任务分配研究
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631463
Pengcheng Wen, J. Zhang
{"title":"Research on task allocation of multi-UAVs based on improved Particle Swarm Optimization algorithm","authors":"Pengcheng Wen, J. Zhang","doi":"10.1117/12.2631463","DOIUrl":"https://doi.org/10.1117/12.2631463","url":null,"abstract":"Task allocation of multiple unmanned aerial vehicles (multi-UAVs) is a typical NP-hard problem. In this paper, according to practical battlefield needs, mathematical model is constructed based on complex constrains of task allocation, and objective function is constructed based on multi-UAVs’ global voyage and task time. An improved strategy of particle position based on basic Particle Swarm Optimization (PSO) algorithm is applied to the problem, and reasonable allocation schemes are obtained. The allocation schemes meet the complex constrains including task sequence, time window, UAVs’ capacities and flight path, and can be chosen and adjusted flexibly by the decision maker according to the practical battlefield needs. A large number of simulation experiments show that improved PSO algorithm is effective and provides a reference for multi-UAVs’ task allocation problem with complex constrains and multi-objectives.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124735910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Shape-driven multiple extended target tracking and classification based on B-Spline and PHD filter 基于b样条和PHD滤波器的形状驱动多扩展目标跟踪与分类
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631562
Fang Li, Jinlong Yang
{"title":"Shape-driven multiple extended target tracking and classification based on B-Spline and PHD filter","authors":"Fang Li, Jinlong Yang","doi":"10.1117/12.2631562","DOIUrl":"https://doi.org/10.1117/12.2631562","url":null,"abstract":"Gaussian inverse Wishart probability hypothesis density (GIW-PHD) filter has been considered a promising algorithm for tracking an unknown number of multiple extended targets (MET) with ellipsoidal shapes. However, when the MET are close to one another with irregularly varying shapes, the tracking accuracy will degrade seriously due to the incorrect measurement partition. To address the problem, we propose a new multiple extended target tracking and classification algorithm based on the shape driven strategy under the framework of PHD. First, the B-spline curve technique is employed to estimate the irregular MET shapes, and then the shape features are extracted for improving the measurement partition and state update for the closely spaced MET. Finally, the MET are classified according to the estimated shape information and the Gaussian mixture implementation of the proposed algorithm is derived and presented in this work. Experimental results show that the proposed technique has a better tracking performance than the existing GIW-PHD for the closely spaced MET with irregular shapes.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132698752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Encryption technology of OFDM satellite system based on five-dimensional hyperchaotic synchronization 基于五维超混沌同步的OFDM卫星系统加密技术
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631549
Jiahao Li, Yuanxiang Chen, Yijun Deng, Changqi Liu, Fan Lu, Bing Ma, Luchen Zhang, Jingshuang Cheng, Jianguo Yu
{"title":"Encryption technology of OFDM satellite system based on five-dimensional hyperchaotic synchronization","authors":"Jiahao Li, Yuanxiang Chen, Yijun Deng, Changqi Liu, Fan Lu, Bing Ma, Luchen Zhang, Jingshuang Cheng, Jianguo Yu","doi":"10.1117/12.2631549","DOIUrl":"https://doi.org/10.1117/12.2631549","url":null,"abstract":"This paper proposes a novel 5-dimensional hyperchaotic coupling synchronization system for physical layer security in OFDM satellite systems. The proposed approach is designed based on the Lyapunov stability theory. The proposed chaotic-based satellite data encryption/decryption system is validated using a numerical simulation study. Additionally, to demonstrate the efficiency of the proposed chaotic encryption structure, we analyzed its key space. The proposed chaotic encryption structure is very sensitive to the initial key, and a tiny discrepancy as small as 10−19 would lead to a completely different sequence. The key space of the proposed scheme is up to 10340.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114669862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Derivative feature and residual spatial attention for low-light image enhancement 弱光图像增强中的导数特征和剩余空间注意
International Conference on Signal Processing Systems Pub Date : 2022-05-01 DOI: 10.1117/12.2631553
Qihan Li, S. Kamata
{"title":"Derivative feature and residual spatial attention for low-light image enhancement","authors":"Qihan Li, S. Kamata","doi":"10.1117/12.2631553","DOIUrl":"https://doi.org/10.1117/12.2631553","url":null,"abstract":"Images taken in low-light conditions often have the problem of poor visibility. Besides inadequate lightings, different types of image quality degradation, such as a large amount of noise and color loss due to the limited quality of cameras and camera ISO setting, cause low quality of the captured image. However, directly amplifying the darkness of the lowlight image will inescapably bring into the pollution of the image. Therefore, the task of low-light image enhancement needs to kindle the dark regions and remove image degradation. To achieve this task, our work builds a Retinex theorybased neural network, which decomposes the input images into an illumination map and a reflectance map. Illumination map, representing the light information, is used for brightness adjustment, while reflectance map, representing the color information, is responsible for reconstructing low-light image into enhanced image with adjusted illumination map. However, there are few studies that notice the derivative of the image is used to solve the noise problem in Retinex decomposition and use spatial attention-based residual structures to increase the effect of light enhancement. For Decomposition sub-Network (Decom-Net), we purpose derivative features to alleviate the occurrence of noise in the reflectance map in the process of low-light image decomposition. For Illumination Enhancement sub-Network (Relight- Net), we use the Gaussian blur for reducing the problem of brightness enhancement degradation and build the Residual Spatial Attention Block (RSAB) to enlarge the volume and increase the capability of pixel-to-pixel mapping. Experiments are implemented to shows the effectiveness of our network, which improves the performance of previous methods on a large scale.","PeriodicalId":415097,"journal":{"name":"International Conference on Signal Processing Systems","volume":"55 7-8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132286034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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