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Novel sensor selection strategy for LPI based on an improved IMMPF tracking method

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Journal of Systems Engineering and Electronics 2014年第6期25卷 1004-1010页

作者： zhenkai zhang Jiehao Zhu Yubo Tian Hailin Li College of Electronic Information Jiangsu University of Science and Technology Science and Technology on Electronic Information Control Laboratory Key Laboratory of Radar Imaging and Microwave Photonics Nanjing University of Aeronautics and Astronautics

Sensor platforms with active sensing equipment such as radar may betray their existence, by emitting energy that will be intercepted by enemy surveillance sensors. The radar with less emission has more excellent performance of the low probability of intercept（LPI）. In order to reduce the emission times of the radar, a novel sensor selection strategy based on an improved interacting multiple model particle filter（IMMPF） tracking method is presented. Firstly the IMMPF tracking method is improved by increasing the weight of the particle which is close to the system state and updating the model probability of every particle. Then a sensor selection approach for LPI takes use of both the target＇s maneuverability and the state＇s uncertainty to decide the radar＇s radiation time. The radar will work only when the target＇s maneuverability and the state＇s uncertainty exceed the control capability of the passive sensors. Tracking accuracy and LPI performance are demonstrated in the Monte Carlo simulations.

关键词： sensor selection low probability of intercept(LPI) interacting multiple model(IMM) particle filter target tracking

Multiple-target tracking with adaptive sampling intervals for phased-array radar

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Journal of Systems Engineering and Electronics 2011年第5期22卷 760-766页

作者： zhenkai zhang Jianjiang Zhou Fei Wang Weiqiang Liu Hongbing Yang College of Information Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing 210016 E R. China College of Electronic Information Jiangsu University of Science and Technology Zhenjiang 212003 E R. China

A novel adaptive sampling interval algorithm for multitarget tracking is presented. This algorithm which is based on interacting multiple models incorporates the grey relational grade （GRG） into the particle swarm optimization （PSO）. Firstly, the desired tracking accuracy is set for each target. Secondly, sampling intervals are selected as particles, and then the advantage of the GRG is taken as the measurement function for resource management. Meanwhile, the fitness value of the PSO is used to measure the difference between desired tracking accuracy and estimated tracking accuracy. Finally, it is suggested that the radar should track the target whose prediction value of the next sampling interval is the smallest. Simulations show that the proposed method improves both the tracking accuracy and tracking efficiency of the phased-array radar.

关键词： target tracking adaptive sampling interval (ASI) particle swarm optimization (PSO) grey relational grade (GRG) phased-array radar.

Research on energy structure and development strategy from 2010 to 2015 in Qingdao, China

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Chinese Journal of Population,Resources and Environment 2017年第3期15卷 239-248页

作者： Feifei Liu Yaoqi Zhou zhenkai zhang Tengfei Zhou School of Geosciences China University of Petroleum Function Laboratory for Marine Mineral Resource Geology and Exploration Qingdao National Laboratory of Marine Science and Technology

With the fast development of Qingdao's economy, the energy consumption is increasing significantly. In this paper, based on the energy statistic data in Qingdao area from 2010 to 2015,energy consumption structure was analyzed, indicating the existence of single energy structure;that is, coal, petroleum, and natural gas are dominant in the area. Thus, some issues between energy supply and demand have been brought. To solve present problem, we put forward to formulate the development strategy of energy, including energy savings, the exploitation of petroleum and natural gas resources, the development and utilization of renewable energy sources, and energy policy. It is worthy of mentioning that, according to the geological investigation, the shale gas may be abundant in Qingdao area and the gas resource amount estimated is huge. This is our first finding, important for developing unconventional energy and adjusting the energy structure in Qingdao in the future. Therefore, we suggest that Qingdao government should take action to develop local new energy resources for satisfying the energy demand.

关键词： Qingdao energyconsumption structure petroleum and gas renewable energy

Short-Term Prediction of Photovoltaic Power Based on DBSCAN-SVM Data Cleaning and PSO-LSTM Model

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Energy Engineering 2024年第10期121卷 3019-3035页

作者： Yujin Liu zhenkai zhang Li Ma Yan Jia Weihua Yin Zhifeng Liu School of Energy and Power Engineering Inner Mongolia University of TechnologyHohhot010051China Key Laboratory ofWind Energy and Solar Energy Utilization Technology Ministry of EducationHohhot010051China Production Management Department Inner Mongolia Energy Power Generation Investment Group Co.Ltd.Hohhot010051China

Accurate short-termphotovoltaic(PV)power prediction helps to improve the economic efficiency of power stations and is of great significance to the arrangement of grid scheduling *** order to improve the accuracy of PV power prediction further,this paper proposes a data cleaning method combining density clustering and support vector *** constructs a short-termPVpower predictionmodel based on particle swarmoptimization(PSO)optimized Long Short-Term Memory(LSTM)***,the input features are determined using Pearson’s correlation *** feature information is clustered using density-based spatial clustering of applications withnoise(DBSCAN),and then,the data in each cluster is cleanedusing support vectormachines(SVM).Secondly,the PSO is used to optimize the hyperparameters of the LSTM network to obtain the optimal network ***,different power prediction models are established,and the PV power generation prediction results are *** results show that the data methods used are effective and that the PSO-LSTM power prediction model based on DBSCAN-SVM data cleaning outperforms existing typical methods,especially under non-sunny days,and that the model effectively improves the accuracy of short-term PV power prediction.

关键词： Photovoltaic power prediction LSTM network DBSCAN-SVM PSO deep learning

Target parameter estimation for OTFS-integrated radar and communications based on sparse reconstruction preprocessing

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Frontiers of Information Technology & Electronic Engineering 2024年第5期25卷 742-754页

作者： zhenkai zhang Xiaoke SHANG Yue XIAO Ocean College Jiangsu University of Science and TechnologyZhenjiang 212003China

Orthogonal time-frequency space(OTFS)is a new modulation technique proposed in recent years for high Doppler wireless *** solve the parameter estimation problem of the OTFS-integrated radar and communications system,we propose a parameter estimation method based on sparse reconstruction preprocessing to reduce the computational effort of the traditional weighted subspace fitting(WSF)***,an OTFS-integrated echo signal model is ***,the echo signal is transformed to the time domain to separate the target angle from the range,and the range and angle of the detected target are coarsely estimated by using the sparse reconstruction ***,the WSF algorithm is used to refine the search with the coarse estimate at the center to obtain an accurate *** simulations demonstrate the effectiveness and superiority of the proposed parameterestimation algorithm.

关键词： Integrated radar and communications system Orthogonal time-frequency space Target parameter estimation Sparse reconstruction Weighted subspace fitting

Late Mesozoic rifting and its deep dynamic mechanisms in the central Sulu orogenic belt: Records from Lingshan Island

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Science China Earth Sciences 2022年第9期65卷 1751-1771页

作者： Tengfei ZHOU Yaoqi ZHOU Nina SФAGER Paul Martin HOLM zhenkai zhang Jun WANG Zhao LIANG Hongyu MU Yanjun CHENG Feifei LIU Miao WANG Yue zhang Hui zhang Yangjian GU Shihui DONG Hanjie ZHAO Manjie LI Yang CHEN Yanzi LIU School of Geosciences China University of Petroleum(East China)Qingdao 266580China Department of Geosciences and Natural Resource Management University of CopenhagenCopenhagen-K 1350Denmark Shandong Provincial Key Laboratory of Deep Oil&Gas China University of Petroleum(East China)Qingdao 266580China Shaanxi Center of Mineral Geological Survey Shaanxi Institute of Geological SurveyXi'an 710068China School of Earth Sciences Yunnan UniversityKunming 650500China Department of Science and Technology Hebei GEO UniversityShijiazhuang 050031China College of Earth Science and Engineering Shandong University of Science and TechnologyQingdao 266590China School of Architectural Engineering Binzhou UniversityBinzhou 256500China Research Institute of Petroleum Exploration and Development Shengli Oilfield CompanySINOPECDongying 257015China Key Laboratory of Geological Safety of Coastal Urban Underground Space Ministry of Natural ResourcesQingdao Geo-Engineering Surveying InstituteQingdao 266101China

The Lingshan Island scientific drill confirms that two episodes(Laiyang period and Qingshan period) of rifting developed in the central Sulu orogenic belt(SOB) in Late Mesozoic. With a set of methods including fieldwork, drilling, core logging, zircon U-Pb dating and whole rock geochemistry applied, the age, the depositional sequence and the deep dynamic mechanisms of rift evolution were unraveled. The stratigraphic sequence of the Laiyang-Qingshan Groups on Lingshan Island was composed of two different rifting sequences:(1) Laiyang Group(147–125 Ma), which consists of deep-water gravity flow deposits with interlayers of intermediate volcanic rocks;and(2) Lower Qingshan Group(125–119 Ma), which unconformably overlies the former sequence and contains subaerial volcanic deposits and terrestrial deposits. The tectonic environment changed during the evolution of these two episodes of rifting: the rift was in a NNW-SSE extensional environment in the Laiyang period and showed the typical passive rifting character that “lithospheric extension and rifting preceded volcanism”. The passive rifting period was ended by a short WNW-ESE compression at about 125 Ma. After that, the tectonic environment transferred to a strong NW-SE extensional environment and the rifting evolved into a volcanic arc basin in the Qingshan period. The igneous rocks are shoshonitic to high-K calc-alkaline trachyandesites to trachytes with a few intercalated lamprophyres and a *** geochemical characteristics of the igneous rocks indicate that they are mantle-derived melts with a metasomatized mantle source and/or crustal contamination. In addition, an increased thinning of the lithosphere happened during the rifting *** low-angle subduction of the Paleo-Pacific plate in the Jurassic weakened the thickened SOB lithospheric mantle. The rollback of the subducting plate started in late Jurassic to early Cretaceous, and the SOB lithospheric mantle was delaminated synchronously because of t

关键词： Sulu orogenic belt Lingshan Island Late Mesozoic Rifting Slab subduction Basin dynamics

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传感器位置浮动情况下的水下TDOA定位算法

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华中科技大学学报（自然科学版） 2021年第10期49卷 91-96页

作者：张贞凯江峰江苏科技大学电子信息学院江苏镇江212003

针对水下声源定位中传感器位置存在不确定性的问题,提出了一种基于两阶段加权最小二乘算法的水下目标定位算法.首先,当传感器位置浮动时,利用获取的到达时间差数据,将测量值噪声和传感器位置误差构造加权系数矩阵,通过加权最小二乘算法... 详细信息

针对水下声源定位中传感器位置存在不确定性的问题,提出了一种基于两阶段加权最小二乘算法的水下目标定位算法.首先,当传感器位置浮动时,利用获取的到达时间差数据,将测量值噪声和传感器位置误差构造加权系数矩阵,通过加权最小二乘算法估计目标位置;然后,通过引入目标定位误差构造定位方程;最后,用求解的目标定位误差调节上个阶段估计的目标位置.仿真结果表明:在传感器位置噪声较小情况下,本文算法具有较好的定位精度.

关键词：水下声源定位到达时间差定位传感器位置浮动加权最小二乘克拉美罗下界

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回波幅度信息辅助的群目标航迹起始方法

雷达学报（中英文） 2020年第4期9卷 723-729页

作者：靳标李聪张贞凯江苏科技大学电子信息学院镇江212003 西安交通大学电子与信息工程学院西安710049

航迹起始是群目标跟踪的首要环节,其性能好坏直接影响着目标跟踪航迹的质量。传统的群目标航迹起始方法仅利用目标的位置信息完成分群检测和等效量测求解等步骤,没有充分利用回波幅度信息,存在分群检测不理想、等效量测求解不准确等问题... 详细信息

航迹起始是群目标跟踪的首要环节,其性能好坏直接影响着目标跟踪航迹的质量。传统的群目标航迹起始方法仅利用目标的位置信息完成分群检测和等效量测求解等步骤,没有充分利用回波幅度信息,存在分群检测不理想、等效量测求解不准确等问题,有可能引起失跟现象。针对此问题,该文提出一种回波幅度信息辅助的群目标航迹起始方法。首先利用目标位置信息和幅度信息完成分群检测,然后综合采用幅度加权和位置加权求解等效量测,最后基于修正的逻辑法进行群目标航迹起始。该文方法在分群检测和求解等效量测等步骤充分利用了回波幅度信息,不仅可以在集群数量未知的情况下正确划分群,而且降低了失跟率,提高了群目标的跟踪性能。仿真结果验证了所提方法的有效性。

关键词：目标跟踪群目标航迹起始幅度信息聚类

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海相碳酸盐鲕粒形成过程的模拟实验研究

中国石油大学学报（自然科学版） 2017年第3期41卷 23-30页

作者：周瑶琪张晗张振凯中国石油大学地球科学与技术学院山东青岛266580

通过实验室模拟沉积环境的方法对鲕粒进行人工合成,探索鲕粒的形成过程及影响鲕粒形成的环境条件,实验的主要参数有体系中的藻类、体系的水动力和晶核数量。结果表明:静水条件及藻类活跃的人造海水中鲕粒的圈层结构及表面结晶程度发育最... 详细信息

通过实验室模拟沉积环境的方法对鲕粒进行人工合成,探索鲕粒的形成过程及影响鲕粒形成的环境条件,实验的主要参数有体系中的藻类、体系的水动力和晶核数量。结果表明:静水条件及藻类活跃的人造海水中鲕粒的圈层结构及表面结晶程度发育最好,说明较弱的水动力及藻类的生物作用有助于鲕粒的生长;体系中碳酸钙晶核的数量是鲕粒能否形成的决定因素。根据晶核数量及反应活化能的不同,对海相碳酸盐鲕粒及泥晶灰岩的形成过程进行动力学分析。

关键词：鲕粒藻类水动力晶核