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基于人工智能的光电搜跟技术研究 被引量:1
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作者 石毅 毕斯琴 《科技与创新》 2020年第18期26-27,共2页
在惯性空间中,采用光电搜跟技术能够保持稳定探测视轴,精确跟踪目标。但在实际应用过程中,雷达探测结果容易受到扰动,使系统性能受到影响。基于此,对人工智能用于改进光电搜跟技术的思路进行了探讨,对基于人工智能的光电搜跟系统、智能... 在惯性空间中,采用光电搜跟技术能够保持稳定探测视轴,精确跟踪目标。但在实际应用过程中,雷达探测结果容易受到扰动,使系统性能受到影响。基于此,对人工智能用于改进光电搜跟技术的思路进行了探讨,对基于人工智能的光电搜跟系统、智能算法、航迹跟踪等内容展开了研究,为关注这一话题的人们提供参考。 展开更多
关键词 人工智能 光电搜跟技术 航迹跟踪 目标跟踪分析
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Underwater multiple target tracking decision making based on an analytic network process
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作者 王汝夯 黄建国 张群飞 《Journal of Marine Science and Application》 2009年第4期305-310,共6页
Underwater multi-target tracking logic and decision (UMTLD) has difficulty resolving multi-target tracking problems for underwater vehicles. Present methods assume factors in UMTLD are uncorrelated, when these are a... Underwater multi-target tracking logic and decision (UMTLD) has difficulty resolving multi-target tracking problems for underwater vehicles. Present methods assume factors in UMTLD are uncorrelated, when these are actually in a complex, interdependent relationship. To provide this, an index set of multi-target tracking decision characteristics and an analytic network process (ANP) model of the UMTLD method was -established. This method brings the index set of multi-target tracking decision into the ANP model, and the optimization multitarket tracking decision is achieved via computation of the resulting supermatrix. The rationality and robustness of decision results increase in simulations by 13% and 47% respectively with analytic hierarchy process (AHP). These results indicate that the ANP method should be the preferred method when UMTLD factors are interdependent. 展开更多
关键词 analytic network process (ANP) underwater multi-target tracking DECISION tracking logic
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Prediction-based energy-efficient target tracking protocol in wireless sensor networks 被引量:3
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作者 BHUIYAN M.Z.A. 王国军 +1 位作者 张力 彭勇 《Journal of Central South University》 SCIE EI CAS 2010年第2期340-348,共9页
A prediction based energy-efficient target tracking protocol in wireless sensor networks(PET) was proposed for tracking a mobile target in terms of sensing and communication energy consumption.In order to maximize the... A prediction based energy-efficient target tracking protocol in wireless sensor networks(PET) was proposed for tracking a mobile target in terms of sensing and communication energy consumption.In order to maximize the lifetime of a wireless sensor network(WSN),the volume of messages and the time for neighbor discovery operations were minimized.The target was followed in a special region known as a face obtained by planarization technique in face-aware routing.An election process was conducted to choose a minimal number of appropriate sensors that are the nearest to the target and a wakeup strategy was proposed to wakeup the appropriate sensors in advance to track the target.In addition,a tracking algorithm to track a target step by step was introduced.Performance analysis and simulation results show that the proposed protocol efficiently tracks a target in WSNs and outperforms some existing protocols of target tracking with energy saving under certain ideal situations. 展开更多
关键词 wireless sensor networks target tracking wakeup mechanism face-aware routing energy efficiency
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A Sensor-Service Collaboration Approach for Target Tracking in Wireless Camera Networks 被引量:1
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作者 Shuai Zhao Le Yu 《China Communications》 SCIE CSCD 2017年第7期44-56,共13页
Mobile target tracking is a necessary function of some emerging application domains, such as virtual reality, smart home and intelligent healthcare. However, existing portable devices for target tracking are resource ... Mobile target tracking is a necessary function of some emerging application domains, such as virtual reality, smart home and intelligent healthcare. However, existing portable devices for target tracking are resource intensive and high-cost. Camera tracking is an effective location tracking way for those emerging applications which can reuse the existing ubiquitous video monitoring system. This paper proposes a dynamic community-based camera collaboration(D3C) framework for target location and tracking. The contributions of D3C mainly include that(1) nonlinear perspective projection model is selected as the camera sensing model and sequential Monte Carlo is employed to predict the target location;(2) a dynamic collaboration scheme is proposed, it is based on the local community-detection theory deriving from social network analysis. The performance of proposed approach is validated by both synthetic datasets and real-world application. The experiment results show that D3C meets the versatility, real-time and fault tolerance requirements of target tracking applications. 展开更多
关键词 service collaboration camera tracking community detection sequential monte carlo
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