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作 者:Hao Wu Peng-fei Wu Zhang-song Shi Shi-yan Sun Zhong-hong Wu
机构地区:[1]School of Ordnance Engineering,Naval University of Engineering,Wuhan,430033,China
出 处:《Defence Technology(防务技术)》2023年第7期231-248,共18页Defence Technology
摘 要:In the internet of battlefield things, ammunition is becoming networked and intelligent, which depends on location information. Therefore, this paper focuses on the self-organized network collaborative localization of munitions with an aerial three-dimensional(3D) highly-dynamic topographic structure under a satellite denied environment. As for aerial networked munitions, the measurement of munitions is objectively incomplete due to the degenerated and interrupted link of munitions. For this reason, a cluster-oriented collaborative localization method is put forward in this paper. Multidimensional scaling(MDS) was first integrated with a trilateration localization method(TLM) to construct a relative localization algorithm for determining the relative location of a mobile cluster network. The information related to relative velocity was then combined into a collaborative localization framework to devise a TLM-vMDS algorithm. Finally, an iterative refinement algorithm based on scaling by majorizing a complicated function(SMACOF) was employed to effectively eliminate the influence of incomplete link observation on localization accuracy. Compared with the currently available advanced algorithms, the proposed TLM-vMDS algorithm achieves higher localization accuracy and faster convergence for a cluster of extensively networked munitions, and also offers better numerical stability and robustness for highspeed motion models.
关 键 词:Highly-dynamic topographic structure MDS Relative ranging Aerial ammunition ad hoc network
分 类 号:TJ410[兵器科学与技术—火炮、自动武器与弹药工程]
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