摘要
文中主要研究无源测向定位中测向数据关联方法。数据关联是多传感器多目标测向交叉定位中的关键问题,主要作用是快速、准确地确定源于同一个辐射源的测向线。在数据关联方面,有效的方法是多维分配算法。但是多维分配在维度大于2时是一个NP-hard问题。文中针对被动多传感器的量测数据关联问题,提出了一种基于传感器基线分组的快速数据关联算法,通过将三个传感器的量测分成四组进行关联,减少了候选关联集数量,有效提高了计算效率。首先对量测基于传感器基线进行分组并通过关联判据对所有可能正确的组合进行筛选,得到候选关联集,然后对候选关联集进行分析得到正确关联集。通过试验仿真,验证了文中方法在降低算法复杂度、提高算法准确率方面效果良好。
The data association method in passive location is researched mainly. Data association is a key issue in multi- sensor multi-target direction- finding crossing location,it is the problem of determining which target,if any,a particular measurements originates. In terms of data association,an effective approach is multidimensional assignment algorithm. While multidimensional assignment is an NP-hard problem for dimension over 2. In consideration of the measurement data association problem of multiple passive sensors,an effective solution by partitioning the measurements via sensor- based baseline was presented,and the measurements of three sensors is transformed into measurements of two sensors about four groups. This method reduced the number of candidate set and effectively improved the computational efficiency. Firstly,the measurements of three sensors were divided into four groups and generating a set of candidate association according to related criteria associated. Secondly,the correct pair of association set was picked out after analysis. Simulation showed that the method proposed has improved the algorithm accuracy,with less computation time.
出处
《计算机技术与发展》
2016年第2期110-113,共4页
Computer Technology and Development
基金
国家"863"高技术发展计划项目(2013AA013902)
关键词
无源定位
数据关联
测向线
视线距离
crossing location
data association
measurements
line-of-sight range
