摘要
针对机载探测设备多传感器系统具有多目标,大量观测数据的特点,提出了一种基于Demp-ster-Shafer(D-S)证据理论和主观Bayesian方法组合的数据融合算法。在数据融合过程中,为保证融合的实时性,融合系统采用时域融合和空域融合相结合的方法,首先对相同传感器的各次抽样值进行时域融合,然后传感器之间的融合采用D-S方法进行融合;最后,其融合结果经概率转化后,与来自于ELINT(Electronic Intelligence)的信息通过主观Bayesian方法进行识别级融合。最后给出一个实例,经过仿真计算证明了该算法的可行性和实用性。
To aim at the the multitarget and vast observational data character of the airborne detection equipment multisensor system, this paper provides a combined data fusion algorithm which based on both Dempster- Sharer evidence theory and Subjective Bayesian algorithm. In the data fusion process, to guarantee real time fusion, the fusion system adopts a combination of time domain fusion and space domain fusion. Firstly, this algorithm makes time domain fusion to the sampling values of the same sensor. Secondly, the data fusion among the multiple sensors uses the D- S method. Finally, the fusion result translated by probability, and then makes recognition level fusion with the information from ELINT （ Electronic Intelligence） using the Subjective Bayesian algorithm. An example is present. The feasibility and practicability have been approved through computer simulation.
出处
《航空计算技术》
2009年第3期110-113,共4页
Aeronautical Computing Technique
关键词
信息融合
D-S证据理论
主观Bayesian算法
机载探测设备
Information fusion
dempster-sharer evidence theory
subjective bayesian algorithm
equipment airplane detecting
