Gpu Acceleration Of Threat Map Computation And Application To Selection Of Sonar Field Controls
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)(2015)
摘要
The Threat Probability Density Map displays the outcomes of the search effort prior to detection and is a digital representation of the probability density function of location of the existing undetected threat. The Threat Map readily provides such diagnostics as the probabilities of the threat being present in different areas of interest and this information can be utilised in selection of sensor field controls. In this work we consider a GPU acceleration of the Monte-Carlo technique for Threat Map computation and discuss application to sonobuoys.
更多查看译文
关键词
multistatic sonar,CUDA,GPU
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络