Research on Automatic Target Recognition in High-Performance Reconfigurable Computing

提议的工作将通过使用其将算法映射到可重构硬件的工具来支持高性能可重构计算中心（CHREC）的研究。所要测试的算法是自动目标识别（ATR）算法的预处理和特征提取部分。本研究的目的是研究隐马尔可夫模型（HMM）算法应用于ATR时的计算复杂度。拟议的研究将允许对目前CHREC行业成员不支持的应用领域进行调查。提出的工作将提供将信号处理算法映射到可重构硬件的尖端工具。这套技能在电信和国防工业中变得越来越普遍。拟议的研究将在一所历史上的黑人学院/大学（HBCU）进行，并将利用在STEM领域代表性不足的本科生，并让他们接触研究活动。

The proposed work will support the research of the Center for High-Performance Reconfigurable Computing (CHREC) by using its tools for mapping algorithms onto reconfigurable hardware. The algorithms to be tested are the preprocessing and feature extraction portion of automatic target recognition (ATR) algorithms. The objective of the proposed work is study the computational complexities associated with hidden Markov model (HMM) algorithms when applied to ATR. The proposed research will allow investigation of application areas that are not supported by the current CHREC industry members. The proposed work will provide access to cutting edge tools for mapping signal processing algorithms onto reconfigurable hardware. This set of skills is becoming more prevalent in the telecommunication and defense industries. The proposed research will be performed at a Historically Black College/University (HBCU), and will utilize undergraduates who are underrepresented in the STEM fields and give them with exposure to research activities.