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在FPGA上进行并行粒子群优化,用于实时弹道目标跟踪.
Juhyeon Park1, Heoncheol Lee2, Hyuck-Hoon Kwon3
1School of Electronic Engineering, Kumoh National Institute of Technology, Gumi 39177, Republic of Korea.
Sensors (Basel, Switzerland)
|October 28, 2023
概括
本研究介绍了一种并行粒子群优化 (PSO) 方法,该方法由现场可编程门阵列 (FPGA) 加速,用于实时弹道目标跟踪. 与传统的PSO方法相比,这种方法显著减少了计算时间.
科学领域:
- * 航空航天工程 航空航天工程
- * 计算机科学 计算机科学
- * * 信号处理 信号处理
背景情况:
- * 实时跟踪高速弹道目标带来了重大的计算挑战.
- * 传统的粒子群优化 (PSO) 是计算密集型的,限制了其在实时系统中的应用.
- *测量模型和目标动态的非线性进一步使弹道目标跟踪复杂化.
研究的目的:
- * 为实时弹道目标跟踪开发加速粒子群优化 (PSO) 技术.
- * 为了解决传统PSO在高速跟踪场景中的计算时间限制.
- * 利用硬件加速来提高跟踪性能.
主要方法:
- * 实现一个并行粒子群优化 (PSO) 算法.
- * 使用现场可编程网关阵列 (FPGA) 进行PSO算法的硬件加速.
- * 在集成FPGA的异质处理系统上进行测试和分析.
主要成果:
- * 拟议的并行PSO成功实现了实时弹道目标跟踪.
- *跟踪结果与传统的公共服务组织方法相似.
- *与基于CPU的PSO相比,计算时间显著减少了3.89×.
结论:
- * 在FPGA上的并行PSO为实时弹道目标跟踪提供了可行的解决方案.
- * 硬件加速有效地克服了传统PSO的计算限制.
- * 拟议的方法在高速跟踪应用程序的处理速度方面取得了重大改进.
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