RADAR BIG DATA REDUCTION USING HARDWARE AND SOFTWARE SOLUTIONS

被引：0

作者：

Nahar, Sabikun ^{[1
]}

Ren, Lingyun ^{[1
]}

Fathy, Aly E. ^{[1
]}

Nghia Tran ^{[2
]}

Kilic, Ozlem ^{[2
]}

机构：

[1] Univ Tennessee, Elect Engn & Comp Sci Dept, Knoxville, TN 37996 USA

[2] Catholic Univ Amer, Elect Engn & Comp Sci Dept, Washington, DC 20064 USA

来源：

2017 INTERNATIONAL APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY SYMPOSIUM - ITALY (ACES) | 2017年

关键词：

SFCW; compressive sensing; fall detection;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Radars typically handle big data, and ways need to be developed to speed the data acquisition and processing. Here, we present methods to speed up step frequency continuous wave radar (SFCW) performance upon using multi-channels, compressive sensing algorithms, in addition to efficient OMP algorithms, and accelerated platforms for signal reconstruction based on FPGAs and GPUs.

引用

页数：2

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