Sequential compressive target detection in wireless sensor networks - Details

author：

Zheng, Haifeng (Zheng, Haifeng.) ^[1] (Scholars：郑海峰) | Xiao, Shilin (Xiao, Shilin.) ^[2] | Wang, Xinbing (Wang, Xinbing.) ^[3]

Indexed by：

EI Scopus

Abstract：

Compressed　sensing　is　an　emerging　theory　which　provides　a　new　framework　for　sampling　and　compressing　a　sparse　signal　simultaneously　at　a　reduced　sampling　rate.　Besides　this,　compressed　sensing　also　provides　a　new　approach　for　the　task　of　detection.　Detection　from　compressive　measurements　without　reconstructing　the　signals　remains　as　a　challenging　problem.　In　this　paper,　we　investigate　the　performance　of　compressive　detection　and　propose　a　sequential　compressive　detection　scheme　to　reduce　the　number　of　measurements　for　target　detection　in　wireless　sensor　networks.　We　derive　the　sequential　compressive　decision　rules　and　analyze　its　detection　performance　in　terms　of　the　number　of　measurements.　Simulations　show　that　sequential　compressive　detection　can　save　about　50　percents　of　the　average　number　of　measurements　under　a　given　detection　performance　requirement　compared　with　that　of　compressive　detection.　©　2011　IEEE.

Keyword：

Compressed sensing Wireless sensor networks

Community：

[ 1 ] [Zheng, Haifeng]State Key Laboratory of Advanced Optical Communication Systems and Networks, Shanghai Jiao Tong University, China
[ 2 ] [Zheng, Haifeng]College of Physics and Information Engineering, Fuzhou University, China
[ 3 ] [Xiao, Shilin]State Key Laboratory of Advanced Optical Communication Systems and Networks, Shanghai Jiao Tong University, China
[ 4 ] [Wang, Xinbing]Dept. of Electronic Engineering, Shanghai Jiao Tong University, China