TY - GEN
T1 - Ampliude based compressive sensing for UWB noise radar signal
AU - Wu, Ji
AU - Liang, Qilian
AU - Chen, Dechang
AU - Cheng, Xiuzhen
AU - Narayanan, Ram M.
PY - 2012
Y1 - 2012
N2 - Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-Nyquist signal acquisition. Ultra-wideband (UWB) noise radar is one of the novel techniques which is widely used in various applications such as emergency rescues and military operations. One challenging problem in UWB noise radar operation is that a huge amount of data will be received which requires tremendous storage space. Compressive sensing could easily handle his problem since it captures all the information we need from far fewer samples. In his paper, we propose a novel amplitude based compressive sensing algorithm to compress data without any knowledge in advance. Simulation results indicate that only 1/5 of original measurements are sufficient to recover original data, which also achieves a higher compression ratio than the conventional compressive sensing.
AB - Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-Nyquist signal acquisition. Ultra-wideband (UWB) noise radar is one of the novel techniques which is widely used in various applications such as emergency rescues and military operations. One challenging problem in UWB noise radar operation is that a huge amount of data will be received which requires tremendous storage space. Compressive sensing could easily handle his problem since it captures all the information we need from far fewer samples. In his paper, we propose a novel amplitude based compressive sensing algorithm to compress data without any knowledge in advance. Simulation results indicate that only 1/5 of original measurements are sufficient to recover original data, which also achieves a higher compression ratio than the conventional compressive sensing.
UR - http://www.scopus.com/inward/record.url?scp=84875649187&partnerID=8YFLogxK
U2 - 10.1109/GLOCOMW.2012.6477794
DO - 10.1109/GLOCOMW.2012.6477794
M3 - Conference contribution
AN - SCOPUS:84875649187
SN - 9781467349413
T3 - 2012 IEEE Globecom Workshops, GC Wkshps 2012
SP - 1430
EP - 1434
BT - 2012 IEEE Globecom Workshops, GC Wkshps 2012
T2 - 2012 IEEE Globecom Workshops, GC Wkshps 2012
Y2 - 3 December 2012 through 7 December 2012
ER -