TY - JOUR
T1 - Selection of dimensional normalization parameters in fractional Fourier transform
AU - Liu, Feng
AU - Xu, Hui Fa
AU - Tao, Ran
PY - 2011/2
Y1 - 2011/2
N2 - Dimensional normalization is required in the digital computation of the fractional Fourier transform, but how to select a suitable dimensional normalization parameter is not studied yet. For this reason, the influence of the dimensional normalization on the initial frequency, the chirp rate and the peak's position on the (p, u) plane is analyzed. And the relationship between the dimensional normalization parameter and the distance between two chirp signals' peaks at the p axis and the u axis is deduced. It is discovered that the distance between two peaks varies with the dimensional normalization parameter and it has maximums. A method is presented to choose the dimensional normalization parameter. By changing signals' observation time and sampling frequency, a suitable dimensional normalization parameter is selected to increase the distance between two signals' peaks and reduce the mutual influence among multi-component chirp signals. The effectiveness of this method is verified by the simulation results.
AB - Dimensional normalization is required in the digital computation of the fractional Fourier transform, but how to select a suitable dimensional normalization parameter is not studied yet. For this reason, the influence of the dimensional normalization on the initial frequency, the chirp rate and the peak's position on the (p, u) plane is analyzed. And the relationship between the dimensional normalization parameter and the distance between two chirp signals' peaks at the p axis and the u axis is deduced. It is discovered that the distance between two peaks varies with the dimensional normalization parameter and it has maximums. A method is presented to choose the dimensional normalization parameter. By changing signals' observation time and sampling frequency, a suitable dimensional normalization parameter is selected to increase the distance between two signals' peaks and reduce the mutual influence among multi-component chirp signals. The effectiveness of this method is verified by the simulation results.
KW - Chirp signal
KW - Dimensional normalization parameter selection
KW - Fractional Fourier transform
UR - http://www.scopus.com/inward/record.url?scp=79953809933&partnerID=8YFLogxK
U2 - 10.3969/j.issn.1001-506X.2011.02.01
DO - 10.3969/j.issn.1001-506X.2011.02.01
M3 - Article
AN - SCOPUS:79953809933
SN - 1001-506X
VL - 33
SP - 237
EP - 241
JO - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
JF - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
IS - 2
ER -