TY - JOUR
T1 - Orthogonal frequency division multiplexing phenomenology
T2 - Recognition of canonical scatterers using flat spectra OFDM pulses
AU - Lellouch, Gabriel
AU - Mishra, Amit Kumar
AU - Inggs, Michael
N1 - Publisher Copyright:
© The Institution of Engineering and Technology 2016.
PY - 2016/4/1
Y1 - 2016/4/1
N2 - In this study, the authors present a novel approach to characterise scattering centres from their radar return using specially designed waveforms. The widely accepted scattering model derived from the geometrical theory of diffraction is considered. They show how the use of flat spectrum orthogonal frequency division multiplexing pulses can help discriminating between the various scattering mechanisms. The technique, which assumes prior information about the target runs into two steps. The first step consists of designing pulses of appropriate length to mitigate intersymbol interference when several scatterers compose the target. In the second step, they calculate the spectrum of the received echo and estimate the slope of this spectrum, whose value is used to infer the scatterer type. Eventually, they assess the sensitivity of this approach with respect to additive white Gaussian noise in terms of the overall probability of correct classification and show that an integration technique can help improve the classification rate even in low signal-to-noise ratio conditions.
AB - In this study, the authors present a novel approach to characterise scattering centres from their radar return using specially designed waveforms. The widely accepted scattering model derived from the geometrical theory of diffraction is considered. They show how the use of flat spectrum orthogonal frequency division multiplexing pulses can help discriminating between the various scattering mechanisms. The technique, which assumes prior information about the target runs into two steps. The first step consists of designing pulses of appropriate length to mitigate intersymbol interference when several scatterers compose the target. In the second step, they calculate the spectrum of the received echo and estimate the slope of this spectrum, whose value is used to infer the scatterer type. Eventually, they assess the sensitivity of this approach with respect to additive white Gaussian noise in terms of the overall probability of correct classification and show that an integration technique can help improve the classification rate even in low signal-to-noise ratio conditions.
UR - http://www.scopus.com/inward/record.url?scp=84961705120&partnerID=8YFLogxK
U2 - 10.1049/iet-rsn.2014.0469
DO - 10.1049/iet-rsn.2014.0469
M3 - Article
AN - SCOPUS:84961705120
SN - 1751-8784
VL - 10
SP - 647
EP - 654
JO - IET Radar, Sonar and Navigation
JF - IET Radar, Sonar and Navigation
IS - 4
ER -