TY - JOUR
T1 - Orthogonal frequency division multiplexing phenomenology
T2 - Radar technique combining genetic algorithm-based pulse design and energy detector for target recognition
AU - Lellouch, Gabriel
AU - Mishra, Amit Kumar
AU - Inggs, Michael
N1 - Publisher Copyright:
© The Institution of Engineering and Technology 2016.
PY - 2016/6/1
Y1 - 2016/6/1
N2 - This study investigates the benefit offered by the orthogonal frequency division multiplexing (OFDM) structure to enhance the recognition functionality in OFDM radar. The authors propose a novel phenomenology-based framework whereby the pulse is composed of several symbols each matched to a particular target and the recognition function in the receiver reduces to an energy detector. In this preliminary study, they make use of simple target models for which they have exact analytical expressions and apply genetic algorithm-based methods to design the symbols. They emphasise on the need to work within a less undeterministic environment and demonstrate the merit of the authors' technique with simulated results. Finally, they show how the integration of multiple echoes improves significantly the overall probability of correct classification despite additive white Gaussian noise.
AB - This study investigates the benefit offered by the orthogonal frequency division multiplexing (OFDM) structure to enhance the recognition functionality in OFDM radar. The authors propose a novel phenomenology-based framework whereby the pulse is composed of several symbols each matched to a particular target and the recognition function in the receiver reduces to an energy detector. In this preliminary study, they make use of simple target models for which they have exact analytical expressions and apply genetic algorithm-based methods to design the symbols. They emphasise on the need to work within a less undeterministic environment and demonstrate the merit of the authors' technique with simulated results. Finally, they show how the integration of multiple echoes improves significantly the overall probability of correct classification despite additive white Gaussian noise.
UR - http://www.scopus.com/inward/record.url?scp=84969651883&partnerID=8YFLogxK
U2 - 10.1049/iet-rsn.2014.0470
DO - 10.1049/iet-rsn.2014.0470
M3 - Article
AN - SCOPUS:84969651883
SN - 1751-8784
VL - 10
SP - 912
EP - 922
JO - IET Radar, Sonar and Navigation
JF - IET Radar, Sonar and Navigation
IS - 5
ER -