Accelerating search based on truncated convolution for rapid detection of linear frequency modulated signals
Author(s) -
Cao Huawei,
Fu Tuo,
Gao Meiguo
Publication year - 2015
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2015.0032
Subject(s) - convolution (computer science) , algorithm , computer science , mathematics , artificial intelligence , artificial neural network
This study investigates the problem of rapid detection of linear frequency modulated signals. An accelerating search algorithm is proposed based on the classical dechirp method. The fast Fourier transform operation is substituted with the truncated convolution in the dechirp method, and then a compatible search strategy is presented. The computational load of the proposed method is reduced. With the increasing length of the input signal, the presented method enhances the computational efficiency more obviously. Both the theoretical analysis and simulation results show that the detection performance of this method is desirable in the case of low signal‐to‐noise ratio; thus, it could be a competitive candidate for applications in engineering practices.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom