TY - GEN
T1 - Multi-component LFM signal detection based on DIRFAT algorithm
AU - Zhao, Langxu
AU - Tao, Haihong
AU - Su, Jia
AU - Chen, Weijia
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - A novel algorithm based on Discrete-Improved-Radon-Fourier-Ambiguity-Transform (DIRFAT) is proposed for linear frequency modulated (LFM) signal detection and parameter estimation in this paper. By the proposed algorithm, the components can be coherently integrated into distinct peaks on DIRFAT plane, and their parameters can be estimated simultaneously. The proposed algorithm consists of three stages. Firstly, eliminate the linear chirp rate of the every component on discrete ambiguity function (DAF) plane by axis rotation (AR). Afterward, compensate the phase item caused by AR. Otherwise, the energy of the components may spread. Finally, coherently integrate the components and realize components detection. Compared with several existing algorithms, DIRFAT algorithm has better parameter estimation accuracy. Both simulations and real data processing demonstrate that DIRFAT algorithm can detect and analyze Multi-component LFM signals effectively without the affection of the cross-terms.
AB - A novel algorithm based on Discrete-Improved-Radon-Fourier-Ambiguity-Transform (DIRFAT) is proposed for linear frequency modulated (LFM) signal detection and parameter estimation in this paper. By the proposed algorithm, the components can be coherently integrated into distinct peaks on DIRFAT plane, and their parameters can be estimated simultaneously. The proposed algorithm consists of three stages. Firstly, eliminate the linear chirp rate of the every component on discrete ambiguity function (DAF) plane by axis rotation (AR). Afterward, compensate the phase item caused by AR. Otherwise, the energy of the components may spread. Finally, coherently integrate the components and realize components detection. Compared with several existing algorithms, DIRFAT algorithm has better parameter estimation accuracy. Both simulations and real data processing demonstrate that DIRFAT algorithm can detect and analyze Multi-component LFM signals effectively without the affection of the cross-terms.
KW - axis rotation (AR)
KW - coherent integration
KW - linear frequency modulated (LFM) signal
UR - https://www.scopus.com/pages/publications/85091891143
U2 - 10.1109/ICSIDP47821.2019.9172945
DO - 10.1109/ICSIDP47821.2019.9172945
M3 - 会议稿件
AN - SCOPUS:85091891143
T3 - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
BT - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019
Y2 - 11 December 2019 through 13 December 2019
ER -