TY - JOUR
T1 - A high-precision instantaneous frequency (IF) estimation method of multi-component Chirp signals
AU - Wang, Baihe
AU - Huang, Jianguo
AU - Xu, Guimin
AU - Zhang, Qunfei
PY - 2008/2
Y1 - 2008/2
N2 - Aim: Under certain conditions, the Wigner distribution maxima (WDM) method gives inaccurate estimation of the IF of multi-component Chirp signal. We now present a new Wigner distribution Viterbi fitting (WDVF) method that can estimate such IF with much higher precision. In the full paper, we explain the WDVF method in some detail; in this abstract, we just add some pertinent remarks to listing the two topics of explanation. The first topic is: The WDM method of IF estimation. In this topic, we point out that IF estimation errors increase because the WDM often deviate from their true values if the signal to noise ratio (SNR) is low. The second topic is: The IF estimation method based on the WDVF method. Under this method, we transform the Wigner distribution of the Chirp signal into digital image and apply the Viterbi algorithm to separating the multi-component Chirp signal into individual-component signals. Then we carry out the linear fitting of the individual components thus separated and obtain their IFs estimated by the WDVF method, as shown in Fig. 3 (c) in the full paper. Finally we simulate and analyze the performance of the WDVF method by comparing it with the WDM method. The simulation results, shown in Fig. 4 in the full paper, indicate preliminarily that the WDVF method reduces considerably the IF estimation errors under low SNR and effectively suppresses the time-frequency interference items and edge effects. Its performance is better than the WDM method, especially under low SNR. When SNR is-15 dB to-8 dB, the WDVF method can reduce the mean square error by approximately 50% compared with the WDM.
AB - Aim: Under certain conditions, the Wigner distribution maxima (WDM) method gives inaccurate estimation of the IF of multi-component Chirp signal. We now present a new Wigner distribution Viterbi fitting (WDVF) method that can estimate such IF with much higher precision. In the full paper, we explain the WDVF method in some detail; in this abstract, we just add some pertinent remarks to listing the two topics of explanation. The first topic is: The WDM method of IF estimation. In this topic, we point out that IF estimation errors increase because the WDM often deviate from their true values if the signal to noise ratio (SNR) is low. The second topic is: The IF estimation method based on the WDVF method. Under this method, we transform the Wigner distribution of the Chirp signal into digital image and apply the Viterbi algorithm to separating the multi-component Chirp signal into individual-component signals. Then we carry out the linear fitting of the individual components thus separated and obtain their IFs estimated by the WDVF method, as shown in Fig. 3 (c) in the full paper. Finally we simulate and analyze the performance of the WDVF method by comparing it with the WDM method. The simulation results, shown in Fig. 4 in the full paper, indicate preliminarily that the WDVF method reduces considerably the IF estimation errors under low SNR and effectively suppresses the time-frequency interference items and edge effects. Its performance is better than the WDM method, especially under low SNR. When SNR is-15 dB to-8 dB, the WDVF method can reduce the mean square error by approximately 50% compared with the WDM.
KW - Instantaneous frequency (IF) estimation
KW - Multi-component Chirp signal
KW - Wigner distribution maxima (WDM)
KW - Wigner distribution Viterbi fitting (WDVF) method
UR - http://www.scopus.com/inward/record.url?scp=41649094671&partnerID=8YFLogxK
M3 - 文章
AN - SCOPUS:41649094671
SN - 1000-2758
VL - 26
SP - 83
EP - 87
JO - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
JF - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
IS - 1
ER -