TY - GEN
T1 - Power Spectral Density Estimation of Radiated Noise with Sparse Spectral Fitting
AU - Jiang, Guoqing
AU - Sun, Chao
AU - Liu, Xionghou
AU - Jiang, Guangyu
AU - Duan, Wenjun
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/5
Y1 - 2020/10/5
N2 - When measuring the radiated noise from a noncooperative target by a small-aperture vertical array, the location of the noise source is usually unknown, so most measurement methods are ineffective. To solve this problem, we improve the sparse spectral fitting (SpSF) method so that it can be used to estimate the power spectral density (PSD) of radiated noise even though the source location is unknown. First, the experiment area is discretized and the sparse representation model of the received data is established. Then the PSD expression of the radiated noise is established by the covariance matrix in frequency-domain. Finally, the PSD and location of the radiated noise can be estimated simultaneously by the SpSF method. Simulation examples are given to demonstrate the performance of PSD estimation by SpSF.
AB - When measuring the radiated noise from a noncooperative target by a small-aperture vertical array, the location of the noise source is usually unknown, so most measurement methods are ineffective. To solve this problem, we improve the sparse spectral fitting (SpSF) method so that it can be used to estimate the power spectral density (PSD) of radiated noise even though the source location is unknown. First, the experiment area is discretized and the sparse representation model of the received data is established. Then the PSD expression of the radiated noise is established by the covariance matrix in frequency-domain. Finally, the PSD and location of the radiated noise can be estimated simultaneously by the SpSF method. Simulation examples are given to demonstrate the performance of PSD estimation by SpSF.
KW - non-cooperative target
KW - power spectral density estimation
KW - Radiated noise measurement
KW - sparse spectral fitting (SpSF)
UR - http://www.scopus.com/inward/record.url?scp=85104590055&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF38699.2020.9389169
DO - 10.1109/IEEECONF38699.2020.9389169
M3 - 会议稿件
AN - SCOPUS:85104590055
T3 - 2020 Global Oceans 2020: Singapore - U.S. Gulf Coast
BT - 2020 Global Oceans 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Global Oceans: Singapore - U.S. Gulf Coast, OCEANS 2020
Y2 - 5 October 2020 through 30 October 2020
ER -