TY - JOUR
T1 - Sparse frequency waveform design for radar-embedded communication
AU - Mai, Chaoyun
AU - Sun, Jinping
AU - Zhou, Rui
AU - Wang, Guohua
N1 - Publisher Copyright:
© 2016 Chaoyun Mai et al.
PY - 2016
Y1 - 2016
N2 - According to the Tag application with function of covert communication, a method for sparse frequency waveform design based on radar-embedded communication is proposed. Firstly, sparse frequency waveforms are designed based on power spectral density fitting and quasi-Newton method. Secondly, the eigenvalue decomposition of the sparse frequency waveform sequence is used to get the dominant space. Finally the communication waveforms are designed through the projection of orthogonal pseudorandom vectors in the vertical subspace. Compared with the linear frequency modulation waveform, the sparse frequency waveform can further improve the bandwidth occupation of communication signals, thus achieving higher communication rate. A certain correlation exists between the reciprocally orthogonal communication signals samples and the sparse frequency waveform, which guarantees the low SER (signal error rate) and LPI (low probability of intercept). The simulation results verify the effectiveness of this method.
AB - According to the Tag application with function of covert communication, a method for sparse frequency waveform design based on radar-embedded communication is proposed. Firstly, sparse frequency waveforms are designed based on power spectral density fitting and quasi-Newton method. Secondly, the eigenvalue decomposition of the sparse frequency waveform sequence is used to get the dominant space. Finally the communication waveforms are designed through the projection of orthogonal pseudorandom vectors in the vertical subspace. Compared with the linear frequency modulation waveform, the sparse frequency waveform can further improve the bandwidth occupation of communication signals, thus achieving higher communication rate. A certain correlation exists between the reciprocally orthogonal communication signals samples and the sparse frequency waveform, which guarantees the low SER (signal error rate) and LPI (low probability of intercept). The simulation results verify the effectiveness of this method.
UR - https://www.scopus.com/pages/publications/84976524333
U2 - 10.1155/2016/7270301
DO - 10.1155/2016/7270301
M3 - 文章
AN - SCOPUS:84976524333
SN - 1024-123X
VL - 2016
JO - Mathematical Problems in Engineering
JF - Mathematical Problems in Engineering
M1 - 7270301
ER -