TY - JOUR
T1 - Design of polyphase sequence sets with good correlation properties under spectral distortion via majorization-minimization framework
AU - Wang, Changjie
AU - Zhang, Hao
AU - Ren, Wei
AU - Liu, Quanhua
N1 - Publisher Copyright:
© 2023 Elsevier Inc.
PY - 2024/2
Y1 - 2024/2
N2 - Orthogonal polyphase sequence sets with desirable properties have numerous applications in sensing fields, e.g., a monostatic radar transmitting such waveforms can effectively counter the coherent repeater jamming (CRJ). However, due to imperfections in practical systems, the delicately designed sequences may suffer significant distortion and reduction in performance when transmitted as radar waveforms. In this paper, we focus on the problem of designing polyphase sequence sets with good correlation properties under spectral distortion. To address this issue, we first introduce a new metric called distortion correlation properties (DCorr), which quantifies the quality of such sequence sets. Subsequently, a majorization-minimization (MM)-based iterative algorithm is developed to solve the problem of minimizing DCorr. A number of numerical examples are provided to demonstrate the effectiveness of the proposed method in improving the correlation properties of polyphase sequence sets under spectral distortion. The results also validate that our proposed algorithms can effectively mitigate the performance reduction caused by the imperfections in practical radar systems simply.
AB - Orthogonal polyphase sequence sets with desirable properties have numerous applications in sensing fields, e.g., a monostatic radar transmitting such waveforms can effectively counter the coherent repeater jamming (CRJ). However, due to imperfections in practical systems, the delicately designed sequences may suffer significant distortion and reduction in performance when transmitted as radar waveforms. In this paper, we focus on the problem of designing polyphase sequence sets with good correlation properties under spectral distortion. To address this issue, we first introduce a new metric called distortion correlation properties (DCorr), which quantifies the quality of such sequence sets. Subsequently, a majorization-minimization (MM)-based iterative algorithm is developed to solve the problem of minimizing DCorr. A number of numerical examples are provided to demonstrate the effectiveness of the proposed method in improving the correlation properties of polyphase sequence sets under spectral distortion. The results also validate that our proposed algorithms can effectively mitigate the performance reduction caused by the imperfections in practical radar systems simply.
KW - Correlation property
KW - Majorization-minimization framework
KW - Polyphase sequence
KW - Spectral distortion
KW - Waveform design
UR - http://www.scopus.com/inward/record.url?scp=85178375128&partnerID=8YFLogxK
U2 - 10.1016/j.dsp.2023.104284
DO - 10.1016/j.dsp.2023.104284
M3 - Article
AN - SCOPUS:85178375128
SN - 1051-2004
VL - 145
JO - Digital Signal Processing: A Review Journal
JF - Digital Signal Processing: A Review Journal
M1 - 104284
ER -