TY - GEN
T1 - Phase Coded Waveform Set Design for MIMO Radar Using SPS-JADE
AU - Liu, Tianqu
AU - Zhang, Hongbo
AU - Chen, Fanyun
AU - Sun, Jinping
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Phase coded waveform set is one of the most extensively studied MIMO radar waveform sets with good application prospects. The goal of the MIMO radar waveform set design is making the peak cross-correlation function ratio (PCCR) and peak auto-correlation function side-lobe ratio (PASR) as low as possible. Existing phase coded waveform set design algorithms include the following two categories, one is cyclic iteration algorithms, and the other is intelligent optimization algorithms. Because of the insufficient mathematical properties of the correlation functions, the performances of the cyclic iterative algorithms have hit a bottleneck. With the development of computing power, the intelligent optimization algorithms are capable of obtaining good results within a short time at the cost of more computing resources. This paper establishes an optimization model of the MIMO radar phase coding waveform set design problem. Then an improved differential evolution algorithm based on successful parent selection framework (SPS-JADE) is used to solve this optimization problem. For some parameters, numerical results show that the values of the PCCR and PASR metrics obtained by SPS-JADE are 3.21 dB and 1.92 dB lower than those obtained by Multi-CAN algorithm on average, respectively. Furthermore, the convergence speed of SPS-JADE is much higher than that of GA algorithm.
AB - Phase coded waveform set is one of the most extensively studied MIMO radar waveform sets with good application prospects. The goal of the MIMO radar waveform set design is making the peak cross-correlation function ratio (PCCR) and peak auto-correlation function side-lobe ratio (PASR) as low as possible. Existing phase coded waveform set design algorithms include the following two categories, one is cyclic iteration algorithms, and the other is intelligent optimization algorithms. Because of the insufficient mathematical properties of the correlation functions, the performances of the cyclic iterative algorithms have hit a bottleneck. With the development of computing power, the intelligent optimization algorithms are capable of obtaining good results within a short time at the cost of more computing resources. This paper establishes an optimization model of the MIMO radar phase coding waveform set design problem. Then an improved differential evolution algorithm based on successful parent selection framework (SPS-JADE) is used to solve this optimization problem. For some parameters, numerical results show that the values of the PCCR and PASR metrics obtained by SPS-JADE are 3.21 dB and 1.92 dB lower than those obtained by Multi-CAN algorithm on average, respectively. Furthermore, the convergence speed of SPS-JADE is much higher than that of GA algorithm.
KW - auto-correlation function side-lobe peak
KW - cross-correlation function peak
KW - differential evolution
KW - MIMO radar
KW - phase coded waveform set
UR - https://www.scopus.com/pages/publications/85146247024
U2 - 10.1109/CISP-BMEI56279.2022.9980077
DO - 10.1109/CISP-BMEI56279.2022.9980077
M3 - 会议稿件
AN - SCOPUS:85146247024
T3 - Proceedings - 2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2022
BT - Proceedings - 2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2022
A2 - Chen, Xin
A2 - Cao, Lin
A2 - Li, Qingli
A2 - Wang, Yan
A2 - Wang, Lipo
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2022
Y2 - 5 November 2022 through 7 November 2022
ER -