TY - GEN
T1 - Cognitive Radar Waveform Design Based on Multi-objective Optimization Criteria
AU - Wu, Fei
AU - Fu, Xiongjun
AU - Lang, Ping
AU - Dong, Jian
AU - Cui, Zongding
AU - Gao, Xuanyi
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In electronic warfare, the target is usually in a complex jamming environment. Cognitive waveform design is very important as an active and intelligent anti-jamming method. It is usually performed in the frequency domain and based on a single criterion, which is difficult to take into account the detection and anti-jamming performance and the operation is complex. Aiming at above problems, in the case of corner reflector jamming, a cognitive waveform design method based on multi-objective optimization criteria is proposed. We construct a multi-objective optimization model based on the maximum signal-to-jamming ratio (SJR), the minimum time delay resolution constant (TRC) and the minimum peak sidelobe ratio (PSLR). Then, it is converted into a single-objective function by the weighting method and solved by the particle swarm optimization (PSO) algorithm. The simulation results show that the method improves the signal-to-jamming ratio and range resolution of radar echoes and effectively enhances the ability of target detection and anti-jamming.
AB - In electronic warfare, the target is usually in a complex jamming environment. Cognitive waveform design is very important as an active and intelligent anti-jamming method. It is usually performed in the frequency domain and based on a single criterion, which is difficult to take into account the detection and anti-jamming performance and the operation is complex. Aiming at above problems, in the case of corner reflector jamming, a cognitive waveform design method based on multi-objective optimization criteria is proposed. We construct a multi-objective optimization model based on the maximum signal-to-jamming ratio (SJR), the minimum time delay resolution constant (TRC) and the minimum peak sidelobe ratio (PSLR). Then, it is converted into a single-objective function by the weighting method and solved by the particle swarm optimization (PSO) algorithm. The simulation results show that the method improves the signal-to-jamming ratio and range resolution of radar echoes and effectively enhances the ability of target detection and anti-jamming.
KW - cognitive radar
KW - corner reflector
KW - multi-objective optimization
KW - particle swarm algorithm
KW - waveform design
UR - http://www.scopus.com/inward/record.url?scp=85139424143&partnerID=8YFLogxK
U2 - 10.1109/ICSIP55141.2022.9886146
DO - 10.1109/ICSIP55141.2022.9886146
M3 - Conference contribution
AN - SCOPUS:85139424143
T3 - 2022 7th International Conference on Signal and Image Processing, ICSIP 2022
SP - 172
EP - 176
BT - 2022 7th International Conference on Signal and Image Processing, ICSIP 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Signal and Image Processing, ICSIP 2022
Y2 - 20 July 2022 through 22 July 2022
ER -