1 |
MARTINO A D . Introduction to modern EW systems[M]. Boston: Artech house, 2012.
|
2 |
司建伟, 曲志星, 赵忠凯, 等. 现代电子对抗导论[M]. 北京: 北京航空航天大学出版社, 2016.
|
|
SI J W , QU Z X , ZHAO Z K , et al. Introduction to modern electronic countermeasures[M]. Beijing: Beihang University Press, 2016.
|
3 |
崔炳福. 雷达对抗干扰有效性评估[M]. 北京: 电子工业出版社, 2017.
|
|
CUI B F . Methods effectiveness evaluation of radar counter-measure jamming[M]. Beijing: Publishing House of Electronics Industry, 2017.
|
4 |
陈静. 雷达箔条干扰原理[M]. 北京: 国防工业出版社, 2017.
|
|
CHEN J . Principles of radar chaff jamming[M]. Beijing: National Defence Industry Press, 2017.
|
5 |
刘业民. 箔条云极化雷达特性及抗干扰技术研究[D]. 国防科技大学, 2019.
|
|
LIU Y M. Study on polarization radar characteristics of chaff clouds and anti-jamming techniques[D]. Changsha: National University of Defense Technology, 2019.
|
6 |
TANG B , LI H M , SHENG X Q . Jamming recognition method based on the full polarisation scattering matrix of chaff clouds[J]. IET Microwaves Antennas & Propagation, 2012, 6 (13): 1451- 1460.
|
7 |
蔡万勇, 李侠, 万山虎, 等. 大气环境下箔条运动轨迹及箔条幕扩散模型[J]. 系统工程与电子技术, 2009, 31 (3): 565- 569.
doi: 10.3321/j.issn:1001-506X.2009.03.020
|
|
CAl W Y , LI X , WAN S H , et al. Model of chaff motion trajectory and curtain wall diffusion in air environment[J]. Systems Engineering and Electronics, 2009, 31 (3): 565- 569.
doi: 10.3321/j.issn:1001-506X.2009.03.020
|
8 |
高东华, 田万顷, 徐庆丰. 箔条幕防御反舰导弹的原理论证与作战仿真研究[J]. 兵工学报, 2005, 26 (3): 418- 422.
doi: 10.3321/j.issn:1000-1093.2005.03.031
|
|
GAO D H , TIAN W Q , XU Q F . Study on principle demonstration and fighting simulation of jamming anti-ship missile by chaff screen[J]. Acta Armamentarii, 2005, 26 (3): 418- 422.
doi: 10.3321/j.issn:1000-1093.2005.03.031
|
9 |
白爽, 姜宁. 舰艇箔条幕干扰使用与布放研究[J]. 舰船电子对抗, 2017, 40 (5): 18- 23.
|
|
BAI S , JIANG N . Research into the usage and arrangement of ship chaff-screen jamming[J]. Shipboard Electronic Countermeasure, 2017, 40 (5): 18- 23.
|
10 |
KARASAKAL O , OZDEMIREL N E , KANDILLE L . Anti-ship missile defense for a naval task group[J]. Naval Research Logistics, 2011, 58 (3): 304- 321.
doi: 10.1002/nav.20457
|
11 |
BRIGHTON C H , CHAPMAN K E , FOX N C , et al. Attack behaviour in nave Gyrfalcons is modelled by the same guidance law as in Peregrines, but at a lower guidance gain[J]. Journal of Experimental Biology, 2021, 224 (5): jeb238493.
doi: 10.1242/jeb.238493
|
12 |
GIRARD A R , KABAMBA P T . Proportional navigation: optimal homing and optimal evasion[J]. Siam Review, 2015, 57 (4): 611- 624.
doi: 10.1137/130947301
|
13 |
王晴昊, 姚登凯, 赵顾颢. 一种远距离复合干扰效能及战术应用研究[J]. 火力与指挥控制, 2019, 44 (11): 20-23, 28.
|
|
WANG Q H , YAO D K , ZHAO G H . Research on efficiency and tactics of a stand-off compound jamming[J]. Fire Control & Command Control, 2019, 44 (11): 20-23, 28.
|
14 |
王晴昊, 姚登凯, 胡剑波, 等. 远距离支援最优干扰空域规划[J]. 系统工程与电子技术, 2019, 41 (4): 835- 842.
|
|
WANG Q H , YAO D K , HU J B , et al. Optimal airspace planning for sand-off jamming[J]. Systems Engineering and Electronics, 2019, 41 (4): 835- 842.
|
15 |
GALLANT J , VANCAEYZEELE T , LAUWENS B , et al. Design considerations for an electromagnetic railgun firing intelligent bursts to be used against anti-ship missiles[J]. IEEE Trans. on Plasma Science, 2015, 43 (5): 1179- 1184.
doi: 10.1109/TPS.2015.2416774
|
16 |
JEON I S , LEE J I , TANK M J . Impact-time-control guidance law for anti-ship missiles[J]. IEEE Trans. on Control Systems Technology, 2006, 14 (2): 260- 266.
doi: 10.1109/TCST.2005.863655
|
17 |
MIRJALILI S , MIRJALILI SM , LEWIS A . Grey wolf optimizer[J]. Advance in Engineering Software, 2014, 69 (3): 46- 61.
|
18 |
ZHAO X H , LYU H F , LYU S J , et al. Enhancing robustness of monthly streamflow forecasting model using gated recurrent unit based on improved grey wolf optimizer[J]. Journal of Hydrology, 2021, 601, 1- 11.
|
19 |
RAMADAN A E , KAMEL S , KHURSHAID L T , et al. Parameter extraction of three diode solar photovoltaic model using improved grey wolf optimizer[J]. Sustainability, 2021, 13 (12): 1- 16.
|
20 |
VASHISTH D , SRIVASTAVA S , SHEKAR B . Joint inversion of Rayleigh wave fundamental and higher order mode phase velocity dispersion curves using multi-objective grey wolf optimization[J]. Geophysical Prospecting, 2022, 70 (3): 479- 501.
doi: 10.1111/1365-2478.13176
|
21 |
MOKHTARI A , GVRBVZBALABAN M , RIBEIRO A . Surpassing gradient descent provably: a cyclic incremental method with linear convergence rate[J]. SIAM Journal on Optimization, 2016, 28 (2): 1- 26.
|
22 |
SHAIKH M S , HUA C , JATOI M A , et al. Application of grey wolf optimization algorithm in parameter calculation of overhead transmission line system[J]. IET Science, Measurement & Technology, 2021, 15 (2): 218- 231.
|
23 |
蔡丹, 季晓勇, 史贺, 等. 改进分段Logistic混沌映射的方法及其性能分析[J]. 南京大学学报(自然科学版), 2016, 52 (5): 809- 815.
|
|
CAI D , JI X Y , SHI H , et al. Method for improving piecewise logistic chaotic map and its performance analysis[J]. Journal of Nanjing University(Natural Sciences), 2016, 52 (5): 809- 815.
|
24 |
周凌云, 丁立新, 彭虎, 等. 一种邻域重心反向学习的粒子群优化算法[J]. 电子学报, 2017, 45 (11): 2815- 2824.
doi: 10.3969/j.issn.0372-2112.2017.11.032
|
|
ZHOU L Y , DING L X , PENG H , et al. Neighborhood cent- roid opposition-based particle swarm optimization[J]. Acta Electronica Sinica, 2017, 45 (11): 2815- 2824.
doi: 10.3969/j.issn.0372-2112.2017.11.032
|
25 |
AHANDANI M A , ALAVI-RAD H . Opposition-based learning in shuffled frog leaping: an application for parameter identification[J]. Information Sciences, 2015, 291, 19- 42.
doi: 10.1016/j.ins.2014.08.031
|
26 |
SONI N , SAINI I , SINGH B . AFD and chaotic map-based integrated approach for ECG compression, steganography and encryption in E-healthcare paradigm[J]. IET Signal Processing, 2021, 15 (5): 337- 351.
doi: 10.1049/sil2.12031
|
27 |
ZDEMIR M T . Optimal parameter estimation of polymer electrolyte membrane fuel cells model with chaos embedded particle swarm optimization[J]. International Journal of Hydrogen Energy, 2021, 46 (30): 16465- 16480.
|
28 |
MIRJALILI S . SCA: a sine cosine algorithm for solving optimization problems[J]. Knowledge-Based Systems, 2016, 96 (15): 120- 133.
|
29 |
CUI F , AL-SUDANI Z A , HASSAN G S , et al. Boosted artificial intelligence model using improved alpha-guided grey wolf optimizer for groundwater level prediction: comparative study and insight for federated learning technology[J]. Journal of Hydrology, 2022, (606): 127384.
|
30 |
FRIZZO S S , SCHUTEL F , SPINDOLA C T , et al. Particle swarm optimization for design of insulators of distribution power system based on finite element method[J]. Electrical Engineering, 2022, 104 (2): 615- 622.
|
31 |
SHARMA P , DINKAR S K . A linearly adaptive sine-cosine algorithm with application in deep neural network for feature optimization in arrhythmia classification using ECG signals[J]. Knowledge-Based Systems, 2022, 242 (22): 108411.
|