第1 章 海上雷達(dá)有源誘餌概況·························································1
1.1 引言·················································································1
1.2 海上雷達(dá)有源誘餌的發(fā)展與應(yīng)用現(xiàn)狀·······································1
1.3 海上雷達(dá)有源誘餌的工作原理················································7
1.3.1 單脈沖雷達(dá)導(dǎo)引頭目標(biāo)位置參數(shù)獲取·······························7
1.3.2 基于數(shù)字射頻存儲的干擾信號轉(zhuǎn)發(fā)技術(shù)·························.10
1.3.3 海上雷達(dá)有源誘餌的角度欺騙干擾模型·························.12
1.4 海上雷達(dá)有源誘餌運用分析與干擾局限性······························.18
1.5 小結(jié)··············································································.21
參考文獻(xiàn)···············································································.21
第2 章 海上雷達(dá)有源誘餌干擾動態(tài)分析··········································.24
2.1 引言··············································································.24
2.2 單個海上雷達(dá)有源誘餌動態(tài)干擾模型····································.24
2.2.1 末制導(dǎo)雷達(dá)目標(biāo)跟蹤的動態(tài)響應(yīng)··································.25
2.2.2 海上雷達(dá)有源誘餌的動態(tài)對抗過程·······························.29
2.2.3 單個海上雷達(dá)有源誘餌的有效干擾臨界條件···················.32
2.3 多個海上雷達(dá)有源誘餌組合欺騙干擾分析······························.33
2.3.1 多個雷達(dá)有源誘餌干擾信號疊加模型····························.34
2.3.2 多個海上雷達(dá)有源誘餌有效干擾臨界條件······················.39
2.3.3 多個海上雷達(dá)有源誘餌空間干擾模型····························.44
2.4 海上雷達(dá)有源誘餌的動態(tài)仿真分析·······································.47
2.4.1 雷達(dá)有源誘餌干擾動態(tài)仿真系統(tǒng)··································.47
2.4.2 雷達(dá)有源誘餌干擾過程仿真分析··································.49

2.5 小結(jié)··············································································.66
參考文獻(xiàn)···············································································.67
第3 章 基于概率推理的海上雷達(dá)有源誘餌干擾有效性評估方法············.68
3.1 引言··············································································.68
3.2 概率推理的基本原理·························································.68
3.2.1 干擾有效性的正向概率推理········································.69
3.2.2 干擾有效性的反向概率推理········································.70
3.3 雷達(dá)有源誘餌欺騙干擾有效性評估方法·································.72
3.3.1 雷達(dá)有源誘餌干擾的非合作要素分析····························.72
3.3.2 雷達(dá)有源誘餌理想態(tài)勢的有效干擾概率·························.74
3.3.3 雷達(dá)有源誘餌空間組合的有效干擾概率·························.77
3.4 干擾有效性評估數(shù)值仿真分析·············································.78
3.4.1 參數(shù)未知條件下的動態(tài)仿真········································.78
3.4.2 基于GeNIe 軟件的有效干擾臨界條件正反向推理············.80
3.4.3 多雷達(dá)有源誘餌干擾有效性評估分析····························.84
3.4.4 雷達(dá)有源誘餌機(jī)動干擾評估分析··································.85
3.5 小結(jié)··············································································.88
參考文獻(xiàn)···············································································.89
第4 章 基于改進(jìn)粒子群優(yōu)化算法的集群干擾陣型優(yōu)化方法··················.90
4.1 引言··············································································.90
4.2 雷達(dá)有源誘餌集群干擾陣型優(yōu)化問題····································.90
4.2.1 集群干擾陣型優(yōu)化問題描述········································.90
4.2.2 集群干擾陣型優(yōu)化數(shù)學(xué)模型········································.94
4.3 基于多策略改進(jìn)的粒子群優(yōu)化算法·······································.96
4.3.1 標(biāo)準(zhǔn)粒子群優(yōu)化算法·················································.96
4.3.2 算法改進(jìn)策略··························································.97
4.3.3 集群干擾陣型尋優(yōu)實現(xiàn)··············································100
4.4 集群干擾陣型優(yōu)化仿真及結(jié)果分析·······································103
4.4.1 單個雷達(dá)有源誘餌干擾陣型優(yōu)化··································103
4.4.2 多個雷達(dá)有源誘餌集群干擾陣型優(yōu)化····························107
4.5 小結(jié)·············································································.116
參考文獻(xiàn)··············································································.116
第5 章 基于改進(jìn)差分進(jìn)化算法的集群干擾目標(biāo)分配方法·····················117
5.1 引言·············································································.117
5.2 雷達(dá)有源誘餌集群干擾目標(biāo)分配問題···································.117
5.2.1 集群干擾目標(biāo)分配問題描述·······································.117
5.2.2 集群干擾目標(biāo)分配數(shù)學(xué)模型·······································.119
5.3 基于任務(wù)組合的改進(jìn)差分進(jìn)化算法·······································121
5.3.1 雷達(dá)有源誘餌干擾任務(wù)組合策略··································122
5.3.2 改進(jìn)差分進(jìn)化算法····················································124
5.3.3 集群干擾目標(biāo)分配仿真及結(jié)果分析·······························128
5.4 融合陣型優(yōu)化與目標(biāo)分配的集群梯次動態(tài)對抗策略··················135
5.4.1 誘餌集群多波次干擾需求分析·····································135
5.4.2 誘餌集群多波次對抗決策流程設(shè)計·······························136
5.4.3 誘餌集群多波次對抗仿真案例分析·······························138
5.5 小結(jié)··············································································142
參考文獻(xiàn)···············································································142
第6 章 基于深度強(qiáng)化學(xué)習(xí)的雷達(dá)有源誘餌自主干擾方法···················.144
6.1 引言··············································································144
6.2 雷達(dá)有源誘餌自主干擾問題描述與建模·································145
6.2.1 雷達(dá)有源誘餌自主干擾問題描述··································145
6.2.2 雷達(dá)有源誘餌自主干擾強(qiáng)化學(xué)習(xí)方法····························147
6.2.3 雷達(dá)有源誘餌自主干擾MDP 模型設(shè)計··························150
6.3 基于PPO 算法的自主對抗訓(xùn)練方法研究································154
6.3.1 雷達(dá)有源誘餌自主干擾決策神經(jīng)網(wǎng)絡(luò)····························154
6.3.2 完全去中心化異步遞進(jìn)訓(xùn)練結(jié)構(gòu)設(shè)計····························155
6.3.3 基于截斷形式近端策略優(yōu)化算法實現(xiàn)····························158
6.4 雷達(dá)有源誘餌自主干擾仿真與試驗分析·································159
6.4.1 仿真訓(xùn)練環(huán)境構(gòu)建與參數(shù)設(shè)置·····································160
6.4.2 雷達(dá)有源誘餌獨立場景訓(xùn)練分析··································161
6.4.3 雷達(dá)有源誘餌遞進(jìn)結(jié)構(gòu)訓(xùn)練分析··································168
6.5 本章小結(jié)········································································171
參考文獻(xiàn)···············································································171