美军正在创新水下网络中心战、21世纪反潜作战、多域战、马赛克战等海上作战概念,结合“分布式、智能化、无人化”的浪潮,探索触手前伸、节点后置的新型反潜作战模式,利用大量低成本分布式无人机(UAV)、无人船(USV)、无人潜航器(UUV)携带多模传感器构建立体协同的探潜网络;推进大中型无人舰、反潜无人机和超大型无人潜航器等无人反潜作战平台,与水面舰艇、反潜巡逻机、攻击型潜艇等有人作战平台协同作战的反潜作战体系。本文首先从水下监听系统、航空反潜、海上反潜、水下反潜4个方面分析了美军反潜装备体系发展现状,进而从自主式、协同式、集群式3个方面分析了反潜杀伤链发展趋势。建议将网络化、智能化、无人化要素引入反潜作战体系研究,尽早进行技术验证、体系磨合、实战演练,为反潜作战领域追平差距提供牵引。
The US military is innovating underwater network-centric warfare, 21st century anti-submarine warfare, multi-domain warfare, Mosaic warfare and other maritime combat concepts, combined with the wave of "distributed, intelligent, unmanned", exploring new anti-submarine warfare modes with tentacles reaching forward and nodes positioned behind. Using a large number of low-cost distributed unmanned aerial vehicles (UAV), unmanned surface vessels (USV) and unmanned underwater vehicles (UUV) to carry multi-mode sensors, a three-dimensional collaborative submarine exploration network is constructed. It will promote an anti-submarine warfare system in which unmanned anti-submarine combat platforms, such as large and medium-sized unmanned ships, anti-submarine drones, and ultra-large unmanned underwater vehicles, coordinate operations with manned combat platforms, such as surface ships, anti-submarine patrol aircraft, and attack submarines. This paper first analyzes the development status of the US military's anti-submarine equipment system from four aspects: underwater listening system, aviation anti-submarine, maritime anti-submarine and underwater anti-submarine, and then analyzes the development trend of the anti-submarine kill chain from three aspects: autonomous, cooperative and cluster. It is suggested that network, intelligent and unmanned elements should be introduced into the research of anti-submarine warfare system, and technical verification, system running-in and actual combat exercises should be carried out as soon as possible to provide traction for closing the gap in the field of anti-submarine warfare.
2024,46(23): 184-189 收稿日期:2024-1-17
DOI:10.3404/j.issn.1672-7649.2024.23.033
分类号:U674.7
基金项目:JKW国防科技创新特区资助项目(23-TQ02-01-ZT-01-003,23-TQ02-01-ZT-01-004)
作者简介:王兆杰(1985-),男,博士,研究员,研究方向为体系创新
参考文献:
[1] 王鲁军, 王青翠, 王南. 美国水下预警探测体系建设及其启示[J]. 声学与电子工程, 2015(1): 49-52.
WANG L J, WANG Q C, WANG N. Construction of American underwater early warning and detection system and its enlightenment[J]. Acoustics and Electronics Engineering, 2015(1): 49-52.
[2] RICE J A. Seaweb acoustic com/nav networks[J]. DARPA ATO Disruption Tolerant Networking Program, 2005.
[3] STEWART M S, PAVLOS J. A means to networked persistent undersea surveillance[C]//Technology Symposium, 2006.
[4] 孔维玮, 冯伟强, 诸葛文章, 等. 美军大中型水面无人艇发展现状及启示[J]. 指挥控制与仿真, 2022, 44(5): 14-18.
KONG W W, FENG W Q, ZHUGE W Z, et al. Development status and enlightenment of Large and medium-sized surface unmanned craft of US military[J]. Command Control & Simulation, 2022, 44(5): 14-18.
[5] 刘大庆, 赵云飞, 吴超, 等. 美军水下无人作战力量发展趋势及启示[J]. 数字海洋与水下攻防, 2021, 4(4): 257-263.
LIU D Q, ZHAO Y F, WU C, et al. The development trend and enlightenment of US military underwater unmanned combat force[J]. Digital Ocean & Underwater Warfare, 2021, 4(4): 257-263.
[6] 宋保维, 潘光, 张立川, 等. 自主水下航行器发展趋势及关键技术[J]. 中国舰船研究, 2022, 17(5): 27-44.
SONG B W, PAN G, ZHANG L C, et al. Development trend and key technologies of autonomous underwater vehicles[J]. Chinese Journal of Ship Research, 2022, 17(5): 27-44.
[7] 李汉清, 戴修亮. 美国海军正在发展的水下探测系统[J]. 情报指挥控制系统与仿真技术, 2004, 26(4): 37-38,50.
LI H Q, DAI X L. An underwater detection system being developed by the U. S. Navy[J]. Command Control & Simulation, 2004, 26(4): 37-38,50.
[8] 李智生, 张强. 深海预置武器系统发展现状及关键技术[J]. 舰船电子工程, 2020, 40(2): 1-3,41.
LI Z S, ZHANG Q. Development status and key technologies of deep-sea preset weapon system[J]. Ship Electronic Engineering, 2020, 40(2): 1-3,41.
[9] 姚明超, 焦慧锋, 张琳丹, 等. 水下预置式无人装备现状及发展分析 [R]. 西安: 第五届水下无人系统技术高峰论坛, 2022.
[10] 李杰, 尹栋, 喻煌超, 等. 无人化联合战术跨域协同及规划能力发展[J]. 国防科技, 2023, 44(2): 82-89.
LI J, YIN D, YU H C, et al. Development of unmanned joint tactical cross-domain coordination and planning capability[J]. National Defense Technology, 2023, 44(2): 82-89.