Article(id=1149769462359966675, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149769458706723113, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2408775, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732377600000, receivedDateStr=2024-11-24, revisedDate=1745337600000, revisedDateStr=2025-04-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1752056001510, onlineDateStr=2025-07-09, pubDate=1747497600000, pubDateStr=2025-05-18, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752056001510, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752056001510, creator=13701087609, updateTime=1752056001510, updator=13701087609, issue=Issue{id=1149769458706723113, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='14', pageStart='5705', pageEnd='6154', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752056000638, creator=13701087609, updateTime=1768456798957, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1218559392753041779, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149769458706723113, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1218559392753041780, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149769458706723113, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=6109, endPage=6117, ext={EN=ArticleExt(id=1149769462754231256, articleId=1149769462359966675, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=A Multi-Attribute Evaluation Method for Low-Altitude Security System Solutions Based on DEMATEL and TOPSIS, columnId=1156262731079607234, journalTitle=Science Technology and Engineering, columnName=Papers·Aeronautics and Astronautics, runingTitle=null, highlight=null, articleAbstract=

In order to address a series of safety management issues involved in low-altitude economic development, the technical routes and principles of low-altitude economy as well as the operational experience of implementation plans are summarized, and four universal construction plans for low-altitude security and protection are analyzed, namely the radar and integrated perception technology fusion plan, the broadcast automatic dependent surveillance technology plan, the remote identification technology plan, and the multi-source fusion plan based on TDOA radio technology. On this basis, an evaluation index system for unmanned aerial vehicle detection technology was constructed, and a multi-attribute evaluation method based on DEMATEL and TOPSIS was established. The results show that the multi-source fusion plan based on time difference of arrival (TDOA) is an effective and universal solution for building a low-altitude security system in cities. It is concluded that the construction of a low-altitude security system is a systematic project, which requires the joint efforts of governments, enterprises and the whole society. Integration is needed at the levels of technology, data and operation to meet the future development needs of the low-altitude economy.

, correspAuthors=Jian WU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Wei SHI, Jian WU), CN=ArticleExt(id=1149769466847871983, articleId=1149769462359966675, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=基于DEMATEL和TOPSIS的低空安防系统方案多属性评价方法, columnId=1156262731373208516, journalTitle=科学技术与工程, columnName=论文·航空、航天, runingTitle=null, highlight=null, articleAbstract=

针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference of arrival )无线电技术的多源融合方案的基础上,构建无人飞行器探测技术评价指标体系,并建立了一种基于决策试验评估实验室(decision-making trial and evaluation laboratory,DEMATEL)和优劣解距离法(technique for order preference by similarity to an ideal solution,TOPSIS)的多属性评价方法。结果发现,以TDOA为基础的多源融合方案是构建城市低空安防体系的有效路径和普适性方案。研究表明,低空安防体系的建设是一个系统性工程,需要政府、企业和社会各方的共同努力,在技术、数据、运营等多个层面进行整合,以适应未来低空经济的发展需求。

, correspAuthors=吴坚, authorNote=null, correspAuthorsNote=
*吴坚(1977—),男,汉族,江苏无锡人,博士,教授。研究方向:群体决策 社会网络。E-mail:
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施玮(1988—),男,汉族,浙江金华人,硕士。研究方向:数字经济 低空经济。E-mail:

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施玮(1988—),男,汉族,浙江金华人,硕士。研究方向:数字经济 低空经济。E-mail:

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Berlin: Springer, 1981., articleTitle=null, refAbstract=null), Reference(id=1172983788599652805, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, doi=null, pmid=null, pmcid=null, year=2025, volume=25, issue=8, pageStart=3487, pageEnd=3496, url=null, language=null, rfNumber=[25], rfOrder=45, authorNames=张建, 严松宏, 曾志刚, journalName=科学技术与工程, refType=null, unstructuredReference=张建, 严松宏, 曾志刚, 等. 利用综合优选模型分析山区高速公路选线影响因素及效果[J]. 科学技术与工程, 2025, 25(8): 3487-3496., articleTitle=利用综合优选模型分析山区高速公路选线影响因素及效果, refAbstract=null), Reference(id=1172983788696121798, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, doi=null, pmid=null, pmcid=null, year=2025, volume=25, issue=8, pageStart=3487, pageEnd=3496, url=null, language=null, rfNumber=[25], rfOrder=46, authorNames=Zhang Jian, Yan Songhong, Zeng Zhigang, journalName=Science Technology and Engineering, refType=null, unstructuredReference=Zhang Jian, Yan Songhong, Zeng Zhigang, et al. Analysis of influencing factors and effects of mountain highway alignment selection using a comprehensive optimization model[J]. Science Technology and Engineering, 2025, 25(8): 3487-3496., articleTitle=Analysis of influencing factors and effects of mountain highway alignment selection using a comprehensive optimization model, refAbstract=null), Reference(id=1172983788754842055, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, doi=null, pmid=null, pmcid=null, year=2024, volume=24, issue=32, pageStart=14086, pageEnd=14093, url=null, language=null, rfNumber=[26], rfOrder=47, authorNames=卢敏, 李晓萍, 胡青蜜, journalName=科学技术与工程, refType=null, unstructuredReference=卢敏, 李晓萍, 胡青蜜. 基于组合赋权-TOPSIS法的受灾点救援需求紧迫度研究[J]. 科学技术与工程, 2024, 24(32): 14086-14093., articleTitle=基于组合赋权-TOPSIS法的受灾点救援需求紧迫度研究, refAbstract=null), Reference(id=1172983788817756616, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, doi=null, pmid=null, pmcid=null, year=2024, volume=24, issue=32, pageStart=14086, pageEnd=14093, url=null, language=null, rfNumber=[26], rfOrder=48, authorNames=Lu Min, Li Xiaoping, Hu Qingmi, journalName=Science Technology and Engineering, refType=null, unstructuredReference=Lu Min, Li Xiaoping, Hu Qingmi. Study on the urgency of rescue needs at disaster sites based on the combined weighting-TOPSIS method[J]. Science Technology and Engineering, 2024, 24(32): 14086-14093., articleTitle=Study on the urgency of rescue needs at disaster sites based on the combined weighting-TOPSIS method, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1172983780559171948, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, xref=null, ext=[AuthorCompanyExt(id=1172983780567560557, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, companyId=1172983780559171948, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. Zhejiang Zheshang Huirong Private Equity Fund Management Co., Ltd., Hangzhou 310000, China), AuthorCompanyExt(id=1172983780575949166, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, companyId=1172983780559171948, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. 浙江浙商汇融私募基金管理有限公司, 杭州 310000)]), AuthorCompany(id=1172983780638863727, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, xref=null, ext=[AuthorCompanyExt(id=1172983780647252336, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, companyId=1172983780638863727, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China), AuthorCompanyExt(id=1172983780651446641, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, companyId=1172983780638863727, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. 上海海事大学经济管理学院, 上海 201306)])], figs=[ArticleFig(id=1172983782094287238, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=EN, label=Fig.1, caption=Evaluation indicators for unmanned aerial vehicle detection technology, figureFileSmall=faCbVc+jaPA6innx3AW5Aw==, figureFileBig=Y2sjG6eXXix9MFqgTtqnxg==, tableContent=null), ArticleFig(id=1172983782144618887, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=CN, label=图1, caption=无人飞行器探测技术评价指标体系, figureFileSmall=faCbVc+jaPA6innx3AW5Aw==, figureFileBig=Y2sjG6eXXix9MFqgTtqnxg==, tableContent=null), ArticleFig(id=1172983782211727752, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=EN, label=Table 1, caption=

Comparison of the environment between traditional civil aviation and low-altitude economy

, figureFileSmall=null, figureFileBig=null, tableContent=
特征 传统民航 低空经济
异构性 民航飞机由少数公司提供,种类较少 不同种类、功能、性能飞行器
高密度 国内全空域约6 000架 中心城市飞行器远期可达百万级
高频次 中心城市主要机场每日起降千次级别 中心城市远期每日起降可达百万次级
高复杂性 多数民航飞机在6 000 m以上飞行,该空域属于平流层,恶劣天气较少 复杂的飞行、地面和信息环境。对流层恶劣天气频繁。城市区域电磁环境复杂,障碍物较多
), ArticleFig(id=1172983782266253705, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=CN, label=表1, caption=

传统民航与低空经济的环境对比

, figureFileSmall=null, figureFileBig=null, tableContent=
特征 传统民航 低空经济
异构性 民航飞机由少数公司提供,种类较少 不同种类、功能、性能飞行器
高密度 国内全空域约6 000架 中心城市飞行器远期可达百万级
高频次 中心城市主要机场每日起降千次级别 中心城市远期每日起降可达百万次级
高复杂性 多数民航飞机在6 000 m以上飞行,该空域属于平流层,恶劣天气较少 复杂的飞行、地面和信息环境。对流层恶劣天气频繁。城市区域电磁环境复杂,障碍物较多
), ArticleFig(id=1172983782312391050, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=EN, label=Table 2, caption=

Principles and application characteristics of radar and integrated sensing and communication technology

, figureFileSmall=null, figureFileBig=null, tableContent=
一次雷达 二次雷达 通感一体
原理 无线电波反射 通过地面站进行询问,机载应答机收到信号后进行应答,通过测量反射波束确定目标位置 兼具一次雷达(感知)及二次雷达(通信)工作特点
优点 ①对于高速、大型飞行器的检测效果优良;
②检测精度较高
①发射功率小;
②干扰杂波少;
③不存在目标闪烁的问题
①发射功率较低;
②对中速飞行器的跟踪精度高;
③无需新增建设用地
缺点 ①无法识别被监视目标的身份信息;
②发射功率大,对周边生产生活产生负面影响;
③造价成本高
需要被监视飞行器装配应答机 ①可检测距离短,目前组网水平距离最大约为1 200 m,高度大约在500 m左右, 而低空经济的规划高度达到3 km;
②射频自干扰问题;
③无法定位飞手位置,效率低;
④结构设计问题;
⑤无法精准实现个体识别
), ArticleFig(id=1172983782379499915, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=CN, label=表2, caption=

雷达与通感一体技术及应用特征

, figureFileSmall=null, figureFileBig=null, tableContent=
一次雷达 二次雷达 通感一体
原理 无线电波反射 通过地面站进行询问,机载应答机收到信号后进行应答,通过测量反射波束确定目标位置 兼具一次雷达(感知)及二次雷达(通信)工作特点
优点 ①对于高速、大型飞行器的检测效果优良;
②检测精度较高
①发射功率小;
②干扰杂波少;
③不存在目标闪烁的问题
①发射功率较低;
②对中速飞行器的跟踪精度高;
③无需新增建设用地
缺点 ①无法识别被监视目标的身份信息;
②发射功率大,对周边生产生活产生负面影响;
③造价成本高
需要被监视飞行器装配应答机 ①可检测距离短,目前组网水平距离最大约为1 200 m,高度大约在500 m左右, 而低空经济的规划高度达到3 km;
②射频自干扰问题;
③无法定位飞手位置,效率低;
④结构设计问题;
⑤无法精准实现个体识别
), ArticleFig(id=1172983782480163212, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=EN, label=Table 3, caption=

Classification and application features of radio detection technology

, figureFileSmall=null, figureFileBig=null, tableContent=
特征 AOA CRPC TDOA
原理 接收电磁波,角度测向 逆向解码,破解协议 接收电磁波,双曲线定位
优点 ①探测距离远;
②技术实现简单;
③能应用于便携式设备
①够破解一定程度的协议;
②对实现协议破解的无人机跟踪能力强
①探测高度范围更广,通过天线设计能有效探测1 000~3 000 m空域;
②能同步探测无人机及飞手,执法效率高;
③拓展性强,可以从无人机探测扩大至各类智能装备探测领域;
④和其他检测设备,如光电,雷达,声音检测协同性好,能大幅提升检测准确率
缺点 ①测向精度不足,无法提供三维坐标;
②引导多源检测能力较弱
①对未知或非标协议的无人机无法探测,不普遍适用;
②如无人机生产厂商修改协议,需重新破解,故而存在检测空窗期
①布设点的间距不宜过短,对于特定小区域的布设存在方案短板;
②对穿越机等高速无人机,现阶段漏报率相对较高,需要不断更新数据库及识别算法
), ArticleFig(id=1172983782605992333, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=CN, label=表3, caption=

无线电探测技术分类及应用特征

, figureFileSmall=null, figureFileBig=null, tableContent=
特征 AOA CRPC TDOA
原理 接收电磁波,角度测向 逆向解码,破解协议 接收电磁波,双曲线定位
优点 ①探测距离远;
②技术实现简单;
③能应用于便携式设备
①够破解一定程度的协议;
②对实现协议破解的无人机跟踪能力强
①探测高度范围更广,通过天线设计能有效探测1 000~3 000 m空域;
②能同步探测无人机及飞手,执法效率高;
③拓展性强,可以从无人机探测扩大至各类智能装备探测领域;
④和其他检测设备,如光电,雷达,声音检测协同性好,能大幅提升检测准确率
缺点 ①测向精度不足,无法提供三维坐标;
②引导多源检测能力较弱
①对未知或非标协议的无人机无法探测,不普遍适用;
②如无人机生产厂商修改协议,需重新破解,故而存在检测空窗期
①布设点的间距不宜过短,对于特定小区域的布设存在方案短板;
②对穿越机等高速无人机,现阶段漏报率相对较高,需要不断更新数据库及识别算法
), ArticleFig(id=1172983782702461326, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=EN, label=Table 5, caption=

Direct influence matrix A

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 C1 C2 C3 C4 C5 C6 C7 C8
C1 0.00 2.00 2.00 2.00 1.33 2.00 1.00 2.00
C2 2.33 0.00 2.00 2.00 1.00 2.00 1.00 2.00
C3 2.00 2.00 0.00 3.00 2.00 1.00 2.00 2.00
C4 2.00 2.33 3.00 0.00 2.00 1.00 1.00 2.00
C5 1.00 1.00 2.00 2.00 0.00 1.00 2.00 1.00
C6 2.33 2.33 1.33 1.33 1.33 0.00 2.33 2.00
C7 1.33 1.33 2.00 1.00 2.00 2.67 0.00 1.00
C8 2.00 2.00 2.00 2.00 1.00 2.33 1.00 0.00
), ArticleFig(id=1172983782824096143, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=CN, label=表5, caption=

直接影响力矩阵A

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 C1 C2 C3 C4 C5 C6 C7 C8
C1 0.00 2.00 2.00 2.00 1.33 2.00 1.00 2.00
C2 2.33 0.00 2.00 2.00 1.00 2.00 1.00 2.00
C3 2.00 2.00 0.00 3.00 2.00 1.00 2.00 2.00
C4 2.00 2.33 3.00 0.00 2.00 1.00 1.00 2.00
C5 1.00 1.00 2.00 2.00 0.00 1.00 2.00 1.00
C6 2.33 2.33 1.33 1.33 1.33 0.00 2.33 2.00
C7 1.33 1.33 2.00 1.00 2.00 2.67 0.00 1.00
C8 2.00 2.00 2.00 2.00 1.00 2.33 1.00 0.00
), ArticleFig(id=1172983782933148048, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=EN, label=Table 6, caption=

Evaluation matrix X of technical solutions

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 C1 C2 C3 C4 C5 C6 C7 C8
D1 0.78 0.72 0.75 0.70 0.78 0.80 0.65 0.75
D2 0.67 0.80 0.83 0.79 0.83 0.63 0.70 0.80
D3 0.72 0.73 0.88 0.73 0.88 0.58 0.80 0.83
D4 0.78 0.73 0.80 0.75 0.77 0.78 0.72 0.78
D5 0.83 0.82 0.80 0.82 0.82 0.88 0.72 0.82
), ArticleFig(id=1172983783079948689, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=CN, label=表6, caption=

技术方案评价矩阵X

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 C1 C2 C3 C4 C5 C6 C7 C8
D1 0.78 0.72 0.75 0.70 0.78 0.80 0.65 0.75
D2 0.67 0.80 0.83 0.79 0.83 0.63 0.70 0.80
D3 0.72 0.73 0.88 0.73 0.88 0.58 0.80 0.83
D4 0.78 0.73 0.80 0.75 0.77 0.78 0.72 0.78
D5 0.83 0.82 0.80 0.82 0.82 0.88 0.72 0.82
), ArticleFig(id=1172983783155446162, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=EN, label=Table 7, caption=

Normalized direct influence matrix B

, figureFileSmall=null, figureFileBig=null, tableContent=
元数 C1 C2 C3 C4 C5 C6 C7 C8
C1 0.00 0.14 0.14 0.14 0.09 0.14 0.07 0.14
C2 0.16 0.00 0.14 0.14 0.07 0.14 0.07 0.14
C3 0.14 0.14 0.00 0.21 0.14 0.07 0.14 0.14
C4 0.14 0.16 0.21 0.00 0.14 0.07 0.07 0.14
C5 0.07 0.07 0.14 0.14 0.00 0.07 0.14 0.07
C6 0.16 0.16 0.09 0.09 0.09 0.00 0.16 0.14
C7 0.09 0.09 0.14 0.07 0.14 0.19 0.00 0.07
C8 0.14 0.14 0.14 0.14 0.07 0.16 0.07 0.00
), ArticleFig(id=1172983783235137939, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=CN, label=表7, caption=

归一化的直接影响力矩阵B

, figureFileSmall=null, figureFileBig=null, tableContent=
元数 C1 C2 C3 C4 C5 C6 C7 C8
C1 0.00 0.14 0.14 0.14 0.09 0.14 0.07 0.14
C2 0.16 0.00 0.14 0.14 0.07 0.14 0.07 0.14
C3 0.14 0.14 0.00 0.21 0.14 0.07 0.14 0.14
C4 0.14 0.16 0.21 0.00 0.14 0.07 0.07 0.14
C5 0.07 0.07 0.14 0.14 0.00 0.07 0.14 0.07
C6 0.16 0.16 0.09 0.09 0.09 0.00 0.16 0.14
C7 0.09 0.09 0.14 0.07 0.14 0.19 0.00 0.07
C8 0.14 0.14 0.14 0.14 0.07 0.16 0.07 0.00
), ArticleFig(id=1172983783327412628, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=EN, label=Table 8, caption=

Comprehensive influence matrix P

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 C1 C2 C3 C4 C5 C6 C7 C8
C1 0.75 0.87 0.93 0.90 0.70 0.80 0.66 0.83
C2 0.89 0.75 0.93 0.90 0.68 0.80 0.66 0.83
C3 0.95 0.95 0.91 1.04 0.81 0.82 0.78 0.90
C4 0.92 0.93 1.05 0.83 0.78 0.79 0.70 0.88
C5 0.68 0.68 0.79 0.76 0.51 0.62 0.61 0.64
C6 0.90 0.89 0.90 0.86 0.71 0.70 0.74 0.84
C7 0.76 0.76 0.86 0.77 0.69 0.78 0.55 0.71
C8 0.88 0.87 0.94 0.90 0.68 0.82 0.66 0.71
), ArticleFig(id=1172983783407104405, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149769462359966675, language=CN, label=表8, caption=

综合影响力矩阵P

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 C1 C2 C3 C4 C5 C6 C7 C8
C1 0.75 0.87 0.93 0.90 0.70 0.80 0.66 0.83
C2 0.89 0.75 0.93 0.90 0.68 0.80 0.66 0.83
C3 0.95 0.95 0.91 1.04 0.81 0.82 0.78 0.90
C4 0.92 0.93 1.05 0.83 0.78 0.79 0.70 0.88
C5 0.68 0.68 0.79 0.76 0.51 0.62 0.61 0.64
C6 0.90 0.89 0.90 0.86 0.71 0.70 0.74 0.84
C7 0.76 0.76 0.86 0.77 0.69 0.78 0.55 0.71
C8 0.88 0.87 0.94 0.90 0.68 0.82 0.66 0.71
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Indicators’ centralities, causalities and weights

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参数 C1 C2 C3 C4 C5 C6 C7 C8
φ i 13.15 13.15 14.46 13.81 10.86 12.66 11.24 12.80
ϑ i -0.29 -0.25 -0.16 -0.06 -0.26 0.40 0.50 0.12
w i 0.13 0.13 0.14 0.14 0.11 0.12 0.11 0.13
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指标中心度、原因度和权重

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参数 C1 C2 C3 C4 C5 C6 C7 C8
φ i 13.15 13.15 14.46 13.81 10.86 12.66 11.24 12.80
ϑ i -0.29 -0.25 -0.16 -0.06 -0.26 0.40 0.50 0.12
w i 0.13 0.13 0.14 0.14 0.11 0.12 0.11 0.13
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基于DEMATEL和TOPSIS的低空安防系统方案多属性评价方法
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施玮 1 , 吴坚 2, *
科学技术与工程 | 论文·航空、航天 2025,25(14): 6109-6117
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科学技术与工程 | 论文·航空、航天 2025, 25(14): 6109-6117
基于DEMATEL和TOPSIS的低空安防系统方案多属性评价方法
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施玮1 , 吴坚2, *
作者信息
  • 1. 浙江浙商汇融私募基金管理有限公司, 杭州 310000
  • 2. 上海海事大学经济管理学院, 上海 201306
  • 施玮(1988—),男,汉族,浙江金华人,硕士。研究方向:数字经济 低空经济。E-mail:

通讯作者:

*吴坚(1977—),男,汉族,江苏无锡人,博士,教授。研究方向:群体决策 社会网络。E-mail:
A Multi-Attribute Evaluation Method for Low-Altitude Security System Solutions Based on DEMATEL and TOPSIS
Wei SHI1 , Jian WU2, *
Affiliations
  • 1. Zhejiang Zheshang Huirong Private Equity Fund Management Co., Ltd., Hangzhou 310000, China
  • 2. School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China
出版时间: 2025-05-18 doi: 10.12404/j.issn.1671-1815.2408775
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针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference of arrival )无线电技术的多源融合方案的基础上,构建无人飞行器探测技术评价指标体系,并建立了一种基于决策试验评估实验室(decision-making trial and evaluation laboratory,DEMATEL)和优劣解距离法(technique for order preference by similarity to an ideal solution,TOPSIS)的多属性评价方法。结果发现,以TDOA为基础的多源融合方案是构建城市低空安防体系的有效路径和普适性方案。研究表明,低空安防体系的建设是一个系统性工程,需要政府、企业和社会各方的共同努力,在技术、数据、运营等多个层面进行整合,以适应未来低空经济的发展需求。

低空经济  /  低空安防系统  /  多属性评价方法  /  TDOA(time difference of arrival )技术  /  无人机管控

In order to address a series of safety management issues involved in low-altitude economic development, the technical routes and principles of low-altitude economy as well as the operational experience of implementation plans are summarized, and four universal construction plans for low-altitude security and protection are analyzed, namely the radar and integrated perception technology fusion plan, the broadcast automatic dependent surveillance technology plan, the remote identification technology plan, and the multi-source fusion plan based on TDOA radio technology. On this basis, an evaluation index system for unmanned aerial vehicle detection technology was constructed, and a multi-attribute evaluation method based on DEMATEL and TOPSIS was established. The results show that the multi-source fusion plan based on time difference of arrival (TDOA) is an effective and universal solution for building a low-altitude security system in cities. It is concluded that the construction of a low-altitude security system is a systematic project, which requires the joint efforts of governments, enterprises and the whole society. Integration is needed at the levels of technology, data and operation to meet the future development needs of the low-altitude economy.

low-altitude security  /  defense system construction framework  /  multi-attribute evaluation method  /  TDOA-based multi-source fusion plan  /  drone control
施玮, 吴坚. 基于DEMATEL和TOPSIS的低空安防系统方案多属性评价方法. 科学技术与工程, 2025 , 25 (14) : 6109 -6117 . DOI: 10.12404/j.issn.1671-1815.2408775
Wei SHI, Jian WU. A Multi-Attribute Evaluation Method for Low-Altitude Security System Solutions Based on DEMATEL and TOPSIS[J]. Science Technology and Engineering, 2025 , 25 (14) : 6109 -6117 . DOI: 10.12404/j.issn.1671-1815.2408775
在科技进步和技术创新的推动下,低空经济作为一种新兴的经济形态,正在迅速崛起,成为推动经济增长和新质生产力发展的关键力量[1]。根据《中国低空经济发展研究报告(2024)》的数据,2023年中国低空经济的市场规模已达5 059.5亿元,同比增长33.8%。2024年,中国政府将低空经济纳入国家战略性新兴产业。这标志着低空经济正式成为国家战略性新兴产业,凸显了其在国家经济转型中的关键作用。随着低空活动的快速增长,其“异构、高密度、高频次、高复杂性”的特征也带来了一系列安全挑战[2-3],包括无人机的无序飞行、恶意使用、航空安全隐患、隐私侵犯和电磁干扰等问题[4]。这些问题对航空秩序、公共安全和国家安全构成了潜在威胁。在这一背景下,构建一个有效的低空安防体系显得尤为重要,它不仅决定了低空经济能否实现可持续发展,更是保障国家安全和公共安全的关键。
低空安防系统作为低空安全体系的核心技术支撑,提供了全面的技术解决方案和操作能力[5]。该系统旨在保护低空空域的安全,通过综合技术手段实现对无人机等低空飞行器的有效监测、识别、跟踪、定位、指挥控制、反制拦截[6],并对潜在威胁进行分析和响应。
近年来,中外学者在低空安防领域取得了一系列重要研究成果,为低空经济的可持续发展提供了坚实的技术保障。罗俊海等[7]系统综述了无人机探测与对抗技术的发展现状与应用前景,指出多技术融合是实现高效低空安防的关键路径。王鼎等[8]提出的协同二维DOA(data oriented architecture)和TDOA( time difference of arrival)观测量的定位新方法,显著提升了超视距短波辐射源的定位精度,为城市级网格化无人机管控系统的构建提供了新的技术思路。在探测技术方面,徐辰宇等[9]对“低慢小”目标探测技术的研究进展进行了全面梳理,特别强调了光电识别跟踪技术在复杂环境下的应用优势。Vinogradov等[10]深入研究了远程识别技术(Remote ID)技术在空域分离和多智能体导航中的应用,为低空飞行器的协同管理提供了重要参考。刘文涛[11]和陈琳等[12]分别从无线电监测和视觉跟踪的角度,探讨了提升低空飞行器探测精度的有效方法。这些研究成果共同推动了低空安防技术的创新发展,为构建智能化、网格化的低空安全防护体系奠定了坚实基础。当前,低空安防系统通过整合雷达探测、Remote ID、无线电频谱监测、光电识别和声音监测等多种技术手段,已形成对无人机等低空飞行器的全方位监测能力。其中,基于TDOA技术的城市级网格化系统实现了对目标的精准识别与实时追踪,显著提升了城市低空安全防护水平。随着低空经济的持续扩展,未来低空安防技术将朝着多源信息融合、智能决策响应和协同管控的方向深入发展,为低空经济的安全有序发展提供更加有力的技术支撑。
然而,面对低空活动的快速增长和电磁环境的复杂性,现有系统在技术成熟度、安全管控能力、监管协同效率等方面仍有待提高。因此,现将深入探讨低空安防系统的无人飞行器探测与监管技术4个方案:雷达与通感一体技术方案、广播式自动相关监视技术(automatic dependent surveillance-broadcast,ADS-B )技术方案、Remote ID技术方案和基于TDOA技术的多源融合方案,并通过构建无人飞行器探测技术评价指标体系,提出一种基于决策试验评估实验室(decision-making trial and evaluation laboratory,DEMATEL)和优劣解距离法(Technique for Order Preference by Similarity to an Ideal Solution,TOPSIS)的多属性评价方法,对无人飞行器探测与监管技术方案进行评估。最后,讨论如何通过技术创新和政策引导,提高低空安防系统的效能,以适应未来低空经济的发展需求。
低空经济是以地表1 000 m以下空域为载体,依托无人机、eVTOL等飞行器发展的新兴业态,其核心特征表现为“异构、高密度、高频次、高复杂性”的大容量融合飞行。如表1所示,与传统航空相比,其特殊性体现在:异构飞行器混合运行导致空域管理复杂化,高频次活动要求分钟级调度能力,以及城市、边境等多场景叠加带来的运行挑战。这些特征对安防体系提出了更高要求,亟需构建全域感知、动态管控、智能反制三位一体的综合防护系统,通过无人机交通管理(Unmanned Aircraft Traffic Management,UTM)、多源监控网络等技术手段实现高效管理。
中国各地正积极推进低空安防体系建设。北京市提出“平战结合”建设要求,重点突破全类型无人机管理、多技术路线融合、协同反制能力建设等关键环节[13-14];深圳通过“低空智能融合基础设施建设项目”,已建成覆盖全市的监控网络,实现重点区域入侵无人机100%发现率[15]。这些实践为构建标准化低空安防模式提供了重要参考。支撑低空经济发展的关键在于平衡安全与效率。当前需要重点突破小型飞行器探测、通信抗干扰等技术瓶颈,同时建立跨部门协同机制。随着行业规模扩大,安防体系必须向“感知-决策-响应”全链条自主化方向演进,通过技术创新和机制完善,为低空经济提供安全可靠的发展环境。
目前,多种技术手段被应用于无人飞行器的探测与监管,包括雷达技术、Remote ID技术、ADS-B技术、无线电探测技术以及基于TDOA技术的多源融合方案等。这些技术各有优势,但也存在一定的局限性。例如,雷达技术能够提供较为准确的距离和速度信息,但在面对小型低慢小飞行器时可能会受到探测距离和分辨率的限制[16];Remote ID技术通过广播飞行器的身份信息,便于监管,但依赖于飞行器的主动配合[17];ADS-B技术在民航领域应用广泛,但对于非合作目标的探测能力有限[18];无线电探测技术可以实现对飞行器的被动探测,但容易受到电磁环境的干扰[19-21];而基于TDOA技术的多源融合方案则通过整合多种技术手段,提高了探测的精度和可靠性,尤其适用于复杂环境下的低空安防需求[22]
雷达与通感一体[16]是指将雷达功能和通信功能有机融合在同一个系统中,使其兼具目标探测、定位、跟踪等雷达特性以及信息传输、交互等通信功能,实现 “一站多用”,从而更高效地利用频谱资源、降低硬件成本、提升系统综合效能等。雷达与通感一体技术及应用特征如表2所示。
RID技术(Remote ID)即远程识别技术,是一种用于增强无人机监管和飞行安全的技术手段[17]。RID技术通过传输位置、高度、速度和识别特征的数据,使飞行中的无人机可以被其他人远程识别。该信息由无人机通过无线电传输,因此几乎可以实时显示无人机的位置。运行识别包含广播式运行识别与网络式运行识别两种模式,运行识别信息通过报文方式实时传输。对于微型无人驾驶航空器系统,应当通过广播式运行识别发送识别信息;对于轻型、小型无人驾驶航空器系统,应当同时通过广播式运行识别与网络式运行识别发送识别信息。运行识别技术,可以提升微型、轻型、小型无人驾驶航空器的可靠被监视能力,这对于确保低空空域运行安全至关重要。通过有效的运行识别,可以显著降低航空活动中的碰撞风险,保障无人机与其他航空器的飞行安全。尽管有《民用无人驾驶航空器系统安全要求》《民用微轻小型无人驾驶航空器运行识别概念(暂行)》等文件的出台,但技术实现仍然是一个挑战。而且它依赖于对方自发位置报告而获得对它监视的能力,对于非合作目标起不到监视作用。
广播式自动相关监视技术(automatic dependent surveillance-broadcast,ADS-B)[18]。ADS-B在民航体系已经具有成熟经验,主要依靠飞机上的设备自动向地面站以及周边其他配备相应接收设备的飞机广播自身的各种信息,包括飞机的精确位置(经纬度、高度等)、速度、航向、航班号等。实践中,通过在无人航空器上装在ADS-B接收器,实现对其他飞行器的自动避让。但该体系目标实现的基础假设是:①无人机装载了ADS-B功能模块;②无人机是规范产品。当前,对低空安全威胁最大的无人机主要是DIY无人机及破解版品牌无人机。DIY无人机装载ADS-B功能模块的动机薄弱,同时在高速飞行,增程等方面具有更强功能。而无人机破解包括硬件破解和软件破解,但最终目的在于突破“限高”“禁飞”等飞行限制。ADS-B功能实现中,实时播报飞机高度,经纬度,速度等信息,是无人机破解中必然涉及的部分。故而ADS-B对于DIY及破解版品牌无人机的安防效用较低。
无线电探测主要有到达角(angle of arrival,AOA)、认知无线电协议破解(cognitive radio protocol cracking,CRPC)、时间差定位法(time difference of arrival,TDOA)三种技术路线,且都已实现产业化[19-21]。三种路线共同的优点是无源检测,检测过程不发射电磁波,故而对于周边环境影响较小,隐蔽性好。共同的局限性为对无线电静默飞行器缺乏检测能力。表3展示了无线电探测技术分类及应用特征。
综合考虑检测精度,对周边环境的影响,相关法规的限制,产业化程度,结合各技术路线的优缺点及商业实践经验,提出一种较优的城市网格化低空安防的路线是:以TDOA技术为基础,依据具体场景配套光电、雷达、声学感知等多源检测能力的方案[22]。该方案已参与国内一些重大活动的低空监管典型应用场景。例如,在成都大运会期间,低空安防方案通过应用TDOA频谱探测定位、AOA交叉测向、雷达探测、光电跟踪等多重探测定位技术,以固定式、车载式、便携式等多种防控模式进行灵活运用,实现防控的全方位与高效性。TDOA频谱探测定位系统能够实现合作及非合作目标的监管,在此基础上,雷达作为补充手段能够实现静默无人机的有效监管,进而实现低空安全保障的完整周密。
通过对现有的无人飞行器探测与监管技术进行研究和总结,本文研究拟确定5个技术方案 D = { D 1 , D 2 , D 3 , D 4 , D 5 }作为评价对象。其中 D 1为雷达与通感一体技术方案, D 2为Remote ID 技术方案, D 3为ADS-B 技术方案, D 4为基于无线电的探测技术方案, D 5为基于TDOA技术的多源融合方案。
通过综合考虑行业标准与规范、市场需要以及现有文献成果,本文研究确定了飞行器探测技术评估5个一级指标和8个二级指标,如图1所示。
为实现更加详细的评估,二级指标被设定为评价指标集合 C = { C j j = 1,2 , , 8 }。这些指标综合考虑了对无人飞行器探测过程中的探测表现、可靠性、技术创新性、成本以及与现有系统是否兼容等方面。
探测能力包括探测范围、探测精度、分辨率、目标识别能力等。探测范围即技术能够有效探测到飞行器的最远距离、最大高度、最大覆盖角度等,这直接关系到其对空域的监控广度;探测精度包括对飞行器位置(方位、距离、高度)、速度、姿态等参数测定的精确程度,高精度的探测有助于准确掌握飞行器状态;分辨率用来衡量能否清晰区分相邻飞行器的能力,高分辨率可避免目标混淆。目标识别能力为了评估是否能准确识别不同类型、型号的飞行器,以及区分飞行器与其他干扰目标(如鸟类、气象目标等)的能力。
实时性包括数据更新频率和响应时间。数据更新频率指单位时间内能够更新飞行器相关探测数据的次数,频率越高,越能及时反映飞行器的动态变化。响应时间指从飞行器进入探测范围到系统输出有效探测结果的时间间隔,短响应时间利于快速应对潜在威胁。
稳定性包括工作时长稳定性和环境适应性稳定性。工作时长稳定性指的是在连续长时间工作状态下,各探测技术性能保持稳定的程度,如是否出现性能波动、数据异常等情况。环境适应性稳定性考察在不同气象条件(雨、雪、雾、风等)、温度、湿度等环境变化下,技术性能的稳定表现。
抗干扰能力由电磁干扰抗性和自然干扰抗性两方面。磁干扰抗性指在复杂电磁环境中(如存在多源无线电信号、电磁脉冲等干扰),抵抗干扰并维持正常探测工作的能力。自然干扰抗性指的是针对自然因素产生的干扰(如雷电、云层反射等),能否有效应对并保证探测准确性。
故障率可以用平均故障间隔时间(mean time between failures,MTBF)计算,用以统计各探测技术在正常运行期间,相邻两次故障的平均间隔时间,长 MTBF 意味着高可靠性。
复杂度包括系统架构复杂度和操作复杂度,系统架构复杂度用于评估探测技术所依托的系统架构的复杂程度,包括硬件组成、软件算法等,简单合理的架构利于维护和升级;操作复杂度考察操作人员对该探测技术相关设备进行操作的难易程度,简单易操作的设备可降低人力成本和培训难度。创新性判断是否采用了新的信号处理技术、探测原理、设备组件等,以及分析该探测技术在未来一段时间内是否有进一步改进、拓展应用的潜力。
成本效益包括:①研发成本,即统计从技术研发初期到可应用阶段所投入的全部研发费用;②制造成本:包括生产制造探测设备所需的原材料、零部件、加工等成本;③运营成本:涵盖设备运行过程中的能源消耗、维护保养、人员培训等各项费用;④寿命周期成本:综合考虑研发、制造、运营以及设备最终报废处理等全生命周期的成本,以评估其整体经济合理性。
兼容性包括与现有系统兼容和多技术协同兼容性。与现有系统兼容包括硬件兼容性和软件兼容性,即考察探测技术相关设备能否与现有飞行器、地面站、空域管理系统等的硬件设备顺利对接。以及判断其软件系统是否能与现有相关软件平台(如数据处理软件、空域监控软件等)兼容,确保数据流畅交换和处理。多技术协同兼容性包括与其他探测技术协同和与飞行器通信技术协同。即评估该探测技术能否与其他常用的飞行器探测技术(如雷达与 Remote ID 协同等)协同工作,提高整体探测效果。并判断是否能与飞行器自身的通信技术(如无人机的 Remote ID 广播、有人机的通信系统等)协同工作,以便更好地获取飞行器信息。
评价主体根据实际的评价问题选定评价指标集合 C = C j j = 1,2 , , n,以及评价对象集合 D = D i i = 1,2 , , m。据此,构建多属性评价矩阵 F = ( f i j ) m × n,其中 f i j表示评价对象 D i在指标 C j下的评价值。
决策试验和评估实验室(DEMATEL)方法是一种面向复杂系统因素分析的方法[23-24]。该方法基于图论通过构建分析结构模型来认知复杂因素之间的因果关联关系并辨析关键要素,能够有效地识别因素之间的因果关系。具体步骤如下。
步骤1 邀请专家学者打分确定各指标的直接影响矩阵 A = ( a i j ) n × n a i j表示指标 C i对指标的 C j的直接影响程度, a i j = 0表示无影响、 a i j = 1表示影响较小、 a i j = 2表示影响适中、 a i j = 3表示影响较大、 a i j = 4表示影响极大,并且规定 a i i = 0。将所有受访者的评分矩阵进行算数平均处理后得到各指标的直接影响矩阵。
步骤2 确定规范化的直接影响力矩阵 B = ( b i j ) n × n
B = ( b i j ) n × n = A / s
式(1)中: s = m a x m a x 1 i n i = 1 n a i j , m a x 1 i n j = 1 n a i j,表示直接影响矩阵 A的行和与列和的最大值。
步骤3 计算综合影响矩阵 P = ( p i j ) n × n
P = ( p i j ) n × n = B ( I - B ) - 1
式(2)中: p i j为指标 C i对指标的 C j的综合影响程度; I为同纬度的单位矩阵。
步骤4 计算各个指标的中心度 φ i和原因度 ϑ i。首先,计算矩阵 P的每行之和为 f i = j = 1 n t i j,每列之和为 e j = i = 1 n p i j
φ i = f i + e j
θ i = f i - e j
式中: φ i为指标在整个系统中的相对重要程度,值越大表明该指标的重要性越大; θ i揭示了指标间的因果关系:其值大于0时,表明该指标为原因因素;其值小于0时,表明该指标为结果因素。
步骤5 确定指标权重 w i
w i = φ i 2 + θ i 2 i = 1 n φ i 2 + θ i 2
TOPSIS法又称优劣解距离法,通过计算评价对象与最优解、最劣解之间的欧氏距离, 获得评价对象与理想解的贴近度,进而对评价对象进行相对优劣评价[25-26]。该方法能够充分利用原始数据的信息,其结果能精确地反映各评价方案之间的差距。计算步骤如下。
步骤1 规范化的评价矩阵 X = ( x i j ) m × n,确定正理想解 X +和负理想解 X -
X + = { m a x x i j 1 i m j = 1,2 , , n } = { x 1 + , x 2 + , , x n + }
X - = { m i n x i j 1 i m j = 1,2 , , n } = { x 1 + , x 2 + , , x n + }
步骤2 计算各评价对象到正理想解 X +和负理想解 X -之间的欧式距离,分别记作理想区分度 ( χ + )和负理想区分度 ( χ - )
χ i + = j = n w j ( x j + - x i j ) 2 ,   i = 1,2 , , m
χ i - = j = n w j ( x j - - x i j ) 2 ,   i = 1,2 , , m
步骤3 计算各个评价对象相对于理想对象的相对贴近度 C i
C i = χ i - χ i - + χ i +
式(10)中: C i 0,1, C i越大表示被评价对象越接近理想对象。
在本文研究中,通过构建一个专家小组获得相关评估数据。专家小组包括5名参加者,其中3名来自无人飞行器设计与制造企业的技术人员,2名是飞行器探测研究领域的专业学者。邀请专家小组成员对各指标进行比较评估,并对各技术方案在指标下的表现进行打分。将所有受访者的评分矩阵进行算数平均处理后,得到各指标的直接影响矩阵 A = ( a i j ) 8 × 8以及规范化的各技术方案在指标下的评价矩阵 X = ( x i j ) 5 × 8,结果如表5表6所示。其中表5的指标打分遵循3.2节的介绍的规则,表6的评价数据是要求受访者对每个方案在每个指标下使用0~1内数值打分,分值越高,表现越好。需要注意的是故障率 C 5为负向表现,而其他指标为正向表现,所以设置打分规则为故障率越低,打分越高。
首先使用DEMATEL方法确定各指标的权重。具体步骤如下。
(1)基于各指标的直接影响矩阵 A = ( a i j ) 8 × 8确定规范化的直接影响力矩阵 B = ( b i j ) 8 × 8,如表7所示。
(2)计算综合影响力矩阵 P = ( p i j ) 8 × 8,如表8所示。
(3)基于式(3)和式(4)计算各个指标的中心度 φ i和原因度 ϑ i,然后基于式(5)计算 w i,如表9所示。
进一步地,在获得指标权重的基础上利用TOPSIS法对5个无人飞行器探测技术进行优劣评价,具体计算步骤如下。
(1)在规范化的评价矩阵 X = ( x i j ) 5 × 8中确定正理想解 X +和负理想解 X -:
X+={0.83,0.82,0.88,0.82,0.88,0.88,0.80,0.83}
X-={0.67,0.72,0.75,0.70,0.77,0.58,0.65,0.75}
(2)计算各评价对象的理想区分度 χ +和负理想区分度 χ -:
χ + = { 0.11,0.12,0.12,0.08,0.05 }
χ - = { 0.09,0.07,0.09,0.09,0.14 }
(3)计算各个评价对象相对于理想对象的相对贴近度 C i:
C i = { 0.45,0.36,0.42,0.53,0.75 }
进而得到无人飞行器探测技术备选方案的排序结果:
D 5 > D 4 > D 1 > D 3 > D 2
通过以上得到的模型结果可知,基于TDOA技术的多源融合方案是现阶段综合表现较优的无人飞行器探测与监管技术,其次是基于无线电的探测技术方案、雷达与通感一体技术方案、ADS-B 技术方案,最后为Remote ID 技术方案。
在实际应用中,TDOA技术已经得到了广泛验证。例如,在成都大运会期间,低空安防系统通过应用TDOA频谱探测定位、AOA交叉测向、雷达探测、光电跟踪等多重探测定位技术,以固定式、车载式、便携式等多种防控模式进行灵活运用,实现了防控的全方位与高效性。大运会保障期间,低空安防系统成功预警并协助处置“黑飞”事件数十起。此外,TDOA技术在移动基站定位中也得到了广泛应用,通过测量信号到达多个基站的时间差来确定目标位置,这种技术在城市环境中表现出色,能够有效应对多径效应和信号干扰。
通过对低空安防技术路线的深入分析和国内重点企业商业实践案例的探讨,提出了低空安防普适性的建设方案:雷达与通感一体技术方案、广播式自动相关监视技术(ADS-B )技术方案、远程识别技术(Remote ID)技术方案和基于TDOA技术的多源融合方案。 本文构建无人飞行器探测技术评价指标体系,建立了一种基于DEMATEL和TOPSIS的多属性评价方法,并进行对这些方案进行排序,得到以下结论。
(1)基于TDOA技术的多源融合方案是构建城市低空安防体系的最优路径。通过整合雷达、光电、声音等多种探测技术,该方案在探测精度、环境适应性、多技术协同性等方面表现突出,能够有效覆盖合作与非合作目标,并在实际应用中(如成都大运会)验证了其高效性与可靠性。
(2) DEMATEL-TOPSIS模型为低空安防技术方案评价提供了科学方法。通过构建包含探测能力、实时性、成本效益等8项指标的评价体系,结合专家权重分析与方案排序,该方法能够客观量化各技术方案的优劣,为决策提供可靠依据。
(3)低空安防体系建设需多方协同与技术深度整合。政府、企业和社会需在政策支持、技术研发、数据共享等层面形成合力,同时注重“平战结合”原则,兼顾日常监管与应急响应能力,以保障低空经济的安全性与可持续发展。
(4)未来需强化技术创新与政策引导。针对电磁环境复杂化、高速无人机漏报率高等挑战,需持续优化探测算法与设备布局,并通过法规完善推动技术标准化,促进低空安防系统与服务体系的深度融合。
通过构建全面、高效、智能的低空安防体系,不仅可以保障低空经济活动的安全性和秩序性,还能为社会经济的现代化转型提供强有力的支持。随着技术的不断进步和政策的不断完善,低空安防体系将在未来发挥越来越重要的作用,为国家经济的高质量发展贡献新的力量。
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doi: 10.12404/j.issn.1671-1815.2408775
  • 接收时间:2024-11-24
  • 首发时间:2025-07-09
  • 出版时间:2025-05-18
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  • 收稿日期:2024-11-24
  • 修回日期:2025-04-23
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    1. 浙江浙商汇融私募基金管理有限公司, 杭州 310000
    2. 上海海事大学经济管理学院, 上海 201306

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*吴坚(1977—),男,汉族,江苏无锡人,博士,教授。研究方向:群体决策 社会网络。E-mail:
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2种不同金属材料的力学参数

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total species (%)

Genus
种数
Number of
species
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Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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