跳频信号的侦察技术研究
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摘要
跳频通信因其良好的抗干扰性、低截获概率及组网能力,在军事通信中得到了广泛的应用,也向通信侦察提出了严峻的挑战。开展对跳频信号侦察的研究,寻求截获、估计、分选跳频信号的方法,已成为当前通信侦察领域紧迫而艰巨的任务之一。论文研究了复杂电磁环境下跳频信号侦察的关键技术,主要包括跳频信号的检测、参数估计和信号分选三部分内容。
首先,将各种时频表示应用于跳频信号的检测,仿真其性能,在时频聚焦性和抑制交叉项两项指标上定性和定量比较了各种时频表示的优劣,寻求综合性能较好的时频表示。建立了跳频信号的数学模型,给出了跳频信号各种参数的定义;重点研究了各种线性时频表示、二次时频分布、重排类时频分布、组合时频分布在跳频信号检测中的应用;利用信息熵,定量评价了各类时频分布的性能,并估算了几种典型时频分布的计算复杂度,给出了各类时频分布的综合评价。
其次,针对单天线宽带数字接收系统,研究了复杂电磁环境下基于时频分析的跳频信号参数盲估计算法。针对跳频信号侦察,提出了“复合信息熵”的定量评估指标,该指标综合考虑电磁环境中的信号类型数、跳频信号数目、跳速和信道使用情况,由类型熵、密度熵和分布熵三部分组成;基于信道化门限和时频分析完成了去噪和信号预选;基于谱图对单个跳频信号的跳周期、跳时和载频进行了盲估计;基于组合时频分析(SP&SPWVD),对多个跳频信号的跳周期、跳时、载频和幅度参数进行了盲估计,并给出了各参数估计的仿真性能。
再次,基于时频分析、空间谱估计,结合数字信道化、时频聚焦等技术对FH信号、FH/DS信号进行空时频测向,实现了欠定条件下的高精度测向。根据传统的空时阵列模型,结合信号的时频分析,建立了空时频分布的数学模型;分析了空时频测向能获得时频增益的原因,研究了增益大小与哪些因素相关;利用空时频分析实现了多个跳频信号的DOA估计,提出了适合无“频率碰撞”情况下的线性空时频DOA估计算法;虽然利用空时频技术能够实现欠定条件的多信号测向,但在N /M值较大情况因为信号之间的互扰较大使测向性能欠佳,故再结合数字信道化技术,解决了N /M值较大情况信号之间互扰很大的问题,实现了多个跳频信号的高精度测向;将空时频分析和宽带信号测向方法,实现了欠定条件下多FH/DS信号的DOA高精度估计。
最后对跳频信号分选技术进行了深入的研究,针对不同的应用场合提出了相应的分选算法。提出了一种适应于环境中仅存在异步组网电台的实时分选方法,该方法计算量少,便于实时分选,适合应用于快速、高速跳频信号的侦察;提出了一种类数目K值的估计和优选初始聚类中心的改进K-Means算法;初始聚类中心优选能使聚类迭代次数大为减少,并能避免聚类过程中陷入局部最小,增强了聚类的鲁棒性;利用改进K-Means聚类算法对HDW集合进行了聚类分选;针对高斯核参数σ的优选问题,提出了粗搜索和精估计相结合的改进方法,在得到精确的σopt同时减少了总搜索次数;利用密度分布图和领域半径、门限参数实现了KKM算法中类数目K的估计和初始聚类中心的优选;利用基于高斯核函数的K-Means对跳速和到达角均时变的跳频信号进行聚类分选,分选效果良好。
Frequency hopping (FH) communication has been widely applied in military communications, due to its anti-jamming performance, low probability of interception and detection, and networking capability. And it’s a great challenge to carry on radio reconnaissance. Now, the research of FH signals reconnaissance, such as signal interception, parameter estimation, and signal sorting is one of the major tasks in communication reconnaissance. A series of key technologies of FH communication reconnaissance in complex electromagnetic environment (CEE), including FH signals detection, parameter estimation, and signal sorting, etc., were mainly researched in this thesis.
Firstly, to find the preferable time-frequency representations (TFRs) for FH signals detection, the performance of various TFRs was simulated and quantificationally compared in time-frequency concentration and suppression cross-term interference. Then, the mathematical model of FH signal was build, and the definitions of FH signal’s parameters were introduced. The applications of some linear TFRs, bilinear TFRs, reassigned TFRs, and synthesized TFR for FH signals detection were emphatically researched. The representation performance of various TFRs was evaluated quantificationally utilizing information entropy. Moreover, the compute complexities of some typical TFRs were given.
Secondly, using single-antenna wideband receiver, a series of new algorithms of blind parameters estimation in CEE based on time-frequency analysis were proposed. In FH signals reconnaissance field, a new quantificational evaluation of electromagnetic environment complexity named‘synthesized information entropy’, which consists of type-entropy, density-entropy and distribution-entropy, was presented. And then, the denoise processing and signal preselection based on TFRs and channelization limits were accomplished. When there was only one FH signal in the interception band, the blind estimation of hop period, hop timming, and carrier frequency would be gained by spectrum and conventional method. The blind parameters estimation algorithm based on synthesized TFR (SP&SPWVD) when there were multicomponent FH signals was proposed, and the performance estimation was simulated numerically.
Thirdly, based on time-frequency analysis, spatial spectrum estimation, integrating digital channelization and time-frequency focusing technologies, the directions of arrival (DOA) of FH or FH/DS signals were estimated accurately in underdetermined case. The mathematical model of spatial time-frequency distribution (TFD) was built based on conventional spatial-time array model and time-frequency analysis. Exploiting STFD to estimate DOAs of multicomponent FH signals can gain SNR enhancement, and the factors that can affect the enhancement value were discussed. Furthermore, an algorithm to estimate DOAs of multicomponent FH signals based on linear STFD was proposed in non-frequency-collisions case. The DOAs estimation can be achieved in underdetermined case, but when N /M is large, the estimation will not be precise because of the interferences among multicomponent signals. This problem is solved solved by using digital channelized receiver. We also proved that the accurate estimation of DOAs of FH/DS signals could be achieved in underdetermined case, and the method was based on STFD and direction finding technologies of wideband signals.
At last, the thesis investigted the FH signal sorting technologies. One novel sorting method for non-orthogonal FH signals was presented. In contrast with some conventional techniques, the proposed method has a lower compute complexity, which is convenient for the real-time sorting and appropriate for fast FH signals reconnaissance. And then, an improved K-Means clustering algorithm with optimal initial clustering center and estimation of K value was proposed. Because the initial centers are optimal, the clustering has less iterations, and clustering in the local minimum is also avoided. The improved K-Means clustering algorithm was applied in the clustering of HDW aggregation, which was with lower compute complexity but more robust than conventional K-Means algorithm. To obtain the optimal parameterσof gaussian kernel function, an improved method including coarse searching and precise estimation was presented, which can obtain preciseσopt with less iterations. The optimization of initial clustering centers and the estimation of K value of kernel K-Means (KKM) clustering were achieved by using density distribution, region radius, and adaptive limits. The clustering sorting of FH signals with time-variable hop periods and DOAs was achieved by using gaussian KKM algorithm, and the simulation results demonstrated that the clustering sorting was effective.
首先,将各种时频表示应用于跳频信号的检测,仿真其性能,在时频聚焦性和抑制交叉项两项指标上定性和定量比较了各种时频表示的优劣,寻求综合性能较好的时频表示。建立了跳频信号的数学模型,给出了跳频信号各种参数的定义;重点研究了各种线性时频表示、二次时频分布、重排类时频分布、组合时频分布在跳频信号检测中的应用;利用信息熵,定量评价了各类时频分布的性能,并估算了几种典型时频分布的计算复杂度,给出了各类时频分布的综合评价。
其次,针对单天线宽带数字接收系统,研究了复杂电磁环境下基于时频分析的跳频信号参数盲估计算法。针对跳频信号侦察,提出了“复合信息熵”的定量评估指标,该指标综合考虑电磁环境中的信号类型数、跳频信号数目、跳速和信道使用情况,由类型熵、密度熵和分布熵三部分组成;基于信道化门限和时频分析完成了去噪和信号预选;基于谱图对单个跳频信号的跳周期、跳时和载频进行了盲估计;基于组合时频分析(SP&SPWVD),对多个跳频信号的跳周期、跳时、载频和幅度参数进行了盲估计,并给出了各参数估计的仿真性能。
再次,基于时频分析、空间谱估计,结合数字信道化、时频聚焦等技术对FH信号、FH/DS信号进行空时频测向,实现了欠定条件下的高精度测向。根据传统的空时阵列模型,结合信号的时频分析,建立了空时频分布的数学模型;分析了空时频测向能获得时频增益的原因,研究了增益大小与哪些因素相关;利用空时频分析实现了多个跳频信号的DOA估计,提出了适合无“频率碰撞”情况下的线性空时频DOA估计算法;虽然利用空时频技术能够实现欠定条件的多信号测向,但在N /M值较大情况因为信号之间的互扰较大使测向性能欠佳,故再结合数字信道化技术,解决了N /M值较大情况信号之间互扰很大的问题,实现了多个跳频信号的高精度测向;将空时频分析和宽带信号测向方法,实现了欠定条件下多FH/DS信号的DOA高精度估计。
最后对跳频信号分选技术进行了深入的研究,针对不同的应用场合提出了相应的分选算法。提出了一种适应于环境中仅存在异步组网电台的实时分选方法,该方法计算量少,便于实时分选,适合应用于快速、高速跳频信号的侦察;提出了一种类数目K值的估计和优选初始聚类中心的改进K-Means算法;初始聚类中心优选能使聚类迭代次数大为减少,并能避免聚类过程中陷入局部最小,增强了聚类的鲁棒性;利用改进K-Means聚类算法对HDW集合进行了聚类分选;针对高斯核参数σ的优选问题,提出了粗搜索和精估计相结合的改进方法,在得到精确的σopt同时减少了总搜索次数;利用密度分布图和领域半径、门限参数实现了KKM算法中类数目K的估计和初始聚类中心的优选;利用基于高斯核函数的K-Means对跳速和到达角均时变的跳频信号进行聚类分选,分选效果良好。
Frequency hopping (FH) communication has been widely applied in military communications, due to its anti-jamming performance, low probability of interception and detection, and networking capability. And it’s a great challenge to carry on radio reconnaissance. Now, the research of FH signals reconnaissance, such as signal interception, parameter estimation, and signal sorting is one of the major tasks in communication reconnaissance. A series of key technologies of FH communication reconnaissance in complex electromagnetic environment (CEE), including FH signals detection, parameter estimation, and signal sorting, etc., were mainly researched in this thesis.
Firstly, to find the preferable time-frequency representations (TFRs) for FH signals detection, the performance of various TFRs was simulated and quantificationally compared in time-frequency concentration and suppression cross-term interference. Then, the mathematical model of FH signal was build, and the definitions of FH signal’s parameters were introduced. The applications of some linear TFRs, bilinear TFRs, reassigned TFRs, and synthesized TFR for FH signals detection were emphatically researched. The representation performance of various TFRs was evaluated quantificationally utilizing information entropy. Moreover, the compute complexities of some typical TFRs were given.
Secondly, using single-antenna wideband receiver, a series of new algorithms of blind parameters estimation in CEE based on time-frequency analysis were proposed. In FH signals reconnaissance field, a new quantificational evaluation of electromagnetic environment complexity named‘synthesized information entropy’, which consists of type-entropy, density-entropy and distribution-entropy, was presented. And then, the denoise processing and signal preselection based on TFRs and channelization limits were accomplished. When there was only one FH signal in the interception band, the blind estimation of hop period, hop timming, and carrier frequency would be gained by spectrum and conventional method. The blind parameters estimation algorithm based on synthesized TFR (SP&SPWVD) when there were multicomponent FH signals was proposed, and the performance estimation was simulated numerically.
Thirdly, based on time-frequency analysis, spatial spectrum estimation, integrating digital channelization and time-frequency focusing technologies, the directions of arrival (DOA) of FH or FH/DS signals were estimated accurately in underdetermined case. The mathematical model of spatial time-frequency distribution (TFD) was built based on conventional spatial-time array model and time-frequency analysis. Exploiting STFD to estimate DOAs of multicomponent FH signals can gain SNR enhancement, and the factors that can affect the enhancement value were discussed. Furthermore, an algorithm to estimate DOAs of multicomponent FH signals based on linear STFD was proposed in non-frequency-collisions case. The DOAs estimation can be achieved in underdetermined case, but when N /M is large, the estimation will not be precise because of the interferences among multicomponent signals. This problem is solved solved by using digital channelized receiver. We also proved that the accurate estimation of DOAs of FH/DS signals could be achieved in underdetermined case, and the method was based on STFD and direction finding technologies of wideband signals.
At last, the thesis investigted the FH signal sorting technologies. One novel sorting method for non-orthogonal FH signals was presented. In contrast with some conventional techniques, the proposed method has a lower compute complexity, which is convenient for the real-time sorting and appropriate for fast FH signals reconnaissance. And then, an improved K-Means clustering algorithm with optimal initial clustering center and estimation of K value was proposed. Because the initial centers are optimal, the clustering has less iterations, and clustering in the local minimum is also avoided. The improved K-Means clustering algorithm was applied in the clustering of HDW aggregation, which was with lower compute complexity but more robust than conventional K-Means algorithm. To obtain the optimal parameterσof gaussian kernel function, an improved method including coarse searching and precise estimation was presented, which can obtain preciseσopt with less iterations. The optimization of initial clustering centers and the estimation of K value of kernel K-Means (KKM) clustering were achieved by using density distribution, region radius, and adaptive limits. The clustering sorting of FH signals with time-variable hop periods and DOAs was achieved by using gaussian KKM algorithm, and the simulation results demonstrated that the clustering sorting was effective.
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