一种协同抗干扰的导航信号接收技术研究

发布时间：2018-06-15 01:28

本文选题：阵列信号处理 + 空时自适应处理　；参考：《电子科技大学》2017年硕士论文

【摘要】：近年来,卫星导航系统在民用和军事领域方面的重要性与日俱增,但卫星信号弱,易受到来自各方面干扰的问题也更加明显,其中尤以人为的压制式干扰和欺骗式干扰更为突出,因此,研究行之有效的卫星信号抗干扰技术迫在眉睫,提升导航信号接收机的抗干扰能力有着重大的意义。课题研究了导航信号接收中面临的宽带干扰以及窄带干扰,分析了当前主流的抗干扰技术,从空域自适应干扰和时域自适应干扰入手,对比研究了空时自适应抗干扰算法。相比于单纯的空域或者时域的干扰抑制效果差、目标过于局限,空时自适应抗干扰算法弥补了空域自适应抗干扰算法存在的空间自由度不足的问题,以及时域自适应抗干扰算法对宽带干扰抑制能力差的问题。课题研究从以下几个方面展开:首先,围绕GPS导航卫星系统、北斗导航卫星系统、GLONASS导航卫星系统和Galileo导航卫星系统介绍了卫星信号发射接收以及定位的基本原理,分析了导航信号的组成结构并做一说明,对本文提出的引入协同参考信号的原理和过程进行分析说明,分别针对空域和时域的干扰抑制算法进行模型的搭建,并在此基础上对空域和时域的自适应干扰抑制算法的过程进行说明和推演,同时,搭建引入协同参考信号进行干扰抑制的模型,分别针对空域和时域的典型干扰抑制算法进行引入协同参考信号后的算法进行说明,并对先前的空域和时域算法以及加入协同参考信号的算法进行对比分析,验证引入协同参考信号的优势并找出不足,说明具体原因。其次,对空时自适应抗干扰算法的原理、结构模型进行研究,确立相关算法,主要有以下六个,分别是单星约束下的最小输出功率算法(MinC)、单星无约束下的最小输出功率算法(MinU)、协同采样矩阵求逆算法(协同SMI)、多星约束下的最小输出功率算法(MinMC)、最大信干噪比算法(MSJNR)、主成分算法(PC),验证空时域自适应抗干扰算法比单纯的空域或者时域抗干扰算法有着更优越的抗干扰能力,并就MinU、MinC算法同协同SMI算法进行仿真比对,说明协同SMI算法的可行性和优势所在。本文是以MATLAB为仿真平台,通过设置和实际情况相近的干扰信号、期望信号、参考信号以及噪声信号参数,对空、时域以及空时自适应滤波处理的各类算法进行分析,性能分析主要是通过输入和输出的信干噪比(SJNR)这个指标来进行评估,针对现在电磁场空间尤其是军用导航设备中面临的强干扰的复杂电磁环境,创新性的提出了引入其他接收机信号作为参考信号,达到了实现技术简单、效果优势明显的目的,为未来实现地面接收信号组网,信号资源共享,共同抑制干扰的目标打下基础。
[Abstract]:The importance of satellite navigation systems in the civilian and military fields has increased in recent years, but the problem of weak satellite signals and vulnerability to interference from all sources has become even more evident, Especially the artificial suppression jamming and deceptive jamming are more prominent. Therefore, it is urgent to study the effective anti-jamming technology of satellite signal, and it is of great significance to improve the anti-jamming ability of navigation signal receiver. In this paper, the wideband interference and narrowband interference in the navigation signal reception are studied, and the main anti-jamming techniques are analyzed. The space-time adaptive anti-jamming algorithm is compared with the space-time adaptive interference based on the spatial adaptive interference and the time-domain adaptive interference. Compared with the pure interference suppression effect in spatial domain or time domain, the target is too limited. Space-time adaptive anti-jamming algorithm makes up for the lack of spatial degree of freedom in spatial adaptive anti-jamming algorithm. And the time domain adaptive anti-jamming algorithm has poor ability to suppress wideband interference. The research is carried out from the following aspects: firstly, the basic principles of satellite signal transmitting and receiving and positioning are introduced around GPS navigation satellite system, Beidou navigation satellite system, GLONASS navigation satellite system and Galileo navigation satellite system. The structure of navigation signal is analyzed and explained. The principle and process of introducing cooperative reference signal in this paper are analyzed. The model of interference suppression algorithm in spatial domain and time domain is built, respectively. On this basis, the process of adaptive interference suppression algorithm in spatial domain and time domain is explained and deduced. At the same time, a model of interference suppression based on cooperative reference signal is built. After introducing the cooperative reference signal to the typical interference suppression algorithms in the spatial domain and the time domain, the previous algorithms in the spatial domain and the time domain and the algorithms that add the cooperative reference signals are compared and analyzed. Verify the advantages of introducing cooperative reference signals and find out the shortcomings, explain the specific reasons. Secondly, the principle and structure model of space-time adaptive anti-jamming algorithm are studied, and the related algorithms are established. The minimum output power algorithm under single star constraint is MinCn, the minimum output power algorithm under single star constraint is Minu, the cooperative sampling matrix inverse algorithm (cooperative Smil, minimum output power algorithm under multi-star constraint), and the maximum signal-to-noise ratio algorithm. The principle component algorithm (PCA) is used to verify that the space-time adaptive anti-jamming algorithm has better anti-jamming capability than the simple space-time or time-domain anti-jamming algorithm. The Minu MinC algorithm is compared with the cooperative SMI algorithm, which shows the feasibility and advantage of the cooperative SMI algorithm. In this paper, MATLAB is used as a simulation platform to analyze all kinds of adaptive filtering algorithms in space, time domain and space time by setting interference signal, expected signal, reference signal and noise signal parameters similar to the actual situation. The performance analysis is mainly based on the SJNR-based input and output signal-to-noise ratio (SJNRs), aiming at the complex electromagnetic environment with strong interference in the electromagnetic field space, especially in the military navigation equipment. This paper proposes to introduce other receiver signals as reference signals, which can achieve the goal of simple technology and obvious effect. It can be used to network ground signals and share signal resources in the future. Joint suppression of interference targets lay the foundation.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN967.1

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