GNSS空域抗干扰算法研究及FPGA实现

发布时间：2018-01-10 04:21

本文关键词：GNSS空域抗干扰算法研究及FPGA实现　出处：《重庆大学》2016年硕士论文　论文类型：学位论文

更多相关文章： GNSS 波束形成 抗干扰 FPGA

【摘要】：全球导航卫星系统(Global Navigation Satellite System,GNSS)是一种具有全能性、全天候、连续性和实时性的无线电导航定位系统,能够提供高精度的导航、定位和授时信息,其应用涉及到国民经济和社会发展的各个领域,已经成为全球发展最快的信息产业之一。但卫星信号到达地面的微弱性使接收机极易受到干扰。GNSS抗干扰技术研究显得尤为重要。传统的时域和频域滤波能够有效抑制少量窄带干扰,但无法对付多个窄带干扰和宽带干扰。而波束形成技术通过对阵列天线上的各阵元加权调整方向图,使方向图的主瓣对准期望信号方向,而在干扰方向形成零陷或者旁瓣,达到抑制多个窄带干扰和宽带干扰的目的。本文围绕GNSS空域抗干扰算法及硬件实现展开研究,主要研究内容如下:首先,分析了导航卫星系统易受干扰的原因,介绍了阵列信号模型、波束形成原理、最优波束形成准则和自适应波束形成算法等波束形成基本理论。重点分析对比了常用的最优波束形成准则和自适应波束形成算法,并深入研究了最小均方(Least Mean Square,LMS)算法的稳态误差、步长因子、收敛速度之间的关系。其次,研究了最小方差无畸变响应(Minimum Variance Distortionless Response,MVDR)波束形成算法和功率倒置(Power Inversion,PI)算法。针对MVDR算法必须知道卫星方位以及传统功率倒置算法对弱干扰的抑制效果不佳,提出了改进的功率倒置算法。仿真验证了该算法无论在抗干扰还是干扰测向性能上均优于传统的功率倒置算法,但需要进行特征分解,运算复杂,不利于现场可编程器件(Field-Programmable Gate Array,FPGA)实现。仿真分析了传统功率倒置三种不同的自适应算法,发现LMS算法采用合适的步长因子,可以达到与其他自适应算法一样的抗干扰效果,并且复杂度较低,易于硬件实现。因此,选择功率倒置自适应LMS算法进行FPGA实现。最后,针对功率倒置自适应LMS算法,搭建了GNSS空域抗干扰系统。对系统中数字自动增益控制(Automatic Gain Control,AGC)、同相正交(In-phase and Quadrature,IQ)变换、抗干扰和干扰测向等重要模块,进行MATLAB仿真、FPGA实现和Modelsim功能验证,分析了整个系统资源使用情况,并对系统进行硬件测试。硬件测试验证了系统抗干扰和干扰测向功能的准确性,且所用资源符合要求。
[Abstract]:The Global Navigation Satellite system (GNSS) is an all-around, all-weather system. Continuous and real-time radio navigation and positioning system can provide high-precision navigation, positioning and timing information, and its application relates to various fields of national economic and social development. It has become one of the fastest-growing information industries in the world, but the weak arrival of satellite signals to the ground makes it particularly important to study the anti-jamming technology of receiver. Traditional time-domain and frequency-domain filtering. Can effectively suppress a small number of narrowband interference. However, it can not deal with multiple narrowband interference and wideband interference, and beamforming technology can adjust the direction of the desired signal by weighting the array elements on the array antenna, so that the main lobe of the pattern can be aligned to the direction of the desired signal. In order to suppress multiple narrowband interference and wideband interference, zero trapping or sidelobe is formed in the interference direction. This paper focuses on the anti-jamming algorithm and hardware implementation in GNSS spatial domain. The main research contents are as follows: firstly, the causes of the interference of navigation satellite system are analyzed, and the array signal model and the principle of beamforming are introduced. The basic theory of beamforming such as optimal beamforming criterion and adaptive beamforming algorithm is analyzed and compared with the conventional optimal beamforming criterion and adaptive beamforming algorithm. The relationship among steady-state error, step size factor and convergence rate of the least mean square Mean squared LMS algorithm is studied. The minimum variance Variance Distortionless Response is studied. MVDR beamforming algorithm and power inversion power Inversion. In view of the MVDR algorithm, we must know that the azimuth of satellite and the traditional power inversion algorithm are not effective to suppress the weak interference. An improved power inversion algorithm is proposed. The simulation results show that the proposed algorithm is superior to the traditional power inversion algorithm in both anti-interference and interference direction finding performance, but it needs to be decomposed and the operation is complex. It is unfavorable to Field-Programmable Gate Array. Three different adaptive algorithms for power inversion are simulated and analyzed. It is found that the LMS algorithm can achieve the same anti-jamming effect as other adaptive algorithms by using the appropriate step size factor. And the complexity is low, easy to implement the hardware. Therefore, select the power inversion adaptive LMS algorithm for FPGA implementation. Finally, for the power inversion adaptive LMS algorithm. The GNSS anti-jamming system in airspace is built. The automatic Gain control system is used to control the digital gain in the system. In-phase and QuadratureIQ) transformation, anti-jamming and direction-finding are simulated by MATLAB. FPGA implementation and Modelsim function verification, analysis of the use of the system resources, and the system hardware testing, hardware testing to verify the system anti-jamming and interference direction finding function accuracy. And the resources used meet the requirements.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN967.1

【相似文献】