【摘要】：全球?qū)Ш叫l(wèi)星系統(tǒng)(Global Navigation Satellite System，GNSS)可以在全球范圍內(nèi)提供全天候的定位、測速和授時業(yè)務(wù)。然而在其被廣泛應(yīng)用的同時，其潛在的風(fēng)險也引起了關(guān)注。欺騙式干擾攻擊通過轉(zhuǎn)發(fā)或者再生的方式偽造的干擾信號，誤導(dǎo)接收機定位授時。本課題針對GNSS的欺騙式干擾，提出基于分塊粒子濾波解算的改進型RAIM(Receiver Autonomous Integrity Monitoring)抗干擾方案，其在提高定位授時精度的同時，還可以有效地消除干擾信號的影響。 首先，本文對GNSS接收機解算的基本原理和最小二乘解算的理論基礎(chǔ)進行介紹。接收機根據(jù)測得的偽距和偽距變化率，以及從星歷中獲知的衛(wèi)星位置信息和速度信息，可以建立一個關(guān)于自身位置和速度信息的非線性方程組，用以定位和測速解算。經(jīng)典的最小二乘解算算法借助牛頓迭代使非線性方程組線性化，然后利用最小二乘法實現(xiàn)對位置與速度的估計。 為了提高GNSS接收機的定位解算精度，本文將粒子濾波引入到導(dǎo)航解算流程，并根據(jù)實際情況提出一種可以進一步提高解算精度的分塊粒子濾波解算算法。粒子濾波借助蒙特卡洛模擬實現(xiàn)對期望變量概率密度函數(shù)的近似估計，從而實現(xiàn)遞推貝葉斯濾波，是一種非參數(shù)化的近似最優(yōu)非線性濾波方法�；诹Ｗ訛V波的解算算法，可以提供比最小二乘法更高的定位、測速和授時精度。而后本文提出的分塊粒子濾波解算算法，將傳統(tǒng)粒子濾波算法的位置估計和速度估計分離，降低狀態(tài)矢量和粒子的維度，如此可以在粒子數(shù)量不變的條件下，，使當(dāng)前粒子更好地覆蓋狀態(tài)矢量空間，進而提高解算精度。 最后，針對GNSS面臨的欺騙式干擾威脅，提出一種基于分塊粒子濾波解算的改進型RAIM抗干擾方案。無論是轉(zhuǎn)發(fā)式還是產(chǎn)生式欺騙干擾，其能夠誤導(dǎo)定位的主要原因都是干擾信號所攜帶的附加偽距；根據(jù)附加偽距的不同特征，可以將干擾場景分為偽距緩變場景和偽距跳變場景，每種場景下又包含單星干擾和多星干擾兩種情況。通過分析不同場景、不同干擾衛(wèi)星數(shù)量和不同模式的干擾攻擊對觀測矢量和定位誤差的影響，提出一種改進型RAIM的抗欺騙式干擾方案。該方案利用觀測矢量的模值進行干擾攻擊檢測，同時利用觀測矢量和殘余矢量之間的線性相關(guān)性實現(xiàn)干擾衛(wèi)星的識別。從仿真結(jié)果可知，本文提出的改進型RAIM可以有效地檢測和識別欺騙式干擾，而包含有改進型RAIM的分塊粒子濾波解算算法可以在干擾攻擊時，依然輸出正確的定位結(jié)果，這也證明了本文提出的GNSS抗欺騙式干擾算法的有效性。
[Abstract]:GNSS (Global Navigation Satellite system (Global Navigation Satellite) can provide all-weather positioning, velocimetry and timing services around the world. However, while it is widely used, its potential risks have attracted much attention. Spoofed jamming attacks mislead the receiver by forgery of jamming signals by forwarding or reproducing them. Aiming at the deceptive interference of GNSS, an improved RAIM (Receiver Autonomous Integrity Monitoring) anti-jamming scheme based on block particle filter solution is proposed in this paper. It can improve the accuracy of location timing and eliminate the influence of interference signal at the same time. Firstly, the basic principle of GNSS receiver and the theoretical basis of least square solution are introduced. According to the measured pseudo-range and pseudo-range rate, and the satellite position information and velocity information obtained from the ephemeris, the receiver can establish a nonlinear system of equations about its position and velocity information, which can be used to locate and calculate the velocity measurement. The classical least square algorithm linearizes the nonlinear equations by Newton iteration, and then estimates the position and velocity by using the least square method. In order to improve the positioning accuracy of GNSS receiver, the particle filter is introduced into the navigation solution flow, and a block particle filter algorithm which can further improve the accuracy of the algorithm is proposed according to the actual situation. Particle filter is a non-parameterized approximate optimal nonlinear filtering method by using Monte Carlo simulation to realize approximate estimation of probability density function of expected variables and to realize recursive Bayesian filtering. The algorithm based on particle filter can provide higher accuracy of localization, velocity measurement and timing than the least square method. Then the partitioned particle filter algorithm proposed in this paper separates the position estimation from the velocity estimation of the traditional particle filter algorithm to reduce the state vector and particle dimension, so that the number of particles can not be changed. The state vector space is better covered by the current particle, and the accuracy of the solution is improved. Finally, an improved RAIM anti-jamming scheme based on block particle filter is proposed for the spoofed jamming threat faced by GNSS. Whether forwarding or producing spoofing interference, the main reason why it can mislead the location is the additional pseudo-range carried by the jamming signal; according to the different characteristics of the additional pseudo-range, The jamming scene can be divided into pseudo-range slow-varying scene and pseudo-range jump scene, and each scenario includes two kinds of single-star interference and multi-star interference. By analyzing the effects of different scenes, different number of jamming satellites and different modes of jamming attack on the observation vector and positioning error, an improved anti-deception jamming scheme of RAIM is proposed. In this scheme, the interference attack is detected by the mode value of the observation vector, and the linear correlation between the observation vector and the residual vector is used to identify the jamming satellite. The simulation results show that the proposed improved RAIM can effectively detect and identify spoofed interference, while the block particle filter algorithm with improved RAIM can still output correct localization results during interference attack. This also proves the effectiveness of the GNSS anti-deception algorithm proposed in this paper.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN96.1

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相關(guān)期刊論文 前2條

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本文編號：2188035