卫星导航接收机干扰及多径抑制方法研究
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摘要
全球卫星导航系统(GNSS)能够提供高精度的全球定位、导航和授时功能，但是用户接收到的信号功率极低，容易受到有意无意的干扰，导致定位精度下降甚至无法定位。同时信号多径是GNSS定位误差的主要来源。自适应阵列是GNSS抗干扰的主要方法之一。但是GNSS信号功率低，导向矢量不易估计，使传统波束形成性能下降，需要不依赖信号导向矢量的波束形成算法。为使接收机获得更好的抗干扰能力，使用空时自适应处理抑制干扰，但是空时自适应处理的时域滤波结构对GNSS信号有影响，需要优化权矢量的时域响应。信号多径导致定位误差，需要抑制多径对接收机的影响。本文围绕GNSS应用中面临的问题，对波束形成抗干扰算法、空时自适应处理对GNSS信号影响及校正和GNSS接收机多径抑制问题进行了研究，主要工作包括：
1.提出了一种无需精确已知GNSS信号导向矢量的干扰抑制方法。针对自适应阵列用于GNSS接收机干扰抑制时精确导向矢量难以获得的问题，基于GNSS信号的自相关性质提出了一种抑制GNSS信号中干扰的波束形成算法。采用GNSS信号多个周期的相关峰值估计相关值中的信号协方差矩阵，使用相关前、后的协方差矩阵在最大化输出信噪比准则下得到最优权。本文算法处理时无需GNSS信号和干扰方向的先验知识。仿真与实测结果表明，与功率倒置方法和SpectralSelf-Coherence Restoral (SCORE)算法相比，本文方法处理后GNSS信号信干噪比获得明显提高。
2. GNSS信号与参考信号的相关函数是接收机中所有处理的输入信号。针对阵列自适应处理对GNSS信号影响这一问题，推导GNSS信号分别经空域自适应和空时自适应处理后与参考信号的相关函数，以此为基础从公式上定性分析了自适应阵列处理对GNSS信号跟踪环路中码跟踪环和载波跟踪环的影响。分析结果表明空域自适应处理对GNSS信号没有影响，而空时自适应处理在抑制干扰的时由于缺少对GNSS信号波形的约束导致信号产生了畸变，造成定位精度下降。考虑到信号畸变是时域滤波结构造成的，分别讨论了空时自适应处理结构中延迟节结构和权矢量对相关函数的影响，并提出了减轻影响的改进结构。最后通过仿真验证了结论。针对传统空时自适应处理对GNSS信号的影响，提出了具有线性相位特性的空时自适应干扰抑制算法。首先求出空时自适应处理结构的等效复FIR滤波器，该滤波器可以准确的描述空时自适应处理对GNSS信号的影响。通过约束等效滤波器的时域响应使之满足线性相位条件，得到了具有线性相位特性空时自适应算法的优化模型。通过转化约束条件求出了优化模型的闭式解。所提算法的计算复杂度与传统方法相近。仿真结果表明，在干扰抑制能力与传统空时自适应算法相近的情况下，所提方法能够明显改善空时自适应处理后GNSS信号的码跟踪性能和载波跟踪性能。
3.针对传统GNSS多径处理算法直接抑制信号多径的问题，提出了一种能在不影响GNSS跟踪精度前提下，利用信号多径的GNSS多径处理算法。首先将信号变换到频域进行积累，然后构造频率冗余字典使用稀疏重构方法估计多径信号参数。基于估计的多径参数，构造参考信号。然后通过在跟踪环路中使用所提参考信号与接收信号相关。所提参考信号能够减轻信号多径对跟踪环路的影响，同时能够增加相关函数峰值。仿真结果表明所提方法能够降低信号多径情况下的码跟踪误差，并且对多径参数估计误差稳健。
Global Navigation Satellite System (GNSS) can provide highly accurate globalpositioning, navigation and timing services. But the received signal power is very low,which is susceptible to intentional and unintentional interferences, resulting inpositioning performance loss and even failed to locate. The multipath signal is also amajor source of GNSS positioning error. Adaptive arrays is one of the importantmethods for GNSS interference suppression. However the GNSS signal power is suchlow that the steering vector is hard to estimate accurately, resulting in the performancedegradation of the classic beamforming algorithms. In order to tackle this problem, thebeamforming algorithm which does not rely on the signal steering vector is needed. Inorder to obtain a better interference suppression performance of the GNSS receivers, thespace-time adaptive processing (STAP) is introduced. Unfortunately, the time domainfiltering structure distorts the GNSS signals, thus the time-domain response of theweight vector should be well designed. Multipath signals cause severe positioning error,the receiver needs to suppress multipath signals. This dissertation focuses on theproblems which are encounted in GNSS applications, involving the interferencesuppression, space-time adaptive processing effects on GNSS signals and multipathmitigation. The main contribution of the work are listed as follows:
1. The accurate steering vector of the GNSS signals which is needed by adaptivealgorithms for interference suppression is hard to obtian. In order to tackle this problem,a novel interference suppression algorithm for GNSS signal is proposed. The spreadingcodes in GNSS signal exhibit strong self-coherence and the correlation matrix of theGNSS signal can be estimated using several peaks of correlation values of receivedsignal and reference signal. The optimum weight is obtained under the maximum SINRcriterion using the covariance matrix of pre-correlation and post-correlation signal. Theproposed algorithm does not need a priori knowledge of the directions of GNSS signals.Simulations and experiments demonstrate that, compared with the power inversionmethod and SCORE algorithm, the proposed algorithm can provide a similarperformance of inference suppression, but the output SINR is significantly increased.
2. The correlation function of the GNSS signals and the reference signal is theinput signals of all processing in GNSS receiver. In order to study the effect of adaptivearray processing on GNSS signals, the correlation function of the output GNSS signalsof spatial adaptive and STAP are derived respectively. The effects of adaptive arrayprocessing on GNSS code tracking loop and carrier tracking loop are analyzed based on the derived correlation funcion. The analysis results show that adaptive spatialprocessing has no effects on GNSS signal, while STAP distorts the GNSS signal due tothe lack of distortion constraint of GNSS signal waveform, resulting in positioningperformance loss. As the distortion of GNSS signals is caused by the time-domainfiltering structures, the effects of delay tap and the weight vector of the space-timeadaptive processing are analyzed respectively. An optimized structure which canmitigate the distortion is proposed. Finally conclusion is verified by simulation. A linearphase space-time adaptive algorithm for interference suppression is proposed in order tomitigate the distortion of GNSS signal which is induced by STAP. First the equivalentcomplex FIR filter of the STAP is derived, which can accurately describe the impact ofspace-time adaptive processing on GNSS signals. By constraining the time domainresponse of the equivalent filter so as to satisfy linear phase conditions, an optimizationmodel of linear phase space-time adaptive algorithm is obtained. The constraints istransformed and combined to obtain a closed-form solution. The computationalcomplexity of the proposed algorithm is similar to that of the classic algorithms.Simulation results show that the proposed algorithm has a similar interferencesuppression capability with the classic space-time adaptive algorithm, while the codetracking performance and carrier tracking performance of GNSS signals aresignificantly improved compared with the classic space-time adaptive algorithms.
3A novel technique for mitigating the multipath-induced code delay estimationerror in GNSS is proposed. In contrast to conventional methods that aim to eliminatemultipath signals, the proposed method exploits them to enhance the direct signalwithout affecting the accuracy of GNSS code delay estimates. To achieve this, coherentaccumulation of the received GNSS signals is first done by transforming the receiveddata into frequency domain and the parameters of multipath signals are then estimatedby sparse reconstruction algorithm. Subsequently, a modified local reference signal isemployed in delay lock loop (DLL) of the GNSS receiver, which mitigates thepseudo-range estimation error and increases the correlation value of direct GNSS signal.Simulation results demonstrate the performance and robustness of the proposed method.
1.提出了一种无需精确已知GNSS信号导向矢量的干扰抑制方法。针对自适应阵列用于GNSS接收机干扰抑制时精确导向矢量难以获得的问题，基于GNSS信号的自相关性质提出了一种抑制GNSS信号中干扰的波束形成算法。采用GNSS信号多个周期的相关峰值估计相关值中的信号协方差矩阵，使用相关前、后的协方差矩阵在最大化输出信噪比准则下得到最优权。本文算法处理时无需GNSS信号和干扰方向的先验知识。仿真与实测结果表明，与功率倒置方法和SpectralSelf-Coherence Restoral (SCORE)算法相比，本文方法处理后GNSS信号信干噪比获得明显提高。
2. GNSS信号与参考信号的相关函数是接收机中所有处理的输入信号。针对阵列自适应处理对GNSS信号影响这一问题，推导GNSS信号分别经空域自适应和空时自适应处理后与参考信号的相关函数，以此为基础从公式上定性分析了自适应阵列处理对GNSS信号跟踪环路中码跟踪环和载波跟踪环的影响。分析结果表明空域自适应处理对GNSS信号没有影响，而空时自适应处理在抑制干扰的时由于缺少对GNSS信号波形的约束导致信号产生了畸变，造成定位精度下降。考虑到信号畸变是时域滤波结构造成的，分别讨论了空时自适应处理结构中延迟节结构和权矢量对相关函数的影响，并提出了减轻影响的改进结构。最后通过仿真验证了结论。针对传统空时自适应处理对GNSS信号的影响，提出了具有线性相位特性的空时自适应干扰抑制算法。首先求出空时自适应处理结构的等效复FIR滤波器，该滤波器可以准确的描述空时自适应处理对GNSS信号的影响。通过约束等效滤波器的时域响应使之满足线性相位条件，得到了具有线性相位特性空时自适应算法的优化模型。通过转化约束条件求出了优化模型的闭式解。所提算法的计算复杂度与传统方法相近。仿真结果表明，在干扰抑制能力与传统空时自适应算法相近的情况下，所提方法能够明显改善空时自适应处理后GNSS信号的码跟踪性能和载波跟踪性能。
3.针对传统GNSS多径处理算法直接抑制信号多径的问题，提出了一种能在不影响GNSS跟踪精度前提下，利用信号多径的GNSS多径处理算法。首先将信号变换到频域进行积累，然后构造频率冗余字典使用稀疏重构方法估计多径信号参数。基于估计的多径参数，构造参考信号。然后通过在跟踪环路中使用所提参考信号与接收信号相关。所提参考信号能够减轻信号多径对跟踪环路的影响，同时能够增加相关函数峰值。仿真结果表明所提方法能够降低信号多径情况下的码跟踪误差，并且对多径参数估计误差稳健。
Global Navigation Satellite System (GNSS) can provide highly accurate globalpositioning, navigation and timing services. But the received signal power is very low,which is susceptible to intentional and unintentional interferences, resulting inpositioning performance loss and even failed to locate. The multipath signal is also amajor source of GNSS positioning error. Adaptive arrays is one of the importantmethods for GNSS interference suppression. However the GNSS signal power is suchlow that the steering vector is hard to estimate accurately, resulting in the performancedegradation of the classic beamforming algorithms. In order to tackle this problem, thebeamforming algorithm which does not rely on the signal steering vector is needed. Inorder to obtain a better interference suppression performance of the GNSS receivers, thespace-time adaptive processing (STAP) is introduced. Unfortunately, the time domainfiltering structure distorts the GNSS signals, thus the time-domain response of theweight vector should be well designed. Multipath signals cause severe positioning error,the receiver needs to suppress multipath signals. This dissertation focuses on theproblems which are encounted in GNSS applications, involving the interferencesuppression, space-time adaptive processing effects on GNSS signals and multipathmitigation. The main contribution of the work are listed as follows:
1. The accurate steering vector of the GNSS signals which is needed by adaptivealgorithms for interference suppression is hard to obtian. In order to tackle this problem,a novel interference suppression algorithm for GNSS signal is proposed. The spreadingcodes in GNSS signal exhibit strong self-coherence and the correlation matrix of theGNSS signal can be estimated using several peaks of correlation values of receivedsignal and reference signal. The optimum weight is obtained under the maximum SINRcriterion using the covariance matrix of pre-correlation and post-correlation signal. Theproposed algorithm does not need a priori knowledge of the directions of GNSS signals.Simulations and experiments demonstrate that, compared with the power inversionmethod and SCORE algorithm, the proposed algorithm can provide a similarperformance of inference suppression, but the output SINR is significantly increased.
2. The correlation function of the GNSS signals and the reference signal is theinput signals of all processing in GNSS receiver. In order to study the effect of adaptivearray processing on GNSS signals, the correlation function of the output GNSS signalsof spatial adaptive and STAP are derived respectively. The effects of adaptive arrayprocessing on GNSS code tracking loop and carrier tracking loop are analyzed based on the derived correlation funcion. The analysis results show that adaptive spatialprocessing has no effects on GNSS signal, while STAP distorts the GNSS signal due tothe lack of distortion constraint of GNSS signal waveform, resulting in positioningperformance loss. As the distortion of GNSS signals is caused by the time-domainfiltering structures, the effects of delay tap and the weight vector of the space-timeadaptive processing are analyzed respectively. An optimized structure which canmitigate the distortion is proposed. Finally conclusion is verified by simulation. A linearphase space-time adaptive algorithm for interference suppression is proposed in order tomitigate the distortion of GNSS signal which is induced by STAP. First the equivalentcomplex FIR filter of the STAP is derived, which can accurately describe the impact ofspace-time adaptive processing on GNSS signals. By constraining the time domainresponse of the equivalent filter so as to satisfy linear phase conditions, an optimizationmodel of linear phase space-time adaptive algorithm is obtained. The constraints istransformed and combined to obtain a closed-form solution. The computationalcomplexity of the proposed algorithm is similar to that of the classic algorithms.Simulation results show that the proposed algorithm has a similar interferencesuppression capability with the classic space-time adaptive algorithm, while the codetracking performance and carrier tracking performance of GNSS signals aresignificantly improved compared with the classic space-time adaptive algorithms.
3A novel technique for mitigating the multipath-induced code delay estimationerror in GNSS is proposed. In contrast to conventional methods that aim to eliminatemultipath signals, the proposed method exploits them to enhance the direct signalwithout affecting the accuracy of GNSS code delay estimates. To achieve this, coherentaccumulation of the received GNSS signals is first done by transforming the receiveddata into frequency domain and the parameters of multipath signals are then estimatedby sparse reconstruction algorithm. Subsequently, a modified local reference signal isemployed in delay lock loop (DLL) of the GNSS receiver, which mitigates thepseudo-range estimation error and increases the correlation value of direct GNSS signal.Simulation results demonstrate the performance and robustness of the proposed method.
引文
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