扩频通信系统中窄带干扰抑制技术研究
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摘要
直接序列扩频技术以隐蔽性好、保密性强和抗多径衰落等优点在军用和民用领域获得了广泛应用。直接序列扩频系统的处理增益决定了它的干扰容限。当干扰强度超过干扰容限时,需要采取有效的干扰抑制技术确保系统性能。以往研究重点多集中在抗平稳干扰上,论文在上述研究的基础上,不仅深入研究了平稳干扰抑制技术,还深入研究了循环平稳干扰抑制技术,并根据扩频系统抗干扰要求改进了现有的算法和抗干扰滤波技术。
论文首先给出接收机简化的信号模型,通过分析常见窄带干扰的统计特性,建立了干扰的平稳模型和循环平稳模型。
在干扰的平稳模型下,总结和比较了几种干扰估计抵消滤波技术的性能,研究了最小误码率(MBER)准则下最优抑制器的一种盲自适应实现结构,推导了其收敛性能和稳态性能;从特征分析角度研究时域干扰抑制技术,简化了一种基于预测/内插结构的特征相消器、降低了计算量,并推导了一种基于MBER准则的特征相消器,分析了抗干扰性能,采用稳健的最小递归二乘(RRLS)算法实现两种特征相消器;针对RRLS算法存在的缺点,增加了正交化过程、自适应估计维数过程,并结合对角加载技术提出一种改进算法,提高了算法的稳健性和估计精度。
在干扰的循环平稳模型下,给出频移(FRESH)预测和频移内插滤波器的结构,推导出输出信干噪比表达式;在分析循环频率误差存在时FRESH滤波器性能恶化原因的基础上,提出一种可使循环频率估计值逐步收敛到真实值的递归算法,增强了FRESH滤波器的稳健性;研究循环平稳模型下基于MBER准则的最优滤波器,将其转化为最小均方误差准则和约束条件下的最小平均能量输出准则下的最优滤波器,导出了基于循环平稳特性的RLS和BRLS自适应算法;同时针对其固有缺点,采用逆正交三角分解加以克服,给出了算法流程、权矢量递归表达式以及相应的脉动阵列。
深入研究了多级维纳滤波器(MWF)的特性,简化了Lanczos-MWF,显著降低了计算量,将MWF应用于循环平稳模型下的干扰抑制,构建了两类基于频移结构的低秩自适应干扰抑制器;分析了Krylov子空间与干扰子空间的等价关系,利用求Krylov子空间的快速算法来构建干扰子空间,提出一种基于Krylov子空间的特征相消器;充分利用已知扩频码信息,将MWF前向递归和RLS算法相结合,提出了一种Krylov-RLS算法,仿真结果表明:相对RLS算法,该算法具有更小的计算量、更好的抗干扰性能。
Direct Sequence Spread Spectrum (DSSS) communication systems have been widely employed in civilian and military fields, for their unique features such as multiple accessing capability, low probability of intercept transmission and multipath rejection etc. Even though DSSS communication systems are inherently robust to the effects of narrow band interference, they have been shown that the use of additional processing aimed at interference suppression can result in substantial performance improvement. In the past thirty years,many researches are focused on stationary narrowand interference suppression techniques in DSSS communication systems. In this dissertation ,not only the stationary narrowband interference suppression technologies, but also the cyclostationary narrowband interference suppression technologies were studied. The improvement on algorithms and narrowband interference suppression technologies was performed to make them feasible for practical realization.
A simplified signal model of receiver was given in this dissertation. Then through analyzing the statistical character of interference, this dissertation built up the stationary model and cyclostationary model of interference.
Based on stationary model of interference, first, the suppression performances of different time domain interference suppression techniques were summed up and compared. Second, a kind of blind adaptive algorithm of minimum bit error ratio (MBER) receiver was discussed., and its stability performance was discussed. Finally, a different approach of time domain interference suppression was studied by the eigenanalysis of the receiving data. An eigencanceler based on predictor/interpolation filter was simplified; it reduces computational complexity greatly. A new MBER eigencanceler was deduced and its suppression performance was analyzed. A subspace tracking method-Robust Recursive Least Square (RRLS) algorithm implements these two eigencancelers. Aiming at the shortcoming of the RRLS algorithm, an improved algorithm was proposed. It added the steps of eigenvector orthogonalization,rank estimating adaptively and diagonal loading technique. The improved algorithm become more stable and its estimation ranks more precisely,when interference is strong.
Based on cyclostationary model of interference, the dissertation gived the structure of the linear frequency shift (FRESH) predictor/interpolation filter and deduced their output SINR. When there was a cyclic frequency error (CFE) of the desired signal, The FRESH filter geted severe performance degradation. A recursive algorithm of cyclic frequency was proposed. It makes the estimative value to converge to the true one gradually. So it can largely depress the sensitivity of frequency shift filter to CFE. On cyclostationary property of interference, a suppressor optimized in the MBER criterion was studied. It was changed into the optimum suppressor in the MMSE criterion and the constrained MMOE criterion. These two optimum suppressors could be completed by two RLS algorithm. This dissertation called them Cyclo (cyclostationary-based)-RLS and Cyclo-BRLS algorithm respectively. These two adaptive algorithms had many problems. The IQR decomposition was used to overcome them. The systolic arrays of IQR decomposition for parallel implementation of these adaptive algorithms were designed.
The Principle of reduce rank based on multistage wiener filter (MWF) had been analyzed. Then a MWF based on Lanczos method was simplified. Its computational cost is less than before. Based on cyclostationary model, a MWF is used for interference suppression ,which has low computational complexity and good performance.It had been proved that the Krylov subspace equal the interference subspace on some conditions. The method which was used to get orthogonal vector of Krylov subspace could be used to get interference subspace. So a new eigecanceler based on Krylov subspace was proposed. Using PN code sufficiently, a new algorithm which combined the forward recursive steps of MWF with RLS algorithm was proposed. It has lower computational complexity and better suppression performance than RLS algorithm.
论文首先给出接收机简化的信号模型,通过分析常见窄带干扰的统计特性,建立了干扰的平稳模型和循环平稳模型。
在干扰的平稳模型下,总结和比较了几种干扰估计抵消滤波技术的性能,研究了最小误码率(MBER)准则下最优抑制器的一种盲自适应实现结构,推导了其收敛性能和稳态性能;从特征分析角度研究时域干扰抑制技术,简化了一种基于预测/内插结构的特征相消器、降低了计算量,并推导了一种基于MBER准则的特征相消器,分析了抗干扰性能,采用稳健的最小递归二乘(RRLS)算法实现两种特征相消器;针对RRLS算法存在的缺点,增加了正交化过程、自适应估计维数过程,并结合对角加载技术提出一种改进算法,提高了算法的稳健性和估计精度。
在干扰的循环平稳模型下,给出频移(FRESH)预测和频移内插滤波器的结构,推导出输出信干噪比表达式;在分析循环频率误差存在时FRESH滤波器性能恶化原因的基础上,提出一种可使循环频率估计值逐步收敛到真实值的递归算法,增强了FRESH滤波器的稳健性;研究循环平稳模型下基于MBER准则的最优滤波器,将其转化为最小均方误差准则和约束条件下的最小平均能量输出准则下的最优滤波器,导出了基于循环平稳特性的RLS和BRLS自适应算法;同时针对其固有缺点,采用逆正交三角分解加以克服,给出了算法流程、权矢量递归表达式以及相应的脉动阵列。
深入研究了多级维纳滤波器(MWF)的特性,简化了Lanczos-MWF,显著降低了计算量,将MWF应用于循环平稳模型下的干扰抑制,构建了两类基于频移结构的低秩自适应干扰抑制器;分析了Krylov子空间与干扰子空间的等价关系,利用求Krylov子空间的快速算法来构建干扰子空间,提出一种基于Krylov子空间的特征相消器;充分利用已知扩频码信息,将MWF前向递归和RLS算法相结合,提出了一种Krylov-RLS算法,仿真结果表明:相对RLS算法,该算法具有更小的计算量、更好的抗干扰性能。
Direct Sequence Spread Spectrum (DSSS) communication systems have been widely employed in civilian and military fields, for their unique features such as multiple accessing capability, low probability of intercept transmission and multipath rejection etc. Even though DSSS communication systems are inherently robust to the effects of narrow band interference, they have been shown that the use of additional processing aimed at interference suppression can result in substantial performance improvement. In the past thirty years,many researches are focused on stationary narrowand interference suppression techniques in DSSS communication systems. In this dissertation ,not only the stationary narrowband interference suppression technologies, but also the cyclostationary narrowband interference suppression technologies were studied. The improvement on algorithms and narrowband interference suppression technologies was performed to make them feasible for practical realization.
A simplified signal model of receiver was given in this dissertation. Then through analyzing the statistical character of interference, this dissertation built up the stationary model and cyclostationary model of interference.
Based on stationary model of interference, first, the suppression performances of different time domain interference suppression techniques were summed up and compared. Second, a kind of blind adaptive algorithm of minimum bit error ratio (MBER) receiver was discussed., and its stability performance was discussed. Finally, a different approach of time domain interference suppression was studied by the eigenanalysis of the receiving data. An eigencanceler based on predictor/interpolation filter was simplified; it reduces computational complexity greatly. A new MBER eigencanceler was deduced and its suppression performance was analyzed. A subspace tracking method-Robust Recursive Least Square (RRLS) algorithm implements these two eigencancelers. Aiming at the shortcoming of the RRLS algorithm, an improved algorithm was proposed. It added the steps of eigenvector orthogonalization,rank estimating adaptively and diagonal loading technique. The improved algorithm become more stable and its estimation ranks more precisely,when interference is strong.
Based on cyclostationary model of interference, the dissertation gived the structure of the linear frequency shift (FRESH) predictor/interpolation filter and deduced their output SINR. When there was a cyclic frequency error (CFE) of the desired signal, The FRESH filter geted severe performance degradation. A recursive algorithm of cyclic frequency was proposed. It makes the estimative value to converge to the true one gradually. So it can largely depress the sensitivity of frequency shift filter to CFE. On cyclostationary property of interference, a suppressor optimized in the MBER criterion was studied. It was changed into the optimum suppressor in the MMSE criterion and the constrained MMOE criterion. These two optimum suppressors could be completed by two RLS algorithm. This dissertation called them Cyclo (cyclostationary-based)-RLS and Cyclo-BRLS algorithm respectively. These two adaptive algorithms had many problems. The IQR decomposition was used to overcome them. The systolic arrays of IQR decomposition for parallel implementation of these adaptive algorithms were designed.
The Principle of reduce rank based on multistage wiener filter (MWF) had been analyzed. Then a MWF based on Lanczos method was simplified. Its computational cost is less than before. Based on cyclostationary model, a MWF is used for interference suppression ,which has low computational complexity and good performance.It had been proved that the Krylov subspace equal the interference subspace on some conditions. The method which was used to get orthogonal vector of Krylov subspace could be used to get interference subspace. So a new eigecanceler based on Krylov subspace was proposed. Using PN code sufficiently, a new algorithm which combined the forward recursive steps of MWF with RLS algorithm was proposed. It has lower computational complexity and better suppression performance than RLS algorithm.
引文
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