摘要
全球导航卫星系统（GNSS：Global Navigation Satellite Systems）具有大范围全天候高精度定位测速和定时服务的能力，在国防和国民经济各个领域得到了广泛应用目前，卫星导航系统抗干扰能力较弱，已成为其在复杂战场环境下作战使用的严重限制因素之一，提高卫星导航系统的抗干扰能力是赢得未来导航战的重要保证因此，深入研究和实现复杂电磁环境下的GNSS抗干扰技术，具有非常重要的军事价值
传统统计型抗干扰方法以阵列接收数据协方差矩阵为基础，需要较多快拍数实现对协方差矩阵的估计，一般计算量偏大，工程实现较困难；同时统计型方法假设工作过程中环境稳定，主要适用于平稳环境但实际复杂电磁环境中信号往往是非平稳或时变的，可能导致统计型方法性能下降；为更好地适应非平稳环境，可以使用直接数据域处理方法直接数据域算法相对统计型算法来说，是一种单快拍处理算法，避免了样本协方差矩阵估计等运算本文系统地研究了基于直接数据域的GNSS阵列误差校正干扰抑制子空间跟踪干扰信号波达方向估计以及波束形成等关键理论和算法；在具体工程实践方面完成了相应的算法验证和技术方案实现，对GNSS实时抗干扰设计具有一定参考价值
研究了直接数据域自适应GNSS抗干扰算法提出了改进的最小均方（LMS：Least Mean Square）算法：VS_NLMS算法，具有较好的收敛速度和收敛稳定性；提出了基于VS_NLMS算法的GNSS阵列误差校正方法，对校正前后性能进行了分析比较；对基于VS_NLMS算法的GNSS空时抗干扰处理进行了性能仿真分析；阵列误差校正和干扰抑制都在直接数据域完成，便于时变环境应用
研究了直接数据域子空间跟踪算法及其抗干扰应用通过深入研究数据投影方法（DPM：Data Projection Method）类OJA类子空间跟踪方法的物理意义，提出了一种基于最小空间距离准则的低复杂度子空间跟踪（STSD：Subspace Trackingbased on Subspace Distance）算法，算法复杂度仅有3NL+O(N)，在同类算法中复杂度最低；并对STSD算法在信号子空间跟踪和噪声子空间跟踪中的数值稳定性进行了理论证明和仿真验证，在有限字长条件下，该算法对舍入误差累积不敏感，能保证子空间基的标准正交收敛，算法稳健；对STSD算法应用于GNSS空时抗干扰处理进行了性能仿真分析STSD算法为子空间跟踪算法的发展开拓了新思路，应用于GNSS干扰抑制取得了较好效果
研究了直接数据域相干干扰波达方向（DOA：Direction ofArrival）估计方法提出了两种直接数据域干扰DOA估计方法：基于低复杂度自适应算法得到不同噪声子空间矢量，或基于子空间跟踪方法得到噪声子空间基估计，从而分别构建空间谱，通过谱峰搜索得到干扰DOA估计进而，为了对相干干扰进行DOA估计，分别提出了直接数据取对称共轭向量和直接数据虚拟空间平滑的解相干算法提出的直接数据域相干信号DOA估计算法都不需协方差矩阵估计和特征分解，大大减少了算法计算量，可应用于复杂时变环境
研究了直接数据域GNSS稳健波束形成方法提出了一种基于直接数据域子空间跟踪结合解扩处理和一阶恒模算法的GNSS盲波束形成算法首先通过噪声子空间跟踪投影完成强干扰抑制；然后利用指定卫星PRN（Pseudorandom Noise）码对干扰抑制后的信号进行解扩处理，突出卫星信号；最后结合一阶恒模算法实现对卫星信号的盲波束形成提出的直接数据域稳健波束形成算法复杂度低，易于实时实现；而且算法不需要知道传输的导航符号以及卫星方位，是一种盲自适应波束形成算法并提出了一种多波束形成方式，针对多个卫星信号进行波束形成
研究了适合GNSS抗干扰实现的系统级联结构和模块设计，完成了GNSS抗干扰处理系统应用VS_NLMS算法进行了GNSS空时自适应处理机的设计和实现；基于子空间跟踪结合解扩处理和恒模算法，以及直接数据域DOA估计算法进行了数字多波束GNSS抗干扰系统设计完成了系统模块设计算法验证和功能测试等工作，相关研究成果具有一定的工程实用价值
本文部分相关成果已被用于某型舰载接收机改造某航空炸弹设计定型某新型超高速导弹设计；作为一种重要的抗干扰措施，也已经被用于北斗二代抗干扰接收机系统论证和实现
Global Navigation Satellite Systems (GNSS) have the abilities of providing highprecision positioning, speed and timing service in wide range and all weather. Theyhave been widely applied in the national defense and the national economy. Meanwhile,the weak anti-interference ability is one of the serious restriction factors of GNSSapplying in the complex battlefield environment; and improving the anti-jammingability of GNSS is the important guarantee to win the future navigation warfare. As aresult, to study and realize the technologies of ensuring the reliability for GNSSreceivers in the complex electromagnetic circumstances is of great importance inmilitary field.
The classical statistical anti-jamming methods are based on the covariance matrixof array receiving data. To get the estimate of covariance matrix, a series of snapshotdata are required. And the big amount of calculation brings the difficulties inengineering realizing. Statistical methods assume that the environment is stable, so it isapplied only in the steady environment. But in the actual environment especially in thecomplex electromagnetic environment, the signal is usually unsteady and time-varying,which would lead to the performance degradation with the statistical method. In order tobe better adapted in the non-stationary environment, the algorithms in direct datadomain (DDD) should be proposed and applied. The DDD algorithm is a signalsnapshot processing method, which avoids the statistical operation, such as the samplecovariance matrix estimates. In this thesis, the key and theoretical problems, whichrelate to GNSS array error correction, interference suppression, subspace tracking,estimation of direction of arrival (DOA), as well as beam forming, are systematicallystudied in the direct data domain; The corresponding algorithm validation andimplementation in engineering practice are also investigated.
The GNSS adaptive algorithms belonging to the direct data domain is studied. Theimprovement is emphasis on the stability of the least mean square (LMS) algorithm andits convergence speed. A kind of calibration technique to GNSS array error is proposedin this thesis and the influence of GNSS anti-jamming performance is also analyzed. Asimulation analysis of GNSS space-time processing based on the improved LMSalgorithm is accomplished. All the processing is carried out in direct data domain, whichis convenient in time-varying environmental engineering application.
The subspace tracking algorithms belonging to the direct data domain is studied.Through in-depth study on the physical meaning of data projection method (DPM) andOJA algorithms, the subspace tracking based on subspace distance (STSD) is proposed,which is based on the minimum space distance criterion. The STSD algorithm has thelowest computational complexity of3NL+O(N) in the congener algorithms. The numerical stability theory proof and simulation verification is also carried out for theproposed algorithm in the signal subspace and noise subspace tracking. In finiteprecision conditions, this algorithm is not sensitive to rounding error accumulation, andcan guarantee orthogonal convergence to the subspace base. A simulation analysis ofGNSS space-time processing based on the proposed STSD algorithm is alsoaccomplished. The STSD algorithm exploits a novel view to the development ofsubspace tracking algorithms, and simulation results reveal that it has good performancein GNSS anti-jamming application.
The DOA estimation of coherent signals in direct data domain is studied. First ofall, this thesis proposes two DOA estimation methods. One of the novel approachsconstructs the spatial spectrum by utilizing the steady-state weights from the improvedLMS algorithm; the other constructs the spatial spectrum by utilizing the estimation ofnoise subspace base. Then the DOA estimation of interference signal could be obtainedfrom searching spectral peak. Furthermore, in order to deal with coherent interferencesignals, the symmetric conjugate vector method and the virtual space smooth algorithmin direct data domain are proposed, respectively. The proposed approaches do not needto estimate the source number or the covariance matrix. Also, they do not need theeigendecomposition, meanwhile the computational complexity is greatly reduced, andthe proposed approaches can be applied to complex time-varying environment.
The GNSS robust beamforming method in direct data domain is studied. Amulti-beamforming method, which form beam to each satellite, is proposed. The stronginterference suppression is finished through the noise subspace projection. Then, thedespread processing which uses the designated satellite pseudorandom noise (PRN)code is carried out to outstanding the satellite signal. The blind beamforming methodcombines with the one-order constant modulus (CM) algorithm. The proposed methodis a blind adaptive beamforming algorithm which does not require the information aboutnavigation symbols or satellite orientations. It also adopts the low complexity algorithmin direct data domain, which mitigates the computational consumption of the receiverand guarantees the real time implementation.
A cascaded structure and module design for GNSS anti-jamming are studied andtwo GNSS anti-jamming systems have been implemented. Based on the improved LMSalgorithm, the GNSS space-time adaptive processor is designed and implemented. Amulti-beam GNSS anti-jamming system is also be proposed, which combines thesubspace tracking algorithm, the CM algorithm and the DOA estimation method indirect data domain. Experimental results show that such a cascaded scheme could bringsignal-to-noise-ratio improvement for the space-time processing. The system design,algorithm validation and functional testing are completed, and relevant research resultsare significant in both theory and engineering application.
Partial correlation results of this thesis have been used to a certain type of carrier receiver transformation, aviation bomb finalize the design, a new type of high speedmissile design. In addition, as important anti-jamming measures, they have been used indemonstration and realization of the second generation “beidou” anti-jamming receiversystem.
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