基于极大似然估计器的GNSS矢量跟踪算法

矢量跟踪是一种将全球导航卫星系统(GNSS)接收机的信号跟踪与导航解算融为一体的跟踪算法。传统的基于矢量延迟/频率锁定环(VDFLL)的跟踪算法普遍采用延迟锁定环(DLL)和锁频环(FLL)鉴别器计算伪距和伪距率偏差观测量,由于锁频环鉴别器存在近似误差和一步延迟效应,在高动态环境下容易造成环路失锁。从直接估计卫星信号特征参数的角度出发,基于中频信号模型构建码相位和载波多普勒的极大似然代价函数,采用非迭代估计算法得到各通道码相位和多普勒频移的估计偏差,转换为卡尔曼滤波器的观测矢量,提出一种基于极大似然估计器(MLE)的矢量跟踪算法。理论分析和仿真结果表明:新算法结合了极大似然估计和矢量跟踪的优点,克服了FLL的延迟效应,与基于VDFLL的矢量环路相比,高动态环境下的跟踪稳定性更好,可以对被遮挡的卫星保持持续的跟踪。     

多径效应对GPS载波相位观测量的影响

推导了ＧＰＳ接收机中多径效应引入的最大载波相位跟踪误差的闭合形式。得到以下结论：当直达信号跟踪误差不超过１码片时,最大载波测相多径误差为１／４周,该值出现在测码伪距多径误差最小的情况下;当直达信号跟踪误差超过或等于１码片时,接收机跟踪多径信号,信号误检发生。     

扩频通信系统伪码相位跟踪环性能研究

在现代通信系统中,对于全数字化扩频接收机来说,由于伪码跟踪环中鉴相器具有非线性特性,所以有可能使扩频通信环路工作在非线性区域。本文分析了一种非相干伪码跟踪环路的线性以及非线性跟踪性能,并得到了环路的收敛域与收敛条件,这些分析结果对环路参数的设计都是至关重要的。     

GPS接收机数字码跟踪环性能研究

建立了伪码捕获和跟踪过程的数学模型;推导出了伪码捕获的检测概率和虚警概率,提出了改进的双Dwell搜索方法;对一阶、二阶、三阶DDLL的动态跟踪性能及输入随机噪声影响进行了定量分析。研究结果表明,双Dwell搜索方法能显著缩短平均捕获时间,应根据不同的系统动态特点,选择不同的环路参数,以优化码跟踪环的特性。     

FFT在高动态扩频信号捕获中的应用

讨论了采用FFT算法实现高动态扩频信号快捕的一种方法。该方法根据帕斯瓦尔定理，以频域多点能量之和作为观测量，对伪码同步和载波多普勒频点位置进行判断，消除了数据符号跳变和栅栏效应对FFT分析的影响。实验结果表明，该方法可以很好地实现高动态扩频信号的捕获，并可以有效地节省硬件资源。     

GPS多径误差特性与抗多径方法

在近距差分ＧＰＳ等高精度定位中，多径干扰已变成了主要误差差源。本文在分析多径干扰源分析的基础上，考虑了天线的多径抑制效应，建立了ＧＰＳ接收机的伪码跟踪与载波同步复合环的等铲数学模型，并分析了多径参数伪以测量 的误差特性，综合了ＧＰＳ抗多径干扰的各种定位方法。     

伪距解除相关法在GPS/SINS紧组合系统中的应用研究

介绍了伪距解除相关法的原理 ,设计了一种加权平均跟踪误差估计器 ,用以估计 GPS接收机码环跟踪误差。研究结果表明 ,与未对伪距测量值进行修正时相比 ,应用伪距解除相关技术可以减小组合系统的导航误差 ,提高系统的导航精度     

基于相位平滑伪距的GNSS时差监测评估

随着全球卫星导航系统进一步的发展和完善,在系统层面上对各个GNSS进行实时时差监测是必要的。为了降低时差监测中伪距观测值的观测噪声及多径误差对时差监测的影响,采用相位平滑伪距的方法对伪距观测值的噪声及多径误差进行平滑,该方法可以实时地对伪距观测值进行处理,并且具有较好的平滑效果。利用平滑后的伪距观测值进行时差监测可以将时差监测值的标准差由2~4ns降低到1~3ns,噪声降低比率平均在20%以上。在与BIPM公布的时差数据相比,GPS-GLONASS实测值也具有较好的一致性,可以满足GNSS时差监测与预报的需求。     

GPS多径信号的自适应滤波估计方法

 研究全球定位系统(GPS)多径信号估计的问题。通过分析自适应滤波器的原理,建立了数字中频信号处理的数学模型,提出一种用自适应滤波实现GPS多径幅度、码相位和载波相位估计的方法。该方法采用不同延迟的伪随机序列对信号进行解扩、解调和累加,得到了作为期望信号的系列自适应滤波相关值。对该方法与其他3种方法进行了理论上的分析比较,得出本方法具有信噪比高、自适应滤波性能好、带有码相位信息和不存在载波模糊度问题等优点。根据各种滤波器算法的特点和本应用的需求,给出了选用递归最小二乘算法实现的方法。通过计算机仿真,验证了提出的方法能够在14 dB的信噪比下,以1个采样间隔的时间延迟分辨率和0.005周的载波相位估计精度估计出GPS L1的多径信号。     

非高斯环境下的GPS自适应多径抑制技术

为解决非高斯环境下的全球定位系统(GPS)信号多径抑制,尤其是短延迟多径抑制问题,推导出一种具有权值修正更新能力的改进最小平均p范数(LMP)算法。该算法通过对权值变化趋势项的预测可有效减小算法的收敛时间,通过对其参数变化影响的理论分析和仿真,证实在所设实验条件下算法的收敛时间最大可减少50%。为在自适应多径参数估计时应对非高斯噪声环境的影响,同时获得更大的处理增益,设计了改进的自适应多径估计方案,将算法应用于方案的权值更新,并对更新后的权值引入均值滤波,仿真证明所提多径抑制方案在非高斯和高斯环境下均能表现出很好的稳定性和有效性。     

Receiver-channel based adaptive blind equalization approach for GPS dynamic multipath mitigation

Aiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square (RLS) algorithm is proposed, which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops. The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; therefore an increase in the number of correlator channels is required compared with conventional GPS receivers. An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response. Then, the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators’ outputs. To demonstrate the capabilities of the proposed approach, this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator, thus simulations under controlled dynamic multipath scenarios can be carried out. Simulation results show that in a dynamic and fairly severe multipath environment, the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase.     

轨道预测辅助GPS载波跟踪技术用于低轨道卫星定位研究

针对低轨道卫星及其特定的运动环境,研究了星载GPS接收机载波跟踪问题。基于卫星轨道可模化、可预测的特性,提出了利用预测卫星轨道计算多普勒频移,并用于辅助载波环路跟踪的新方法。该方法有效地降低了低轨道卫星GPS信号跟踪中的动态,从而在跟踪过程中可以采取降低环路阶数、减小环路带宽、增加预检测积分时间这几种措施来提高环路跟踪弱信号的能力,有助于提高低轨道卫星的定位性能。     

Array shape estimation tracking using active sonar reverberation

This paper concerns the problem of array shape estimation and tracking for towed active sonar arrays, using received reverberation returns from a single transmitted CW pulse. Uniform linear arrays (ULAs) deviate from their nominal geometry while being towed due to ship maneuvers as well as ocean currents. In such scenarios, conventional beamforming performed under the assumption of a ULA can sometimes lead to unacceptably high spatial sidelobes. The reverberation leaking through the sidelobes can potentially mask weak targets in Doppler, especially when the target Doppler is close to that of the mainlobe reverberation and the reverberation-to-target ratio (RTR) is very high. Although heading sensors located along the array can be used to provide shape estimates, they may not be sufficiently available or accurate to provide the required sidelobe levels. We propose an array shape calibration algorithm using multipath reverberation returns from each ping as a distributed source of opportunity. More specifically, a maximum likelihood (ML) array shape calibration algorithm is developed, which exploits a deterministic relationship between the reverberation spatial and Doppler frequencies causing it to be low rank in the space-time vector space formed across a single coherent processing interval (CPI). In this application, a sequence of overlapped CPI length snapshots of duration less than the CW pulse is used. The ML estimates obtained for each snapshot are tracked using a Kalman filter with a state equation corresponding to the water pulley model for array dynamics. Simulations performed using real heading sensor data in conjunction with simulated reverberation suggest that 8-10 dB improvement in sidelobe level may be possible using the proposed array shape tracking algorithm versus an algorithm that uses only the available heading information.     

基于滑动DFT和插值DFT算法的GPS信号载波跟踪方法

 在分析GPS接收机跟踪环路信号特征的基础上,将滑动离散傅里叶变换（DFT）算法和插值DFT频率估计算法相结合,提出一种在频域进行的载波跟踪方法。该方法首先根据捕获时得到的粗略载波频率估计值确定计算DFT值点的范围,然后利用滑动DFT算法计算这部分点的DFT值,最后利用插值DFT频率估计算法估计载波频率,进行跟踪环路中载波频率的更新。该方法计算复杂度低,便于实际应用。仿真结果显示,该方法能够对载波频率正确跟踪,验证了算法的可行性。     

Decorrelation of broadband signals by Toeplitz-Block-Toeplitzstructuring

We propose F-norm of the cross-correlation part of the array covariance matrix as a measure of correlation between the impinging signals and study the performance of different decorrelation methods in the broadband case using this measure. We first show that dimensionality of the composite signal subspace, defined as the number of significant eigenvectors of the source sample covariance matrix, collapses in the presence of multipath and the spatial smoothing recovers this dimensionality. Using an upper bound on the proposed measure, we then study the decorrelation of the broadband signals with spatial smoothing and the effect of spacing and directions of the sources on the rate of decorrelation with progressive smoothing. Next, we introduce a weighted smoothing method based on Toeplitz-block-Toeplitz (TBT) structuring of the data covariance matrix which decorrelates the signals much faster than the spatial smoothing. Computer simulations are included to demonstrate the performance of the two methods     

2-D spatial smoothing for multipath coherent signal separation

The use of two-dimensional spatial smoothing (SS) to increase channel capacity of wireless communications system is discussed, The necessary and sufficient conditions on array configuration for applying SS to multiple signal classification (MUSIC), and adaptive beamforming algorithms are defined and proved, This array must have an orientational invariance structure with an ambiguity free center array, and the number of subarrays must be larger than or equal to the size of the largest group of coherent signals. We also studied the cause of ambiguities in a multipath environment. We found the necessary and sufficient conditions for a three-sensor array manifold to be ambiguity free and identified several higher order ambiguity situations, If an array is also central symmetric, the forward/backward SS (FBSS) can be used to improve the resolution. Finally, we extended our results to the estimation of signal parameters via rotational invariance techniques (ESPRIT). All the predicted results are verified by simulations     

平滑重构稀疏贝叶斯学习测向算法

针对二级嵌套阵列中的紧凑阵元结构易受互耦效应影响的问题,提出了两种不同的嵌套阵列结构改进方法：连续平移嵌套阵列和间隔平移嵌套阵列。通过对原有二级嵌套阵列阵元位置进行调整,形成了两种不同的平移嵌套阵列结构,这两种结构对应的差分共阵均"无孔",并且测向自由度和阵列稀疏度均大于原二级嵌套阵列。针对嵌套阵列的差分共阵测向模型为单测量矢量模型,稀疏贝叶斯学习测向算法复杂度高的问题,提出了平滑重构稀疏贝叶斯学习算法。该算法通过空间平滑重构将单测量矢量模型变为多测量矢量模型,降低了观测矩阵的维度,减小了计算复杂度。算法求解时,通过对变换后的观测矩阵进行奇异值分解,进一步降低了观测矩阵维度,利用稀疏贝叶斯学习算法估计辐射源角度。仿真表明,在信噪比和采样数相同的条件下,该算法收敛速度比单测量矢量稀疏贝叶斯学习（SMV-SBL）算法快,且测向精度高于SMV-SBL算法和空间平滑多重信号分类（MUSIC）算法;存在互耦影响时,两种平移嵌套阵列比原嵌套阵列受互耦影响小。     

GPS code and carrier multipath mitigation using a multiantennasystem

Multipath is a major source of error in high precision Global Positioning System (GPS) static and kinematic differential positioning. Multipath accounts for most of the total error budget in carrier phase measurements in a spacecraft attitude determination system. It is a major concern in reference stations, such as in Local Area Augmentation Systems (LAAS), whereby corrections generated by a reference station, which are based on multipath corrupted measurements, can significantly influence the position accuracy of differential users. Code range, carrier phase, and signal-to-noise (SNR) measurements are all affected by multipath, and the effect is spatially correlated within a small area. In order to estimate and remove code and carrier phase multipath, a system comprising a cluster of five GPS receivers and antennas is used at a reference station location. The spatial correlation of the receiver data, and the known geometry among the antennas, are exploited to estimate multipath for each satellite in each antenna in the system. Generic receiver code and carrier tracking loop discriminator functions are analyzed, and relationships between receiver data, such as code range, carrier phase, and SNR measurements, are formulated and related to various multipath parameters. A Kalman filter is described which uses a combination of the available information from the antennas (receivers) in the multiantenna cluster to estimate various multipath parameters. From the multipath parameters, the code range and carrier phase multipath is estimated and compensated. The technique is first tested on simulated data in a controlled multipath environment. Results are then presented using field data and show a significant reduction in multipath error     

极弱信号环境下GPS位同步和载波跟踪技术

为解决环路未锁定、无法找出正确的导航数据位跳变点时极弱全球定位系统(GPS)信号跟踪问题,通过分析信号跟踪模型和相关器1 ms采样数据特性,将最优路径动态规划算法应用于GPS位同步,并提出基于平方根无迹卡尔曼滤波(SRUKF)和位同步结合的载波联合跟踪算法。建立了适合位同步的SRUKF载波环参数估计模型,针对位同步的实现条件和无相位频率先验信息的情况,将位同步模块提前,研究设计了环路未锁定时串行和并行两种弱信号跟踪方案。位同步跟踪完成后环路采用单独的SRUKF工作方式。实验结果证实该文提出的算法具有较高的数据位边缘检测概率(EDR)和参数估计性能,而无须关心环路是否处于锁定状态,能够对载噪比低至22 dB/Hz的弱信号实现跟踪。     

基于矩阵填充的二维自适应波束形成算法

针对基于矩阵填充的二维自适应波束形成问题,提出一种基于奇异值门限(SVT)的特征分解线性约束最小方差(SVT-ELCMV)算法。首先建立二维自适应波束形成矩阵填充模型,其次验证接收信号矩阵满足零空间性质(NSP),并分析最小可恢复阵元数,最后以SVT算法将稀疏阵列信号恢复为完整信号,并通过修正的特征分解线性约束最小方差(LCMV)形成有效波束。算法解决了稀疏阵列平均副瓣大幅度上升的缺陷,且在平面阵列部分阵元无法正常工作时依然有效。计算机仿真表明:SVT-ELCMV算法可使稀疏阵列具有与完整阵列相同的二维波束形成能力,并可有效抑制干扰信号,验证了算法的有效性和优越性。