一种SINS/GPS深组合导航系统技术问题分析

为了满足高动态用户及强干扰条件下的应用需求,提出了一种基于卫星信号矢量跟踪的SINS/GPS深组合导航方法,设计了基于FPGA硬件平台的实施方案。利用组合卡尔曼滤波器反馈回路取代了传统接收机中独立、并行的跟踪环路,能够同时完成所有可视卫星信号的跟踪和导航信息处理;通过矢量跟踪算法对所有可视卫星信号进行集中处理,能够增强跟踪通道对信号载噪比变化的适应能力,从而提高接收机在强干扰或信号中断条件下的跟踪性能;根据SINS导航参数和星历信息推测GPS伪码相位和多普勒频移等参数,用以辅助卫星信号的捕获和跟踪,能够大大缩短接收机的搜索捕获时间,并增强接收机在高动态条件下的跟踪性能。基于矢量跟踪的深组合方法不仅在GPS信号短暂中断期间,能够保证系统的导航精度和可靠性,而且在强干扰环境中能够维持较好的伪码相位和载波频率跟踪性能。     

一种改进的GNSS／INS非相干深组合导航

针对GNSS／INS非相干深组合导航中通道滤波器状态模型中信号幅值估测不准而导致跟踪环路观测噪声较大的问题,提出了一种改进的GNSS／INS非相干深组合导航方法。该方法通过去除通道滤波器中信号幅值状态变量,增加载波相位变化率加速度误差,重新设计了通道滤波器数学模型。仿真结果表明：相比于传统的非相干深组合导航方法,这种滤波器的跟踪性能与导航精度有了进一步提高。     

超紧组合中不同精度IMU对GNSS信号跟踪性能的提升

详细推导了惯性测量单元(IMU)精度与全球导航卫星系统(GNSS)接收机信号跟踪环路误差之间的数学模型,分析了IMU辅助的高动态载波跟踪环路误差精度,比较了不同精度IMU辅助GNSS信号捕获性能,证明了分析推导的正确性和合理性,指出了惯性卫星超紧组合导航系统对IMU的精度要求。     

基于软件接收机的GNSS/INS深组合导航算法研究

深组合导航系统将导航参数估计与GNSS卫星信号跟踪融合在一起,将相关器的输出I/Q信息作为GNSS/INS组合导航kalman滤波器的观测量,提高系统的导航精度、抗干扰性和动态性能。利用GNSS软件接收机方便处理基带信号的优势进行深组合导航算法研究,推导了深组合kalman滤波器的观测方程。仿真结果表明:在高动态条件下,深组合导航系统的导航精度明显优于紧组合导航系统的导航精度,位置误差稳定在2m范围内,速度误差稳定在0.04m/s内。     

FPLL载波跟踪环仿真及高动态GPS信号测试

针对高动态环境下普通GPS接收机跟踪环路容易失锁的问题,考虑到锁频环动态性能好、锁相环跟踪精度高的特点,实现了二阶锁频环辅助三阶锁相环的载波跟踪环(FPLL)。根据FPLL结构原理和误差分析理论,提出了一种FPLL环路的码相位和载波相位精度分析方法。借助GPS软件接收机平台,在Matlab环境下仿真实现了FPLL载波跟踪环,并利用Spirent GSS7700仿真器采集高动态GPS模拟信号对FPLL环路进行了测试。测试结果和精度分析表明,在导航信号的载噪比为40dB-Hz,加速度为26g,加加速度为9g/s的条件下,该高动态跟踪环路能够达到码相位1.31m(1σ),载波相位为4.24×10-3 m/s(1σ)的跟踪精度。     

高动态宽带信号码跟踪方法仿真分析

针对高动态场景,单独的码环路很难实现跟踪,由于高动态载波跟踪的算法很成熟,通常应用载波跟踪结果对码环路进行辅助,针对窄体制信号,这种方法可以帮助消除码环的动态误差,但对宽体制信号来说,辅助力度减小。从高动态宽带信号码跟踪误差门限以及跟踪精度入手,分析了单独码跟踪算法的易失锁性,理论和仿真验证应用高动态载波跟踪结果辅助码跟踪算法的有效性,且具有高的跟踪精度。这为导航接收机的跟踪算法提供了理论依据。     

基于容错型联邦强跟踪滤波的多星座组合导航算法研究

在多星座组合导航应用于高动态场景时,由于受加速度变化范围大、动态噪声和观测噪声难以准确预测等因素影响,常规联邦滤波估计精度将会严重下降甚至发散。针对这一问题,提出将强跟踪滤波算法应用到容错型联邦滤波器中,构成容错型联邦强跟踪滤波器。对COMPASS/GPS/GLONASS组合导航系统进行的仿真结果表明:该算法设计灵活,容错性强,对高动态目标有较强的跟踪能力,能够显著提高导航定位的精度和可靠性。同时,由于组合应用了无重置联邦滤波结构和渐消矩阵一步次优算法、残差χ2检验算法等实用算法,使得该算法整体计算量适中,易于实现,具有一定的工程实用价值。     

一种组合导航的直接法滤波算法

提出了一种基于直接法无迹卡尔曼粒子滤波的组合导航系统滤波方法。以惯性导航系统参数和平台误差角作为系统状态,惯导力学编排方程及姿态误差方程作为系统状态方程,卫星导航接收机输出的导航信息作为观测值,采用粒子滤波方法对导航参数进行估计。仿真结果表明,无迹卡尔曼粒子滤波算法可简化滤波参数的调整过程,有效地解决了系统非线性复杂性问题、简化了滤波过程并提高了定位精度。     

基于卡尔曼滤波的GPS高动态载波跟踪环路设计

针对高动态环境会使接收机接收信号载频上产生很大的多普勒频移及其变化率,普通的GPS载波跟踪环无法保证可靠的跟踪等问题,通过综合分析传统的二阶叉积自动频率控制环(CPAFC)辅助三阶锁相环(PLL)的高动态载波跟踪环路,以及卡尔曼滤波器在动态跟踪中的优势与劣势,该文设计了一种基于卡尔曼滤波的二阶CPAFC辅助三阶PLL的GPS高动态载波跟踪环路。通过仿真分析证明,新的环路能更好地适应动态性,整体跟踪性能更好;并且在信噪比较低的情况下,环路优势更明显。     

抗干扰型卫星导航接收机中本地载波优化技术

载波数字振荡器(NCO)是导航接收机中对接收信号进行载波剥离处理的关键部分. 在接收机的基带数字信号处理模块中,NCO通过量化位宽和地址字长分别对本地载波信号的幅值和频率进行量化,即通过存储器数据的位宽和深度设计本地载波. 在给定输入信号/干扰动态范围下,根据本地载波的特点,优化设计了载波NCO中只读存储器(ROM)的幅值量化位宽和地址字长,使其适应实际工程需求,在保证信噪比(SNR)损耗和频率误差的条件下避免了本地载波存储的冗余. 实验结果表明:从需求出发设计导航接收机本地载波的最优位宽和深度,可保证数字下变频SNR损耗小于0.1 dB,本地载波实际输出频率相对误差小于0.1%,且最优位宽和深度小于优化前,减小了存储资源占用率,有效地提高了本地载波输出信号在动态信号和干扰下的适应性.      

基于GPS软件接收机的SINS／GPS紧组合系统仿真

为了系统验证SINS／GPS紧组合系统的性能,基于GPS软件接收机,进行了仿真系统构建。仿真系统由轨迹发生器、GPS中频信号模拟器、IMU信号模拟器、GPS软件接收机、SINS导航解算模块、组合滤波算法和导航性能分析模块等部分构成,其中详细设计了GPS软件接收机中的捕获和跟踪算法、SINS解算以及基于伪距和伪距率的组合滤波算法。仿真结果表明：紧组合导航系统收敛性较好,能够一定程度上抑制惯导系统误差的积累,有较好的导航性能。设计的该系统满足紧组合导航系统性能验证的需要,也为后续的超紧组合研究奠定了良好的基础。     

北斗二代／SINS组合导航系统研究

将伪距、伪距率组合方法应用于北斗二代卫星／SINS组合导航系统,利用卫星系统的星历数据与SINS给出的位置、速度计算出相应的伪距和伪距率,然后与接收的伪距和伪距率相比较得出误差作为量测值,通过卡尔曼滤波器估计卫星定位系统和SINS的误差量,从而实现系统的校正。建立了组合导航系统的状态模型和量测模型,仿真实验表明,该组合模式可得到很好的导航精度。     

Use of a reduced IMU to aid a GPS receiver with adaptive tracking loops for land vehicle navigation

A reduced inertial measurement unit (IMU) consisting of only one vertical gyro and two horizontal accelerometers or three orthogonal accelerometers can be used in land vehicle navigation systems to reduce volume and cost. In this paper, a reduced IMU is integrated with a Global Positioning System (GPS) receiver whose phase lock loops (PLLs) are aided with the Doppler shift from the integrated system. This approach is called tight integration with loop aiding (TLA). With Doppler aiding, the noise bandwidth of the PLL loop filters can be narrowed more than in the GPS-only case, which results in improved noise suppression within the receiver. In this paper, first the formulae to calculate the PLL noise bandwidth in a TLA GPS/reduced IMU are derived and used to design an adaptive PLL loop filter. Using a series of vehicle tests, results show that the noise bandwidth calculation formulae are valid and the adaptive loop filter can improve the performance of the TLA GPS/reduced IMU in both navigation performance and PLL tracking ability.     

State transformation extended Kalman filter for GPS/SINS tightly coupled integration

Extended Kalman filter (EKF) is a widely used estimator for integrated navigation systems, and it works well in general situations. However, in adverse conditions such as partially observable environments and highly dynamic maneuvers, the performance of the traditional EKF-based strap-down inertial navigation system (SINS)/GPS integrated navigation system is easily to be affected by the dynamic changes of the specific force, thus leading to the problem of error covariance inconsistency. Though the inconsistency problem can be overcome to some extent if the system matrix, the states and the error covariance matrix are propagated as fast as possible in the SINS calculation rate, the problem cannot be fully solved. State transformation extended Kalman filter (ST-EKF) mechanization, with a new converted velocity error model for the SINS, is proposed, which can also be used to solve the inconsistency problem. In the ST-EKF, the specific force vector in the system error model is replaced by the nearly constant gravity vector for local navigation. Since the propagation and the updating of the ST-EKF can be executed simultaneously in the updating interval, the computation cost is greatly reduced compared with the traditional EKF. Experiments for the GPS/SINS tightly coupled navigation, including linear vibration Monte Carlo test and an unmanned aerial vehicle flight test, are implemented to evaluate the performance of the proposed ST-EKF. The results show that the proposed ST-EKF has superior performance to the traditional EKF, especially in partially observable situations.     

Modeling and verifying the impact of time delay on INS-aided GNSS PLLs

The timing error between global navigation satellite system (GNSS) and inertial navigation system (INS) processes limits the integration performance in GNSS/INS integrated systems. In a deeply coupled system, this timing error affects not only the integrated navigation solution, but also the GNSS signal tracking. We propose a time-domain model of INS-aided second-order phase-locked loops (PLLs) in consideration of the INS aiding delay, and analyze the effect of INS aiding delay on the tracking errors in details. In addition, an integrated hardware deeply coupled system platform was developed to verify the impact of time delay on INS-aided PLLs. Simulation and field vehicles testing results demonstrate that the tracking error of the INS-aided PLL caused by aiding delay increases with the lengthening of the delay time, the compression of the bandwidth, and the increase in the acceleration. Testing results verify the proposed model.     

Performance of GPS and GPS/SINS navigation in the CE-5T1 skip re-entry mission

A CE-5T1 spacecraft completed a high-speed skip re-entry to the earth after a circumlunar flight on October 31, 2014. In addition to the strapdown inertial navigation system (SINS), a lightweight GPS receiver with rapid acquisition was developed as a navigation sensor in the re-entry capsule. The GPS receiver effectively solved the poor accuracy problem of long-term navigation using only the SINS. In contrast to ground users and low-earth-orbit spacecraft, numerous factors, including high altitude and kinetic characteristics in high-speed skip re-entry, are important for GPS positioning feasibility and were presented in accordance with the flight data. GPS solutions started at nearly 4900 km orbital altitude during the phases of re-entry process. These solutions were combined by an inertial measurement unit in a loosely coupled integrated navigation method and SINS navigation initialization. A simplified GPS/SINS navigation filter for limited resources was effectively developed and implemented on board for spacecraft application. Flight data estimation analyses, including trajectory, attitude, position distribution of GPS satellite, and navigation accuracy, were presented. The estimated accuracy of position was better than 42 m, and the accuracy of velocity was better than 0.1 m/s.     

基于泛在位置服务的嵌入式导航计算机系统研究与设计

分析了全球定位系统(GPS)、捷联惯导系统(SINS)和无线定位技术(WLAN)在城市复杂环境下室内外定位时的优缺点,提出了在城市复杂环境下采用基于卡尔曼滤波松组合的SINS／GPS组合导航定位方式,在室内环境下时,单独使用WLAN无线定位技术时易受室内复杂环境的影响,比如天花板、墙壁造成的多径效应,在传播过程中易受相近频段电器的干扰等等;提出了采用基于卡尔曼滤波的SINS／WLAN的组合导航定位技术来实现,从而实现更加平滑的导航定位结果。同时兼顾全组合导航系统高精度、低功耗、小型化的要求,设计出基于TMS320C6713和FPGA架构的嵌入式导航计算机平台。通过该平台系统的搭建,能够有效解决人们对泛在位置服务的需求问题。      

Receiver Architectures for Improved Carrier Phase Tracking in Atenuation, Blockage, and Interference

A significant impediment to real-time centimeter survey and vehicle guidance in difficult reception environments is the underlying signal tracking performance of the receiver. A number of researchers have investigated receiver signal tracking enhancements that take advantage of intersatellite path correlations, of particular benefit in environments with multiple satellite attenuations and blockages. This article surveys work in the area, with a focus upon an optimal estimation scheme known as integrated demodulation/navigation (IDN). By contrast with other techniques, IDN employs a high update rate extended Kalman filter to combine and process raw correlator data across satellites. Nonlinear loop simulations of real time kinematic (RTK) tracking during high-g aircraft maneuvers with vehicle-induced blockages are used to illustrate the filtering method and it s robustness. ? 1999 John Wiley & Sons, Inc.     

利用神经网络预测的GPS/SINS组合导航系统算法研究

提出了一种基于神经网络预测的GPS/SINS组合导航系统算法。GPS信号可用时,该算法分别将惯性传感器的输出以及卡尔曼滤波器的输出信息作为神经网络的输入及理想输出信息,并进行在线训练;当GPS信息失锁时,利用已经训练好的神经网络预测各导航参数误差,并校正SINS。地面静态实验与动态跑车实验结果证明了该方法的可行性与有效性。