Collision Vehicle Detection System Based on GPS/INS Integration

Continuous vehicle tracking as well as detecting accidents, are significant services that are needed by many industries including insurance and vehicle rental companies. The main goal of this paper is to provide methods to detect the position of car accident. The models consider GPS/INS-based navigation algorithm, calibration of navigational sensors, a de-nosing method as long as vehicle accident, expressed by a set of raw measurements which are obtained from various environmental sensors. In addition, the location-based accident detection model is tested in different scenarios. The results illustrate that under harsh environments with no GPS signal, location of accident can be detected. Also results confirm that calibration of sensors has an important role in position correction algorithm. Finally, the results present that the proposed accident detection algorithm can recognize accidents and related its positions.

GPS与INS的组合定位技术研究

组合定位技术是一种新的导航技术,能够使多个导航系统实现信息的互补性和协同性。其中,GPS和惯导结合是一种较为理想的组合定位系统,而深度融合模式是目前GPS和惯导(INS)联合使用的最佳方式,因此,对深度融合模式的研究显得尤为重要。

Modified Observation Model in Tightly-Coupled INS/GPS Integration

The conventional Kalman filter（CKF）is widely used in tightly-coupled INS/GPS integrated navigation systems.The linearization accuracy of the CKF observation model is one of the decisive factors of the estimation accuracy and therefore navigation accuracy.Additionally,the conventional observation model（COM）used by the filter may be divergent,which would result into some terrible accuracies of INS/GPS integration navigation in some cases.To improve the navigation accuracy,the linearization accuracy of the COM still needs further improvement.To deal with this issue,the observation model is modified with the linearization of the range and range rate equations in this paper.Compared with COM,the modified observation model（MOM）further considers the difference between the real user position and the position calculated by SINS.To verify the advantages of this model,INS/GPS integrated navigation simulation experiments are conducted with the usage of COM and MOM respectively.According to the simulation results,the positions（velocities）calculated using COM are divergent over time while the others using MOM are convergent,which demonstrates the higher linearization accuracy of MOM.

Novel approach to GPS/SINS integration for IMU alignment

Strapdown inertial navigation system（SINS） requires an initialization process that establishes the relationship between the body frame and the local geographic reference.This process,called alignment,is generally used to estimate the initial attitude angles.This is possible because an accurate determination of the inertial measurement unit（IMU） motion is available based on the measurement obtained from global position system（GPS）.But the update frequency of GPS is much lower than SINS.Due to the non-synchronous data streams from GPS and SINS,the initial attitude angles may not be computed accurately enough.In addition,the estimated initial attitude angles may have relatively large uncertainties that can affect the accuracy of other navigation parameters.This paper presents an effective approach of matching the velocities which are provided by GPS and SINS.In this approach,a digital high-pass filter,which implements a pre-filtering scheme of the measured signal,is used to filter the Schuler cycle of discrete velocity difference between the SINS and GPS.Simulation results show that this approach improves the accuracy greatly and makes the convergence time satisfy the required accuracy.

Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration

Traditional cubature Kalman filter(CKF)is a preferable tool for the inertial navigation system(INS)/global positioning system(GPS)integration under Gaussian noises.The CKF,however,may provide a significantly biased estimate when the INS/GPS system suffers from complex non-Gaussian disturbances.To address this issue,a robust nonlinear Kalman filter referred to as cubature Kalman filter under minimum error entropy with fiducial points(MEEF-CKF)is proposed.The MEEF-CKF behaves a strong robustness against complex nonGaussian noises by operating several major steps,i.e.,regression model construction,robust state estimation and free parameters optimization.More concretely,a regression model is constructed with the consideration of residual error caused by linearizing a nonlinear function at the first step.The MEEF-CKF is then developed by solving an optimization problem based on minimum error entropy with fiducial points(MEEF)under the framework of the regression model.In the MEEF-CKF,a novel optimization approach is provided for the purpose of determining free parameters adaptively.In addition,the computational complexity and convergence analyses of the MEEF-CKF are conducted for demonstrating the calculational burden and convergence characteristic.The enhanced robustness of the MEEF-CKF is demonstrated by Monte Carlo simulations on the application of a target tracking with INS/GPS integration under complex nonGaussian noises.

DESIGN & REALIZATION ON GPS/INS INTEGRATED NAVIGATION SYSTEM

讨论了应用卡尔曼滤波器的ＧＰＳ／ＩＮＳ组合导航系统，其中包括理论、方案与实际的ＩＮＳ和ＧＰＳ接收机的结合，研究的重点是对系统误差的建模及组合的实现，以及松组合和紧组合等各种组合方式等。该ＧＰＳ／ＩＮＳ组合导航开发系统，可以有效和经济地用于组合导航系统的研究和设计，在实际应用中起到了非常有效的作用。该系统不仅仅是一个计算机辅助设计软件，而且可以对实际获得的惯导和ＧＰＳ数据进行半物理仿真。开发系统的核心软件可以方便地转换成实际组合系统中的工程应用软件。应用结果表明，开发系统的设计思想和组合方案是成功的，可以取得良好的导航结果。

GPS与INS组合的便携式轨道类游乐设施轨迹研究

为检测轨道类游乐设施运行速度和轨迹,利用安卓智能手机内置的惯性导航系统(INS)、卫星导航系统(GPS)进行轨道类游乐设施运行加速度、角速度等数据进行采集分析;采用捷联惯性导航系统,建立轨道类游乐设施轨迹姿态解算模型,以卡尔曼滤波器为基础,在Matlab软件中构建松耦合模式的组合导航系统,对INS输出的速度、位置数据进行校正;在试验场地对游乐设施数据进行采集并进行处理,基于UG NX二次开发实现轨道游乐设施姿态信息显示、轨迹拟合。实验结果验证了使用安卓智能手机内置的INS\GPS组合导航系统采集轨道类游乐设施数据、运行轨迹的可行性,弥补了轨道类游乐设施姿态和轨迹测量相关研究的不足。

A FAST KALMAN FILTER FOR INTEGRATED GPS/INS BASED ON U-D FACTORIZATION

研究了基于Ｕ－Ｄ分解的快速Ｋａｌｍａｎ滤波算法，并将它应用到一个２１状态的ＧＰＳ／ＩＮＳ组合导航系统工程实现中。常规的Ｋａｌｍａｎ滤波器已广泛应用于ＧＰＳ／ＩＮＳ组合系统，但由于系统建模误差和计算舍入误差，Ｋａｌｍａｎ滤波器在工程应用中会出现发散现象。为了解决这个问题，本文推导了一个基于Ｕ－Ｄ的扩展Ｋａｌｍａｎ滤波器。此外，由于高阶组合系统计算量大，导致基于Ｕ－Ｄ分解的滤波器在实时应用中有困难，为此，本文提出了一种快速的滤波算法来节省计算时间。文中设计了一条近于实际的飞机航迹来仿真。结果表明，本文所提的滤波算法能有效地克服组合系统滤波器发散问题，并减少计算时间近６９％。

基于GPS/INS的无人机物流配送路径控制研究

随着科技的发展,通过利用无线电遥控设备和自备的程序控制装置操纵的无人驾驶的低空飞行器运载包裹,自动送达目的地,其优点主要在于解决偏远地区的配送问题,提高配送效率,同时减少人力成本。本文以GPS/INS技术为基础,通过深入分析无人机的运动轨迹,指出无人机物流配送路径的识别与控制方法,有利于提高无人机的速度和加速度,增加识别精度。

因子图框架下里程计辅助GNSS/INS组合导航算法

在复杂观测环境下,GNSS/INS组合导航系统的GNSS信号易受干扰从而导致INS独立导航精度迅速下降。针对上述问题,本文基于因子图的里程计辅助GNSS/INS组合导航算法,利用里程计观测信息结合非完整性约束构建航向速度约束方程,同时采用能多次线性化计算和多次迭代的因子图优化方法进行参数估计。实际车载试验解算结果表明,在GNSS信号良好时,基于因子图方法比滤波方法具有更快的收敛时间,收敛速度提高了近10倍;在GNSS信号发生中断时,添加里程计辅助后组合导航系统在东向和北向分别提升了83%和89%。与传统的滤波融合手段相比,本文采用因子图优化后在东向和北向的定位精度分别有63%、70%的改善。

Accuracy improvement of GPS/MEMS-INS integrated navigation system during GPS signal outage for land vehicle navigation

To improve the reliability and accuracy of the global po- sitioning system （GPS）/micro electromechanical system （MEMS）- inertial navigation system （INS） integrated navigation system, this paper proposes two different methods. Based on wavelet threshold denoising and functional coefficient autoregressive （FAR） model- ing, a combined data processing method is presented for MEMS inertial sensor, and GPS attitude information is also introduced to improve the estimation accuracy of MEMS inertial sensor errors. Then the positioning accuracy during GPS signal short outage is enhanced. To improve the positioning accuracy when a GPS signal is blocked for long time and solve the problem of the tra- ditional adaptive neuro-fuzzy inference system （ANFIS） method with poor dynamic adaptation and large calculation amount, a self-constructive ANFIS （SCANFIS） combined with the extended Kalman filter （EKF） is proposed for MEMS-INS errors modeling and predicting. Experimental road test results validate the effi- ciency of the proposed methods.

Adaptive Federal Kalman Filtering for SINS/GPS Integrated System

A new adaptive federal Kalman filter for a strapdown integrated navigation system/global positioning system (SINS/GPS) is given. The developed federal Kalman filter is based on the trace operation of parameters estimation's error covariance matrix and the spectral radius of update measurement noise variance-covariance matrix for the proper choice of the filter weight and hence the filter gain factors. Theoretical analysis and results from simulation in which the SINS/GPS was compared to conventional Kalman filter are presented. Results show that the algorithm of this adaptive federal Kalman filter is simpler than that of the conventional one. Furthermore, it outperforms the conventional Kalman filter when the system is undertaken measurement malfunctions because of its possession of adaptive ability. This filter can be used in the vehicle integrated navigation system.

ANALYSIS OF LEVER ARM EFFECTS IN GPS／IMU INTEGRATION SYSTEM

Disturbance specific force caused by the lever arm ef-fects in integration navigation system is investigated,Navigation errors eaused by the lever arm effects have been demonstrated under three flinght scenarios of the air-craft.Analytical under three flight scenarios of the ari-craft.Analytical results show that disturbance specific force resulted from lever arm effects may become one of the major error sources while an aircraft undertakes the maneuvers,and mavigation errors caused by the lever arm effects accumulate rapidly with time.Therefore,a com-pensation method must be taken into account to eliminate the disturbance specific force caused by the lever arm ef-fects in integration navigation system.

Hybrid Kalman and unscented Kalman filters for INS/GPS integrated system considering constant lever arm effect

In inertial navigation system(INS) and global positioning system(GPS) integrated system, GPS antennas are usually not located at the same location as the inertial measurement unit(IMU) of the INS, so the lever arm effect exists, which makes the observation equation highly nonlinear. The INS/GPS integration with constant lever arm effect is studied. The position relation of IMU and GPS's antenna is represented in the earth centered earth fixed frame, while the velocity relation of these two systems is represented in local horizontal frame. Due to the small integration time interval of INS, i.e. 0.1 s in this work, the nonlinearity in the INS error equation is trivial, so the linear INS error model is constructed and addressed by Kalman filter's prediction step. On the other hand, the high nonlinearity in the observation equation due to lever arm effect is addressed by unscented Kalman filter's update step to attain higher accuracy and better applicability. Simulation is designed and the performance of the hybrid filter is validated.

基于GPS/INS和线控转向的农业机械自动驾驶系统

研究旨在设计出一套农用车辆自动导航控制系统,让机器人代替农民进行田间作业,实现农用车辆自动驾驶,从而可以有效提高农业机械的作业精度、生产效率和使用安全性,并且为精细农业研究提供技术支持,改善农业生产的方法。该文通过GPS/INS（global positioning system/inertial navigation system）组合导航技术实时获得载体的导航信息（位置、速度、航向、姿态）,根据导航信息与预设轨迹参数计算出载体的目标前轮转向角,并以该目标前轮转向角与当前前轮转角的差值作为控制输入,实现对转向执行电机的精确控制,从而实现载体的路径跟踪控制。同时对整个系统的软硬件进行设计,并对系统控制策略进行仿真和试验验证。最终结果表明,本文所设计的组合导航系统定位精度高,其定位精度可达到0.1~0.5 m;路径跟踪系统误差小,当车速分别为0.5 m/s和1 m/s时,路径跟踪的最大横向误差分别为0.16 m和0.27 m;整个系统响应速度快,可达到0.1s。通过将GPS/INS组合导航技术与线控转向技术相结合,能够实现农用车辆的自动驾驶。

GPS/INS组合导航系统时间同步系统设计

为了说明高动态环境中时间同步对于组合导航系统的重要性,在Kalman滤波方程的基础上,推导了时间同步误差与Kalman滤波结果之间的定性关系。提出一种利用GPS接收机中1PPS(Pulse Per Second)信号作为同步标签的时间同步方法,将IMU中的数据加上精确的时间标签,从而达到时间同步的目的。全部时间同步功能由FPGA实现,利用Verilog HDL语言进行开发,整体硬件结构简单而且适用范围广。试验结果显示了这种时间同步设计可以明显减小滤波结果的估计误差,有效的提高了组合导航系统的定位精度。

基于模糊自适应卡尔曼滤波的INS/GPS组合导航系统算法研究

针对车载组合导航系统量测噪声统计特性随实际工作条件的不同而变化的特点,提出了一种基于模糊自适应卡尔曼滤波的车载INS/GPS组合导航算法。该方法通过监视理论残差与实际残差的比值是否在一附近,应用模糊推理系统不断的调整量测噪声协方差阵的加权,对卡尔曼滤波的量测噪声协方差阵进行递推在线修正,使其逐渐逼近真实噪声水平,从而使滤波器执行最优估计,提高导航系统的精度。对车载组合导航系统的仿真结果表明,这种算法对时变的量测噪声具有较强的自适应性,进而精度比常规卡尔曼滤波也大为提高,是一种可行的车载组合导航算法。

自适应UKF算法及其在GPS/INS组合导航中的应用

提出了一种自适应无迹Kalman滤波(UKF)算法.针对UKF受初始值误差和动力学模型异常扰动误差影响的问题,将自适应估计原理引入到UKF算法,将动力学模型信息对导航解的贡献进行合理调整.计算结果表明,在GPS/INS松组合导航系统数据处理时,UKF算法略优于扩展Kalman滤波(EKF),自适应UKF算法优于自适应EKF算法,自适应UKF算法能够很好地抑制动力学模型误差对导航解的影响,进一步提高导航解的精度和可靠性.

GPS/INS组合导航系统数据同步处理方法研究

论述了GPS/INS组合导航系统中的数据同步问题,提出了一种完全利用软件编程的数据实时同步的方法。实验结果表明,这种方法不需借助硬件电路,能较好地消除由GPS接收机和INS(惯性导航系统)之间数据不同步所引起的误差对组合系统导航精度的影响。

紧耦合GPS/INS组合特性及其关键技术

针对GPS/INS组合导航系统在军民各领域广泛应用的特点,鉴借国外对紧耦合GPS/INS组合模式的实验研究,分析常规紧耦合和深紧耦合GPS/INS组合模式的构成与工作原理,仿真研究紧耦合GPS/INS组合模式的特性,其具有高抗干扰能力、高伪距测量精度及高导航定位能力。面对深紧耦合GPS/INS组合导航突出的性能特点,探讨深紧耦合GPS/INS组合研究从仿真到工程化中的几个关键技术问题,目的以供相关人员在组合导航系统研制时参考。