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首页> 外文会议>International symposium on photoelectronic detection and imaging;ISPDI 2011 >Study on UKF based Federal Integrated navigation for High Dynamic Aviation
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Study on UKF based Federal Integrated navigation for High Dynamic Aviation

机译：基于UKF的高动态航空联邦集成导航研究

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High dynamic aircraft is a very attractive new generation vehicles, in which provides near space aviation with large flight envelope both speed and altitude, for example the hypersonic vehicles. The complex flight environments for high dynamic vehicles require high accuracy and stability navigation scheme. Since the conventional Strapdown Inertial Navigation System (SINS) and Global Position System (GPS) federal integrated scheme based on EKF (Extended Kalman Filter) is invalidation in GPS single blackout situation because of high speed flight, a new high precision and stability integrated navigation approach is presented in this paper, in which the SINS, GPS and Celestial Navigation System (CNS) is combined as a federal information fusion configuration based on nonlinear Unscented Kalman Filter (UKF) algorithm. Firstly, the new integrated system state error is modeled. According to this error model, the SINS system is used as the navigation solution mathematic platform. The SINS combine with GPS constitute one error estimation filter subsystem based on UKF to obtain local optimal estimation, and the SINS combine with CNS constitute another error estimation subsystem. A non-reset federated configuration filter based on partial information is proposed to fuse two local optimal estimations to get global optimal error estimation, and the global optimal estimation is used to correct the SINS navigation solution. The χ~2 fault detection method is used to detect the subsystem fault, and the fault subsystem is isolation through fault interval to protect system away from the divergence. The integrated system takes advantages of SINS, GPS and CNS to an immense improvement for high accuracy and reliably high dynamic navigation application. Simulation result shows that federated fusion of using GPS and CNS to revise SINS solution is reasonable and availably with good estimation performance, which are satisfied with the demands of high dynamic flight navigation. The UKF is superior than EKF based integrated scheme, in which has smaller estimation error and quickly convergence rate.
机译：高动力飞机是一种非常吸引人的新一代车辆，其中向高空速飞行器提供近距离飞行，同时在速度和高度上具有较大的飞行包线。用于高动力车辆的复杂飞行环境需要高精度和稳定性的导航方案。由于基于EKF（扩展卡尔曼滤波器）的常规捷联惯性导航系统（SINS）和全球定位系统（GPS）联邦综合方案由于高速飞行而在GPS单一停电情况下失效，因此，一种新的高精度和稳定性的综合导航方法本文提出，其中结合SINS，GPS和天体导航系统（CNS）作为基于非线性无味卡尔曼滤波器（UKF）算法的联邦信息融合配置。首先，对新的集成系统状态误差进行建模。根据该误差模型，将SINS系统用作导航解决方案数学平台。 SINS与GPS结合构成一个基于UKF的误差估计滤波器子系统，以获得局部最优估计，而SINS与CNS结合构成另一个误差估计子系统。提出了一种基于局部信息的非复位联合配置滤波器，将两个局部最优估计融合，得到全局最优误差估计，并利用全局最优估计对SINS导航解进行修正。采用χ〜2故障检测方法对子系统进行故障检测，通过故障间隔将故障子系统隔离开来，以保护系统免受发散的影响。该集成系统充分利用了SINS，GPS和CNS的优势，实现了高精度和可靠的高动态导航应用的巨大改进。仿真结果表明，采用GPS和CNS联合修正SINS解决方案的联合融合是合理，可行的，并且具有良好的估计性能，可以满足高动态飞行导航的需求。 UKF优于基于EKF的集成方案，该方案具有较小的估计误差和快速的收敛速度。

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