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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >SINS/CNS Nonlinear Integrated Navigation Algorithm for Hypersonic Vehicle
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SINS/CNS Nonlinear Integrated Navigation Algorithm for Hypersonic Vehicle

机译：高超声速飞行器SINS / CNS非线性组合导航算法

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摘要

Celestial Navigation System (CNS) has characteristics of accurate orientation and strong autonomy and has been widely used in Hypersonic Vehicle. Since the CNS location and orientation mainly depend upon the inertial reference that contains errors caused by gyro drifts and other error factors, traditional Strap-down Inertial Navigation System (SINS)/CNS positioning algorithm setting the position error between SINS and CNS as measurement is not effective. The model of altitude azimuth, platform error angles, and horizontal position is designed, and the SINS/CNS tightly integrated algorithm is designed, in which CNS altitude azimuth is set as measurement information. GPF (Gaussian particle filter) is introduced to solve the problem of nonlinear filtering. The results of simulation show that the precision of SINS/CNS algorithm which reaches 130 m using three stars is improved effectively.
机译：天体导航系统（CNS）具有定位准确，自主性强的特点，已广泛应用于高超音速飞行器中。由于CNS的位置和方向主要取决于包含陀螺仪漂移和其他误差因素引起的误差的惯性参考，因此传统的捷联惯性导航系统（SINS）/ CNS定位算法不会将SINS和CNS之间的位置误差设置为测量值有效。设计了高度方位角，平台误差角和水平位置的模型，设计了以CNS高度方位角为测量信息的SINS / CNS紧密集成算法。引入GPF（高斯粒子滤波）来解决非线性滤波问题。仿真结果表明，采用三颗星达到130INSm的SINS / CNS算法精度得到了有效提高。

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