基于 MEMS 辅助的单基线北斗融合测姿算法

载体的姿态信息是导航的重要参数，随着北斗卫星导航系统（Beidou navigation satellite system，BDS）和微机电系统（micro-electro-mechanical systems，MEMS）惯性传感器的发展与完善，高精度、低成本、自主化的融合测姿技术具有广阔的应用前景，因此，提出MEMS辅助单基线北斗融合测姿算法。根据MEMS惯性传感器解算出的姿态信息确定基线向量的搜索范围，从而辅助模糊度函数法（ambiguity function method，AFM）减小整周模糊度搜索空间，提高整周模糊度快速求解的成功率和计算效率。将BDS输出的姿态角信息作为观测信息，对MEMS陀螺仪解算出的姿态信息进行实时校正，实现BDS和MEMS传感器二者的数据融合算法。通过实测数据仿真验证，该算法能够解决信号失锁带来的整周模糊度求解困难的问题，并且测姿系统能在遮挡和动态等复杂环境下提供高质量姿态测量结果。

Single baseline Beidou fusion attitude determination algorithm based on MEMS inertial sensors

The attitude information of a platform is an important parameter for modern navigation. With the development and improvement of the Beidou navigation satellite system (BDS) and micro-electro-mechanical systems (MEMS) inertial sensor, high-precision, low-cost and independent fusion attitude determination technology has broad application prospects.Based on this,a single baseline Beidou fusion attitude determination algorithm aided by MEMS Inertial sensors has been proposed to solve the real-time attitude determination problem. Firstly, using the MEMS attitude information deduce the range of baseline vector in order to aide ambiguity function method (AFM), the success rate of fast ambiguity solution is increased. Secondly the BDS attitude is taken as the observation information to eliminate the MEMS gyroscope drift during long-time attitude measurement. The results of simulation test experiments on measured data demonstrate the algorithm can solve ambiguity resolution problem when the signal is unlock and can offer high precision attitude information under complex circumstance.