Attitude estimation using multi-antenna Global Navigation Satellite System (GNSS) has caught broad attention in recent years. The methods of indirectly calculating attitude parameters based on baseline vectors have been widely used. However, the accuracy of such methods needs to be further improved. An algorithm of directly estimating attitude parameters based on adaptive Kalman filtering (AKF) is proposed. The high-precision phase measurements are used and the system noise covariance matrix corresponding to Euler angles and angle rates is adaptively adjusted according to the maximum a posteriori estimation principle. To decrease the linearisation errors and speed the filtering convergence, a switching strategy is implemented. Namely, when the number of fixed ambiguities is equal to or more than three, the authors deem that the attitude estimate is sufficiently accurate, hence the initial state vector is constructed to start filtering. Otherwise, the attitude parameters are indirectly obtained. The static and simulation experiments are carried out. A comparative study is implemented with the two methods of indirectly calculating attitude parameters. The static and simulation results demonstrate that the proposed method has a competent performance in both accuracy and fixing success rate. The simulation results also show that the adaptability of the AKF method is nice.

中文翻译：

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基于相位测量的自适应卡尔曼滤波的GNSS姿态估计

近年来，使用多天线全球导航卫星系统（GNSS）进行姿态估计已引起广泛关注。基于基线矢量间接计算姿态参数的方法已被广泛使用。但是，这种方法的准确性需要进一步提高。提出了一种基于自适应卡尔曼滤波的姿态参数直接估计算法。使用高精度相位测量，并根据最大后验估计原理自适应调整与欧拉角和角速率对应的系统噪声协方差矩阵。为了减少线性化误差并加快滤波收敛，实施了一种切换策略。即，当固定歧义数等于或大于三个时，作者认为姿态估计足够准确，因此构造了初始状态向量以开始滤波。否则，间接获取姿态参数。进行了静态和模拟实验。用两种间接计算姿态参数的方法进行了比较研究。静态和仿真结果表明，该方法在准确性和修复成功率方面均具有出色的性能。仿真结果还表明，AKF方法的适应性很好。两种间接计算姿态参数的方法进行了比较研究。静态和仿真结果表明，该方法在准确性和修复成功率方面均具有出色的性能。仿真结果还表明，AKF方法的适应性很好。两种间接计算姿态参数的方法进行了比较研究。静态和仿真结果表明，该方法在准确性和修复成功率方面均具有出色的性能。仿真结果还表明，AKF方法的适应性很好。