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矢量跟踪是一种将全球导航卫星系统(GNSS)接收机的信号跟踪与导航解算融为一体的跟踪算法。传统的基于矢量延迟/频率锁定环(VDFLL)的跟踪算法普遍采用延迟锁定环(DLL)和锁频环(FLL)鉴别器计算伪距和伪距率偏差观测量,由于锁频环鉴别器存在近似误差和一步延迟效应,在高动态环境下容易造成环路失锁。从直接估计卫星信号特征参数的角度出发,基于中频信号模型构建码相位和载波多普勒的极大似然代价函数,采用非迭代估计算法得到各通道码相位和多普勒频移的估计偏差,转换为卡尔曼滤波器的观测矢量,提出一种基于极大似然估计器(MLE)的矢量跟踪算法。理论分析和仿真结果表明:新算法结合了极大似然估计和矢量跟踪的优点,克服了FLL的延迟效应,与基于VDFLL的矢量环路相比,高动态环境下的跟踪稳定性更好,可以对被遮挡的卫星保持持续的跟踪。
Vector tracking is a tracking algorithm that combines the signal tracking and navigation solutions of a Global Navigation Satellite System (GNSS) receiver. Traditional tracking algorithms based on vector delay / frequency locked loop (VDFLL) commonly use delay locked loop (DLL) and frequency locked loop (FLL) discriminators to calculate pseudoranges and pseudo range error observations. Because of the existence of the locked loop discriminator Approximate error and one-step delay effect, in a high dynamic environment is likely to cause the loop loss of lock. From the point of view of directly estimating the characteristic parameters of satellite signals, based on the maximum likelihood cost function of the IF phase and the carrier Doppler of the intermediate frequency signal model, the estimation error of the phase and Doppler shift of each channel is obtained by a non-iterative estimation algorithm , Converted to Kalman filter observation vector, a maximum likelihood estimator (MLE) based vector tracking algorithm. Theoretical analysis and simulation results show that the new algorithm, which combines the advantages of maximum likelihood estimation and vector tracking, overcomes the delay effect of FLL. Compared with the vector loop based on VDFLL, the new algorithm has better tracking stability under high dynamic environment, Keep track of occluded satellites.