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Ben K. H. Soon Steve Scheding Hyung-Kuen Lee Hung-Kyu Lee Hugh Durrant-Whyte 《GPS Solutions》2008,12(4):261-271
This paper presents a simple and effective approach that incorporates single-frequency, L1 time-differenced GPS carrier phase
(TDCP) measurements without the need of ambiguity resolution techniques and the complexity to accommodate the delayed-state
terms. Static trial results are included to illustrate the stochastic characteristics and effectiveness of the TDCP measurements
in controlling position error growth. The formulation of the TDCP observation model is also described in a 17-state tightly-coupled
GPS/INS iterative, extended Kalman filter (IEKF) approach. Preliminary land vehicle trial results are also presented to illustrate
the effectiveness of the TDCP which provides sub-meter positional accuracies when operating for more than 10 min. 相似文献
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A method to improve the alignment performance for GPS-IMU System 总被引：1，自引：0，他引：1
Zero velocity and zero east component of rotation rate relative to local geographic frame have been traditionally applied
as measurements for fine alignment of a GPS-IMU system. The performance of the fine alignment, however, will be affected by
several types of inertial sensor errors, which could cause part of the Kalman filter states to be unobservable. To overcome
this problem, a new method that utilizes the total outputs of the gyro triad and the accelerometer triad as part of the measurements
has been proposed by the authors. The initial results have confirmed the effectiveness of the method. In this paper, the observability
for both traditional and new alignment methods will be first reviewed. The results from computer simulations will then be
presented to compare the traditional and the new alignment methods for the purpose of evaluating the performance of the proposed
new method. Data acquired from real inertial sensors will also be applied to assess the traditional and new alignment methods
by analyzing their innovation sequences from the Klaman filter.
Based on a paper presented at the 18th International Technical Meeting of the Satellite Division of the Institute of Navigation,
Long Beach, California, September 2005. 相似文献
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在低精度MEMS-IMU和GPS组合导航中,由于IMU的精度问题,无法通过传统的解析方法实现方位失准角的粗对准,造成了大方位失准角问题,从而导致系统的强非线性。通过变换状态量,用方位失准角的两个三角函数代替方位失准角作为状态量,建立了新的线性系统方程。用改进奇异值分解法对新对准系统进行可观测度分析,完成了车载导航试验,结果表明：本初始对准方案在低精度的组合导航中具有很好的对准精度和对准速度。 相似文献
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CNS+GNSS+INS船载高精度实时定位定姿算法改进研究 总被引：2，自引：1，他引：1
天文导航（CNS）、卫星导航（GNSS）和惯性导航（INS）3种系统组合可提供高精度的定位定姿结果。实际工程中因INS长时间误差累积，以及系统硬件传输存在不可忽略的时间延迟，导致INS提供给CNS的预报粗姿态误差较大，恶劣海况下难以保障快速搜星，造成天文导航可靠性下降、姿态测量精度较低的问题。为此，本文提出了一种CNS+GNSS+INS高精度信息融合实时定位定姿框架，引入了等角速度外推措施，有效地解决了惯导信息延迟问题。通过高精度转台模拟恶劣海况下载体大角速度摇摆，验证了本文提出的改进算法的有效性。试验结果表明，该算法架构简单，性能可靠，显著提高了恶劣环境下星敏感器的快速、准确搜星能力，保障了三组合姿态测量的精度和可用性。 相似文献
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利用小型低空航摄平台和非量测小相幅相机,搭载动态GNSS/INS组合系统进行空三加密,研究无人机搭载GNSS/INS辅助在不同分辨率、不同基线数量条件下的像控点布设以及空三加密,并对其平面精度、高程精度进行分析,以实现利用少量地面控制点进行大比例尺地形图测图。 相似文献
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常规GPS/INS紧组合抗差自适应滤波只适用于卫星数≥4的情况,且预测残差构造自适应因子要求观测值可靠。针对该局限性,对常规抗差自适应滤波算法做出两点改进:1)采用两步滤波,用第1步常规EKF滤波残差构造第二步抗差算法的粗差判别量;2)在第2步滤波用预测残差构造自适应因子时,剔除异常观测值对应的预测残差和预测残差协方差,以削弱观测异常对自适应因子的不良影响。实验结果表明,常规抗差算法在卫星数4时不适用。常规自适应滤波算法在观测值存在异常的情况下无法正确修正模型异常。改进后的抗差自适应滤波算法在组合系统观测卫星数4且观测值存在异常的情况下,仍能正确修正观测粗差和动力学模型异常,能够达到良好的导航精度。 相似文献