摘要
为了降低动态扰动误差对容积卡尔曼滤波(Cubature Kalman Filter,CKF)精度的影响,采用新息自适应估计(Innovation-based Adaptive Estimation,IAE)理论构造改进的CKF滤波模型,利用新息序列在线估计和修正噪声统计特性,自适应地调整量测噪声。通过SINS/GPS组合导航系统对标准CKF与改进的CKF进行仿真验证,结果表明,改进的CKF算法能够在一定程度上提高组合导航系统对不同随机噪声的适应能力,有效地降低了滤波误差,提高了解算精度。
An improved Cubature Kalman Filter（CKF）model using Innovation-based Adaptive Estimation（IAE）is implemented to reduce abnormal dynamic error of CKF.The innovation information is used to on-line estimate and correct noise statistical characteristics,automatically adjust measurement.Both the CKF and improved CKF are applied to the SINS/GPS integrated navigation system,and the simulation results show that the improved CKF algorithm can improve the adaptability to different stochastic disturbances,decrease filtering error and improve the calculation accuracy.
出处
《长春工业大学学报》
CAS
2016年第2期134-140,共7页
Journal of Changchun University of Technology
