机构

• 海洋研究所 [2]
• 长春光学精密机械与物... [1]
• 自动化研究所 [1]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [5]

内容类型

• 期刊论文 [3]
• 会议论文 [1]
• 学位论文 [1]

发表日期

• 2024 [2]
• 2023 [2]
• 2010 [1]

学科主题

筛选

浏览/检索结果: 共5条，第1-5条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 卡尔曼滤波算法在波浪浮标数据处理中的应用研究 学位论文  OAI收割 中国科学院海洋研究所: 中国科学院大学, 2024 作者:  蒋莎   |  收藏  |  浏览/下载：18/0  |  提交时间：2024/06/13 波浪观测  波浪浮标  加速度传感器  Sage-Husa自适应卡尔曼滤波  海浪谱   Adaptive Kalman Filter Based on Online ARW Estimation for Compensating Low-Frequency Error of MHD ARS 期刊论文  OAI收割 IEEE Transactions on Instrumentation and Measurement, 2024, 卷号: 73, 页码: 1-10 作者:  Su, Yunhao;  Han, Junfeng;  Ma, Caiwen;  Wu, Jianming;  Wang, Xuan   |  收藏  |  浏览/下载：29/0  |  提交时间：2024/07/22 Angular random walk (ARW)  magnetohydrodynamic angular rate sensor (MHD ARS)  microelectromechanical system (MEMS) gyroscope  Sage-Husa adaptive Kalman filter(SHAKF)  signal fusion   Advancements in Buoy Wave Data Processing through the Application of the Sage-Husa Adaptive Kalman Filtering Algorithm 期刊论文  OAI收割 SENSORS, 2023, 卷号: 23, 期号: 16, 页码: 18 作者:  Jiang, Sha;  Chen, Yonghua;  Liu, Qingkui   |  收藏  |  浏览/下载：14/0  |  提交时间：2023/12/13 Sage-Husa adaptive kalman filter  combined filter  wave direction spectrum  acceleration sensor   A Novel Adaptive Kalman Filter Based on Credibility Measure 期刊论文  OAI收割 IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 1, 页码: 103-120 作者:  Quanbo Ge;  Xiaoming Hu;  Yunyu Li;  Hongli He;  Zihao Song   |  收藏  |  浏览/下载：53/0  |  提交时间：2023/01/03 Credibility  expectation maximization-particle swarm optimization method (EM-PSO)  filter calculated mean square errors (MSE)  inaccurate models  Kalman filter  Sage-Husa  true MSE (TMSE)   Application of adaptive Kalman filter technique in initial alignment of strapdown inertial navigation system (EI CONFERENCE) 会议论文  OAI收割 29th Chinese Control Conference, CCC'10, July 29, 2010 - July 31, 2010, Beijing, China 作者:  Liu P. 收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25 In order to improve the alignment precision and convergence speed of strap-down inertial navigation system  but in the active system most noise statistical characteristics are unknown  an initial alignment method based on Sage-Husa adaptive filter is presented. We also derived the exactitude alignment error model and adaptive Kalman filter equation in the azimuth of small misalignment angle. As usual  in this case  known the noise statistical characteristics  we introduce the adaptive Kalman filter. It uses the information of observed data  Kalman filter is suitable  on-line estimation noise statistical characteristics and state simultaneously in order to improve the filter continuously  so  the filter has a higher estimation accuracy than the conventional Kalman filter. By simulating verifying  the adaptive Kalman filter enhances the convergence speed and alignment accuracy effectively.