| GNSS/声学联合定位的自适应滤波算法 |
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| 引用本文： | 邝英才,吕志平,王方超,李林阳,杨凯淳.GNSS/声学联合定位的自适应滤波算法[J].测绘学报,2020,49(7):854-864. |
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| 作者姓名： | 邝英才 吕志平 王方超 李林阳 杨凯淳 |
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| 作者单位： | 信息工程大学, 河南 郑州 450001 |
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| 基金项目： | 国家重点研发计划（2016YFB0501701）；国家自然科学基金（41674019） |
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| 摘 要： | 海底控制点布设是构建海洋时空基准的重要环节,而可靠的海洋基准定位模型及方法又是实现高精度海底控制点布设的前提和基础。应用广泛的走航船测量方式兼具灵活性和可控性,但载体异常扰动影响不可避免,易导致海底控制点联合定位模型解算失真。针对这一问题,本文提出一种基于自适应选权滤波的GNSS/声学联合解算方法。首先推导了统一海面及水下观测过程的GNSS/声学联合定位数学模型;然后研究了在联合模型的自适应滤波解算中对载体异常扰动的判别标准,给出了各状态参数自适应因子的构造方法;最后通过仿真和实测数据进行了试验验证。结果表明:引入自适应滤波算法后,能有效改善状态扰动对GNSS/声学联合定位的异常影响,提升其定位稳定性及定位精度;当分别对各类状态参数的自适应因子进行合理构造后,滤波效果可达最佳。
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| 关 键 词： | 海底控制点 GNSS/声学联合定位 自适应选权滤波 参数异常 动力学扰动 |
| 收稿时间： | 2019-09-24 |
| 修稿时间： | 2020-02-25 |
The adaptive filtering algorithm of GNSS/acoustic joint positioning |
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| KUANG Yingcai,Lü Zhiping,WANG Fangchao,LI Linyang,YANG Kaichun.The adaptive filtering algorithm of GNSS/acoustic joint positioning[J].Acta Geodaetica et Cartographica Sinica,2020,49(7):854-864. |
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| Authors: | KUANG Yingcai Lü Zhiping WANG Fangchao LI Linyang YANG Kaichun |
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| Institution: | Information Engineering University, Zhengzhou 450001, Chinat |
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| Abstract: | The layout of seafloor control points is an important part of constructing the marine space-time frame. And the reliable marine datum positioning models and methods are the premise and basis for the layout of high-precision seafloor control points. The widely used vessel sailing surveying has both flexibility and controllability. However, there are also the inevitable abnormal disturbance effects of the vessel, which leads to the distortion of the joint positioning model of seafloor control points. To solve this problem, a GNSS/acoustic joint positioning algorithm based on adaptive weight filtering is proposed. First, the GNSS/acoustic joint positioning mathematical model for combined sea surface and underwater observation processes is derived. Then the criterion of judging the dynamic disturbance when using the adaptive filter to solve the joint positioning model is studied, and the method of constructing adaptive factors for each state parameter is given. Finally, the simulated and the measured data were used to carry out the experiment. Results show that the adaptive filtering algorithm can effectively improve the abnormal influence of state disturbance on GNSS/acoustic joint positioning, and promote its positioning stability and accuracy. When the corresponding adaptive factors of various state parameters are constructed reasonably, the best performance of the filtering effect is proved. |
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