一种在较大初始数学平台误差角下提高AUV导航精度的新方法  被引量:2

A Method to Improve AUV Navigation Accuracy Under Considerable Initial Alignment Errors

在线阅读下载全文

作  者:严恭敏[1] 严卫生[1,2] 徐德民[1,2] 

机构地区:[1]西北工业大学航海学院,陕西西安710072 [2]水下信息处理与控制国家级重点实验室,陕西西安710072

出  处:《鱼雷技术》2009年第2期20-24,共5页Torpedo Technology

基  金:中国博士后科学基金(20070420215);国防科技重点实验室基金资助项目

摘  要:如果发射冲击很大或者初始对准时间很短,可能导致自主水下航行器(AUV)中捷联惯导系统(SINS)的初始平台误差角比较大,特别是方位误差角大时,它成为影响AUV自主导航精度的重要因素。发射后利用捷联惯性测量组件(SIMU)和多普勒测速仪(DVL)的采样输出,同时实施航位推算(DR)和捷联罗经对准(GA)2种算法。当GA在短时间内水平调平后,直接修正DR的水平姿态角;当GA方位对准基本收敛后,计算GA方位与DR方位之间的方位误差,并借助于航迹相似性原理修正DR的方位角和位置,从而提高后续阶段的AUV导航精度。仿真结果表明,该方法可以修正由初始平台误差角造成的定位误差,但对与DVL有关的定位误差无效,修正后AUV定位误差下降到不修正的19.8%。For strapdown inertial navigation system (SINS) in autonomous underwater vehicle (AUV), launch shock or insufficient alignment time may result in considerable initial misalignment errors, and the azimuth misalignment error is a major factor to reduce AUV position accuracy. In this paper, dead-reckoning (DR) and strapdown gym-compass alignment (GA) algorithms are synchronously executed soon after AUV launch using raw data from strapdown inertial measurement unit (SIMU) and Doppler ve- locity log (DVL). After a short-time of GA level tuning stage, DR level attitudes are corrected to diminish level errors, but DR azimuth is corrected only when GA is convergent during the azimuth adjustment stage. Azimuth error between GA and DR is cal- culated, and DR position errors can be estimated by the similarity theory of DR course and AUV actual course. Hence, AUV navigation accuracy can be improved. The simulation results show that the proposed method can perfectly correct position errors due to initial misalignment errors, but excluding position errors caused by DVL scale error. In the simulation case, AUV position errors diminish to 19.8% after error compensation.

关 键 词:自主水下航行器 捷联惯导系统 多普勒测速仪 航位推算 捷联罗经初始对准 

分 类 号:V249.3[航空宇航科学与技术—飞行器设计]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象