白龙, 李速, 吴爽. 基于目标优化的多普勒计程仪参数离线标定方法[J]. 中国舰船研究, 2020, 15(增刊 1): 180–188. doi: 10.19693/j.issn.1673-3185.01934
引用本文: 白龙, 李速, 吴爽. 基于目标优化的多普勒计程仪参数离线标定方法[J]. 中国舰船研究, 2020, 15(增刊 1): 180–188. doi: 10.19693/j.issn.1673-3185.01934
shu
BAI L, LI S, WU S. Research on offline calibration of DVL parameters based on objective optimization method [J]. Chinese Journal of Ship Research, 2020, 15(Supp 1): 180–188. doi: 10.19693/j.issn.1673-3185.01934
Citation: BAI L, LI S, WU S. Research on offline calibration of DVL parameters based on objective optimization method [J]. Chinese Journal of Ship Research, 2020, 15(Supp 1): 180–188. doi: 10.19693/j.issn.1673-3185.01934
shu

基于目标优化的多普勒计程仪参数离线标定方法

Research on offline calibration of DVL parameters based on objective optimization method

    摘要
  • 摘要:
      目的  为提高水下机器人的水下组合导航定位精度，需要准确标定出捷联惯性导航系统(SINS)和多普勒计程仪(DVL) 之间的安装误差角以及DVL的刻度系数。借鉴多学科优化设计思路，提出基于目标优化方法和传感器实航采集数据的DVL参数离线标定方法。
      方法  首先，通过跑船实航的方式，开展传统两点法的DVL标定试验和4个航次的FINS/DVL组合导航定位精度验证试验，并将该试验结果作为对比参照；其次，基于离线数据的组合导航过程仿真，使用田口试验法对DVL参数的值域空间进行随机撒点计算，应用响应面模型对计算结果进行截面插值，得到初步的最优解，即DVL标定参数的初值；之后，使用单目标粒子群优化算法，通过迭代优化DVL参数，最终收敛得到最优解，即该方法标定出的DVL参数；最后，使用实航标定出的DVL参数和优化方法得到的DVL参数，分别进行4个航次的FINS/DVL组合导航的离线仿真验证。
      结果  结果表明：目标优化方法适用于DVL参数的离线标定，与传统两点法标定相比，经过该方法标定后的FINS/DVL组合导航的终点定位误差降低了24.1%，水下组合导航定位精度显著提升。
      结论  所提方法可为自主式水下机器人（AUV）组合导航系统的DVL标定提供有效手段。

     

    Abstract:
      Objectives  In order to improve the positioning accuracy of underwater integrated navigation, it is necessary to accurately calibrate the installation error angle between strapdown inertial navigation system (SINS) and Doppler velocity log (DVL), and the calibration coefficient of DVL. Based on the idea of multidisciplinary optimization design, this paper presents an offline for DVL parameter calibration method based on the target optimization method and sensor real data.
      Methods  First, the traditional two-point method of DVL calibration and four voyages of FINS/DVL integrated navigation positioning accuracy verification are carried out by sailing, which can be used as a reference for comparison with this method. Second, based on a simulation of the integrated navigation process with offline data, the Taguchi test method is used to calculate the value space of the DVL parameters. The response surface model is then used to interpolate the calculation results so as to serve as the initial value of the DVL calibration parameters. Next, a single objective particle flow optimization algorithm is used to optimize the DVL parameters by iteration and converge to the optimal solution as the DVL parameters are calibrated. Finally, using the DVL parameters calibrated by sailing and those obtained through the optimization method, the offline simulation verification of FINS/DVL integrated navigation is carried out in four rounds.
      Results  The results show that the target optimization method is suitable for the offline calibration of DVL parameters. Compared with the traditional two-point method, after calibration by this method, the end-point positioning error of FINS/DVL integrated navigation is reduced by 24.1%, and the positioning accuracy of underwater integrated navigation is significantly improved.
      Conclusion  The proposed method can provide an effective method for the DVL calibration of autonomous underwater vehicle (AUV) integrated navigation systems.

     

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