CAJ | 학술논문

在基于双领航者的MAUVs协同定位过程中,为了减轻NLOS量测误差的影响,在假设NLOS修正偏差先验已知的前提下,以4状态Markov链描述了4种LOS/NLOS量测模型间相互独立转换过程,继而利用交互多模和Kalman滤波理论设计了一种AUVs间相对距离量测平滑算法,并将其距离量测估计结果应用于MAUVs协同定位系统中. 仿真结果对比表明,该算法可以有效提高AUVs间的相对距离量测估计精度,获得了更好的协同定位性能.
재기우쌍령항자적MAUVs협동정위과정중,위료감경NLOS량측오차적영향,재가설NLOS수정편차선험이지적전제하,이4상태Markov련묘술료4충LOS/NLOS량측모형간상호독립전환과정,계이이용교호다모화Kalman려파이론설계료일충AUVs간상대거리량측평활산법,병장기거리량측고계결과응용우MAUVs협동정위계통중. 방진결과대비표명,해산법가이유효제고AUVs간적상대거리량측고계정도,획득료경호적협동정위성능.
In the process of MAUVs cooperative localization based on two leaders, in order to mitigate the influence of NLOS measurement deviation, a four state Markov chain is used to describe the switch process among four LOS/NLOS range measurement models which are independent of each other. Then we design a relative range measure?ment smoothing algorithm by combining the IMM and Kalman filter theory among AUVs, and the range measurement estimation results are applied to the MAUVs cooperative localization system. Simulation results and their analysis indicate preliminarily that the proposed algorithm does improve effectively the estimation accuracy of relative range measurement among AUVs. Moreover, the performance of the corresponding cooperative localization is also better than that of conventional method.