CAJ | 학술논문

为提高自主水下航行器的导航精度,比较目前 AUV 常用的水下导航方式,将捷联式惯性导航系统与地球物理导航系统相结合构成水下无源组合导航系统.采用容错联邦卡尔曼滤波对各子系统信息进行故障诊断、系统重构和融合.针对传统的2c检验法不能确定故障具体原因,而仅能判断量测信息是否有效的缺陷,提出利用神经网络辅助2c检验法进行故障诊断.通过对水下组合导航系统算法进行仿真分析,结果表明该算法能够快速、准确地判断系统故障源,通过故障隔离和系统重构,使系统在故障情况下依然保持正常工作.
위제고자주수하항행기적도항정도,비교목전 AUV 상용적수하도항방식,장첩련식관성도항계통여지구물리도항계통상결합구성수하무원조합도항계통.채용용착련방잡이만려파대각자계통신식진행고장진단、계통중구화융합.침대전통적2c검험법불능학정고장구체원인,이부능판단량측신식시부유효적결함,제출이용신경망락보조2c검험법진행고장진단.통과대수하조합도항계통산법진행방진분석,결과표명해산법능구쾌속、준학지판단계통고장원,통과고장격리화계통중구,사계통재고장정황하의연보지정상공작.
To improve the navigation accuracy of autonomous underwater vehicle, an integrated navigation system was proposed, which was composed of strapdown inertial navigation system (SINS), terrain-aided navigation (TAN) system and gravity-aided navigation (GAN) system. A fault-tolerant federated Kalman filter was used to fuse the various navigation sensors, detect the system fault and reconstruct the navigation system. In view that traditional cai-square hypothesis testing processes fault detection cannot determine the specific cause of the fault, and could only determine the validity of measure information, a new fault detection algorithm based on neural network was adopted. The application on underwater integrated navigation system demonstrates that the algorithm can rapidly and accurately detecting and identify the faults in the system. Therefore the effective fault isolating can be performed to realize the fault tolerance navigation.