Page 100 - 《应用声学》2020年第1期
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[11] 王满林. 自适应衰减记忆 UKF 算法在三维水下目标跟踪中的 Liu Qinghui, Gao Jiang, Deng Nanming. Application
应用 [J]. 四川兵工学报, 2012, 33(5): 44–47. of CKF algorithm based on square root of variance in
[12] Zhu H, Hu H, Gui W. Adaptive unscented kalman filter torpedo tracking[J]. Torpedo Technology, 2015, 23(6):
for deep-sea tracked vehicle localization[C]. International 428–432.
Conference on Information & Automation, 2009. [18] 杨建, 罗涛, 魏世乐, 等. 基于 CKF 的多 UUV 协同定位方
[13] Yan W, Wei C, Cui R. Moving long baseline positioning 法 [J]. 舰船电子工程, 2018, 38(2): 53–56, 99.
algorithm with uncertain sound speed[J]. Journal of Me- Yang Jian, Luo Tao, Wei Shile, et al. A cooperation local-
chanical Science Technology, 2015, 29(9): 3995–4002. ization method of MUUVs based on CKF[J]. Ship Elec-
[14] Arasaratnam I, Haykin S. Cubature Kalman filters[J]. tronic Engineering, 2018, 38(2): 53–56, 99.
IEEE Transactions on Automatic Control, 2009, 54(6): [19] 迟凤阳. 水下航行器组合导航定位技术研究 [D]. 哈尔滨: 哈
1254–1269. 尔滨工程大学, 2015.
[15] Arasaratnam I, Haykin S. Cubature Kalman smoothers[J]. [20] Liu K, Liu B, Wang Y, et al. Adaptive square-root CKF
Automatica, 2011, 47(10): 2245–2250. with application to DR/LBL integrated heading estima-
[16] Zhen D, Balaji B. Comparison of the unscented and cu- tion for HOV[C]. Control & Decision Conference, 2015.
bature Kalman filters for radar tracking applications[C]. [21] Li X R, Jilkov V P. Survey of maneuvering target track-
IET International Conference on Radar Systems, 2012. ing. part I: dynamic models[J]. IEEE Transactions on
[17] 刘清慧, 高江, 邓南明. 基于方差平方根 CKF 算法在鱼雷跟 Aerospace Electronic Systems, 2003, 39(4): 1333–1364.
踪中的应用 [J]. 鱼雷技术, 2015, 23(6): 428–432.