南京理工大学学报（自然科学版）
南京理工大學學報（自然科學版）
남경리공대학학보（자연과학판）
JOURNAL OF NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY
2009年
6期
751-755
,共5页
单观测器%纯方位%被动跟踪%平方根无迹卡尔曼滤波%非线性滤波
單觀測器%純方位%被動跟蹤%平方根無跡卡爾曼濾波%非線性濾波
단관측기%순방위%피동근종%평방근무적잡이만려파%비선성려파
single observer%bearing-only%passive tracking%square-root unscented Kalman filter%nonlinear filtering
为了避免被动跟踪中非线性性带来的计算复杂化及跟踪精度的下降,该文将平方根无迹卡尔曼滤波(SR-UKF)算法应用到水下仅测角目标跟踪.利用协方差平方根代替协方差参加递推运算,解决了标准无迹卡尔曼滤波(UKF)算法中由于计算误差和噪声等因素有可能引起误差协方差矩阵负定而导致滤波结果发散的问题,保证了滤波算法的数值稳定性,提高了跟踪的精度和可靠性.仿真结果表明,SR-UKF非线性滤波算法应用于水下仅测角目标跟踪系统是有效的,而且滤波精度、稳定性和收敛时间明显优于扩展卡尔曼滤波(EKF)和标准UKF算法.
為瞭避免被動跟蹤中非線性性帶來的計算複雜化及跟蹤精度的下降,該文將平方根無跡卡爾曼濾波(SR-UKF)算法應用到水下僅測角目標跟蹤.利用協方差平方根代替協方差參加遞推運算,解決瞭標準無跡卡爾曼濾波(UKF)算法中由于計算誤差和譟聲等因素有可能引起誤差協方差矩陣負定而導緻濾波結果髮散的問題,保證瞭濾波算法的數值穩定性,提高瞭跟蹤的精度和可靠性.倣真結果錶明,SR-UKF非線性濾波算法應用于水下僅測角目標跟蹤繫統是有效的,而且濾波精度、穩定性和收斂時間明顯優于擴展卡爾曼濾波(EKF)和標準UKF算法.
위료피면피동근종중비선성성대래적계산복잡화급근종정도적하강,해문장평방근무적잡이만려파(SR-UKF)산법응용도수하부측각목표근종.이용협방차평방근대체협방차삼가체추운산,해결료표준무적잡이만려파(UKF)산법중유우계산오차화조성등인소유가능인기오차협방차구진부정이도치려파결과발산적문제,보증료려파산법적수치은정성,제고료근종적정도화가고성.방진결과표명,SR-UKF비선성려파산법응용우수하부측각목표근종계통시유효적,이차려파정도、은정성화수렴시간명현우우확전잡이만려파(EKF)화표준UKF산법.
To avoid the computational complexity and the tracking precision decrease from the nonlinear feature in passive tracking, a new square-root unscented Kalman filter(SR-UKF) algorithm is proposed to track underwater targets. The covariance square root matrix is taken in stead of covariance matrix in filter recursion. The filtering divergence problem caused by non-positive error covariance matrix in general unscented Kalman filter(UKF) is solved, and the tracking precision and stability of the algorithm is improved. The simulation results show that the SR-UKF is an effective nonlinear filtering method for underwater bearing-only tracking system, and it performs better than extended Kalman filter(EKF) and general UKF in filtering precision, stability and convergence time.
