鱼雷技术
魚雷技術
어뢰기술
TORPEDO TECHNOLOGY
2013年
1期
15-20
,共6页
水下声自导武器%目标跟踪%基座运动%观测时变%卡尔曼滤波
水下聲自導武器%目標跟蹤%基座運動%觀測時變%卡爾曼濾波
수하성자도무기%목표근종%기좌운동%관측시변%잡이만려파
underwater acoustic homing weapon%target tracking%observation-base movement%time-varying observation%Kalman filter
目标跟踪是水下声自导武器智能化发展的重要方向之一.水下主动声自导武器目标跟踪过程具有观测基座运动和观测时变的特点,本文利用水下声自导武器导航定位及航行姿态参数和水下声自导武器检测到的目标信息,基于坐标变换将目标坐标从水下声自导武器坐标系变换到大地坐标系,解决了观测基座运动的问题,通过实时计算采样周期解决了观测时变问题,建立了基于卡尔曼滤波的水下声自导武器目标跟踪模型,分析了滤波初值选取问题,给出了滤波初值选取的工程方法.仿真结果证明,本文所建模型正确,跟踪算法具有较快的收敛速度,跟踪效果良好.
目標跟蹤是水下聲自導武器智能化髮展的重要方嚮之一.水下主動聲自導武器目標跟蹤過程具有觀測基座運動和觀測時變的特點,本文利用水下聲自導武器導航定位及航行姿態參數和水下聲自導武器檢測到的目標信息,基于坐標變換將目標坐標從水下聲自導武器坐標繫變換到大地坐標繫,解決瞭觀測基座運動的問題,通過實時計算採樣週期解決瞭觀測時變問題,建立瞭基于卡爾曼濾波的水下聲自導武器目標跟蹤模型,分析瞭濾波初值選取問題,給齣瞭濾波初值選取的工程方法.倣真結果證明,本文所建模型正確,跟蹤算法具有較快的收斂速度,跟蹤效果良好.
목표근종시수하성자도무기지능화발전적중요방향지일.수하주동성자도무기목표근종과정구유관측기좌운동화관측시변적특점,본문이용수하성자도무기도항정위급항행자태삼수화수하성자도무기검측도적목표신식,기우좌표변환장목표좌표종수하성자도무기좌표계변환도대지좌표계,해결료관측기좌운동적문제,통과실시계산채양주기해결료관측시변문제,건립료기우잡이만려파적수하성자도무기목표근종모형,분석료려파초치선취문제,급출료려파초치선취적공정방법.방진결과증명,본문소건모형정학,근종산법구유교쾌적수렴속도,근종효과량호.
Target tracking is one of the important directions in the development of modern intellectualized underwater acoustic homing weapon. However, the observation-base is moving and the observation is time-varying when an active acous-tic homing weapon tracks a target. In this study, the parameters of location and attitude from the acoustic homing weapon′s navigation system and the target information detected by the acoustic homing weapon are used to resolve the problem of ob-servation-base movement and time-varying observation. The target coordinates in acoustic homing weapon coordinate systems are transformed to terrestrial coordinate system to resolve the problem of observation-base′s movement, and the sampling time is calculated in real time to resolve the problem of observation′s time-varying. A target tracking model of acoustic homing weapon based on Kalman filter is established. The choosing of filter′s initialization values is analyzed, and the application method of choosing filter initialization values is presented. Simulation results show that the model is accurate, and the tracking algorithm is of faster convergence and better tracking effect.