摘要
被动测距中直接测量的方位角、俯仰角与位置坐标的非线性函数组成测量方程。假设目标相对于观测站在三维空间中作匀速直线运动,建立了运动单站被动测距的状态转移方程。由测量方程和状态转移方程组成的动力学模型,将被动测距归结为典型的非线性状态估计问题。粒子滤波器利用Monte Carlo模拟计算状态的最优Bayesian估计,它适合于任何能用动力学系统概述的模型,状态估计精度不依赖于坐标初始假设值。模拟实验实现了粒子滤波在匀速运动观测站对匀速运动目标的被动测距,实验结果说明:粒子滤波器在被动测距中有重要的意义。
Measurement equation in passive ranging consists of nonlinear functions among observed azimuth, elevation angle and position coordinates. Given that the object moves with uniform speed in a straight line relative to observation station in 3D space, state transfer equation for single moving platform passive ranging was proposed.In the dynamic model composed of measurement and state transfer equation, the passive ranging was described as a classical nonlinear state estimation. Monte Carlo simulation was used by the particle filters （PF） to calculate the optimized Bayesian estimation of the state, which was suitable for any state-space models. State estimation precision didn＇t depend on the initialized coordinate hypothesis. When the observation station moved with constant speed, the simulation of constant speed passive ranging was implemented. The experimental results show that particle filter plays an important role in the single moving platform passive ranging.
出处
《红外与激光工程》
EI
CSCD
北大核心
2009年第4期716-720,741,共6页
Infrared and Laser Engineering
基金
国家863高技术项目
