摘要
利用频率变化率、方位角及俯仰角信息,提出一种对固定辐射源的三维单站无源定位算法。该方法通过质点运动学原理,得出目标辐射源的位置,之后采用EPF滤波算法进行处理,对粗略定位结果进行修正和平滑,逐步估计出目标的位置。EPF(Extended Particle Filter)滤波是将EKF(Extended Kalman Filter)算法作为重要性函数的一种粒子滤波方法。仿真结果表明,基于EPF滤波的单站无源定位算法比传统的EKF滤波算法收敛更快、更稳定,滤波效果更好,定位精度更高,这对无源定位跟踪算法精度的提高和实际应用有很大的意义。
A 3-D single observer passive positioning method based on frequency variation, azimuth and elevation information is presented. According to the theory of particle kinematics, the radiation position of target can be obtained and processed by using EPT. The rough positioning result is corrected and smoothed to estimate the position of target. EPF （Extended Particle Filter） is a particle filtering method taking EKF as an important function. Simulation results show that EPF-based single observer passive position method is used to achieve more quick and stabilized convergences and better accuracy than conventional EKF. It has profound significance for improvement in passive positioning and tracking algorithm and actual application.
出处
《现代导航》
2013年第2期134-139,共6页
Modern Navigation
关键词
三维单站无源定位
频率变化率
方位角
俯仰角
扩展卡尔曼粒子滤波
3-D Single Observer Passive Positioning
Frequency Variation： Azimuth~ Elevation： Extended Kalman ParticleFilter
