摘要
阐述了卡尔曼滤波(KF)和扩展卡尔曼滤波(EKF)的原理和方法,建立了无源定位系统的状态模型和观测模型,推导了将非线性观测模型线性化,并利用EKF进行递推滤波估计的步骤和公式。通过计算机仿真,验证了运用EKF算法解决基于方位角及其变化率测量信息的无源定位方法,结果表明,运用EKF滤波算法,可以实现单观测站对运动目标的无源定位,初始状态估计误差对定位收敛的性能有较大影响。
The principle and the method of Kalman filter（KF） and extended Kalman filter（EKF） are illuminated. The status model and the measurement model of the passive location system are established. The procedure and formulas are deduced, which the measurement model was linearization and the position of the emitter was estimated by EKF. Through computer simulation, the method of passive location is validated feasibility, which is realized by EKF algorithm based on azimuth angle and its changing rate information. The result shows that the error of the estimate initialization affects the property of the location convergence.
出处
《中国电子科学研究院学报》
2011年第6期622-625,共4页
Journal of China Academy of Electronics and Information Technology
关键词
EKF
无源定位
仿真
EKF
Passive Location
Simulation
