UKF与EKF在空对海单站TO-TMA中的应用

Application of Air-to-Sea Time-of-Arrival Only TMA Based on UKF and EKF Algorithms

探讨了目标运动分析(Target moving analysis,TMA)中基本的非线性估计问题,介绍了基于UT的UKF算法的设计思想与具体实现,特别针对空对海单站无源到达时间TMA(TO-TMA)问题应用UKF和EKF进行了对照研究,建立了问题的离散非线性滤波估计模型,设计了典型的应用场景,给出了Monte Carlo仿真运行结果;表明UKF在该特定应用背景下,由于模型的非线性较弱,使得UKF在精度上与EKF相当,而且在运算量上也有所增加。

Compared with the extended kalman（EKF） algorithm, unscented kalman filtering filtering（UKF） algorithm is used to solve the problems of the target moving analysis （TMA） based on time-of-arrival measurements（TO-TMA）. Firstly, the nonlinear filtering problem is identified in the groundwork embedded in TMA. The UT and UKF including their design consideration and specific algorithm are then introduced . Particular attention is paid to the problem of single observer passive air-to-sea TO-TMA. The discrete-time models are formulated as to the nonlinear filtering problem and a typical scenario is depicted. The results of Monte Carlo simulations have demonstrated that the UKF performs nearly the same as the EKF does in accuracy for the above special background with weak nonlinearity.