基于UKF算法的双机协同无源跟踪  

Passive Tracking by Dual Aircraft Cooperation Based on UKF Algorithm

作　　者：张平[1] 方洋旺[1] 朱剑辉[1] 乔治军[2] 

机构地区：[1]空军工程大学工程学院 [2]中国人民解放军95856部队

出　　处：《电光与控制》2012年第4期26-30,共5页Electronics Optics & Control

摘　　要：针对单机对目标被动定位跟踪不具有完全可观测性,建立了双机协同探测定位跟踪模型,利用双机探测到的目标方位角和俯仰角,结合非线性滤波算法估计出目标的位置和速度参数。为解决传统的非线性滤波误差比较大、容易发散的问题,引入无迹卡尔曼滤波(UKF)算法。仿真实验表明,与扩展卡尔曼滤波相比较,UKF能更好地解决量测方程的非线性问题,滤波效果更好。Passive target locating and tracking by single airborne observer may not show complete observability under some special conditions. To solve the problem, a mathematical model for target tracking by dual aircraft cooperation was established. With the azimuth and pitch angle of the target measured by the dual aircrafts, nonlinear filtering algorithm was used to estimate the position and velocity of the target. To solve the problems of traditional nonlinear filtering of large error and liable to diverge, the novel algorithm of Unscented Kalman Filter （UKF） was introduced in this paper. Simulation results show that： compared with Extended Kalman Filter（ EKF）, UKF is superior in solving the nonlinear system problem and has better filtering effects.

关 键 词：双机协同 无源跟踪 可观测性 UKF 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计] TP721.1[自动化与计算机技术—检测技术与自动化装置]