基于角度和频率信息的机动目标无源自适应跟踪算法

在进行可观测性分析的基础上,综合利用方位角和频率观测信息,提出了一种利用单个模型对机动目标进行无源跟踪的UKF算法,该算法通过对目标的运动状态和机动参数进行联合估计自适应地逼近真实的运动模型,从而进行准确跟踪。与现有算法相比,本文的算法不仅运算量小,而且降低了对观测站自身的运动要求,但却保持了良好的性能。仿真结果表明了算法的有效性和正确性。

Adaptive Algorithm for Maneuvering Target Passive Tracking Based on Angle and Frequency Measurements

Utilizing the integrated information of target's angle of arrival and emitting frequency,a novel Unscented Kalman filter algorithm is proposed for maneuvering target tracking using only one single model based on the analysis of system's observability.The algorithm has the capability of approximating the true motion model adaptively through the joint estimation of target's motion status and maneuvering parameter,on which basis,the accurate tracking is obtained.Compared with the conventional algorithm,the proposed meth- od has the superiority of lower computational complexity and looser requirement of observer's own motion,without degrading the tracking performance.Numerical simulation shows that the algorithm is valid and correct.