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提出了一种加权和(WS)-H∞滤波算法实现远距离干扰机(SOJ)环境下的目标跟踪。算法通过使用合适的传感器模型和高斯和(GS)似然函数,充分利用了干扰信息从而提高没有量测时的跟踪精度;同时针对干扰环境下的量测和干扰信息的统计分布不确定的特点,采用WS-H∞滤波算法提高整个跟踪系统的鲁棒性。仿真证明,WS-H∞滤波算法在量测噪声和干扰估计不准确时表现出了良好的鲁棒性,其航迹连续性和跟踪精度都明显优于GS扩展卡尔曼(GS-EKF)滤波算法,而计算复杂度却没有明显提高。
A weighted sum (WS) -H∞ filtering algorithm is proposed to realize the target tracking under long distance jammer (SOJ) environment. The algorithm uses the appropriate sensor model and Gaussian (GS) likelihood function to make full use of the interference information so as to improve the tracking accuracy without measurement. In view of the uncertain statistical distribution of the measurement and interference information in the interference environment , Using WS-H ∞ filtering algorithm to improve the robustness of the entire tracking system. The simulation results show that the WS-H∞ filtering algorithm shows good robustness when the measurement noise and interference estimation are inaccurate, and the track continuity and tracking accuracy are obviously better than the GS-EKF filtering Algorithm, and computational complexity has not significantly improved.