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针对超高速强机动目标运动模型难以准确建立且观测数据易出现不良量测而导致滤波发散的问题,提出一种适用于超高速强机动目标的跟踪算法。该算法根据正交性原理推导了一种新的强跟踪平方根容积卡尔曼滤波(ST-SRCKF)结构,并引入多重渐消因子,渐消因子求解方法和作用位置均不同于已有的ST-SRCKF。根据新息的统计学特性,即新息协方差矩阵的迹服从卡方分布,建立了一种改进的CS-Jerk模型,该模型对目标机动的描述更准确,它与改进ST-SRCKF算法的结合实现了对超高速强机动目标的高精度跟踪。仿真结果表明,改进算法对超高速强机动目标的跟踪性能更佳。
Aiming at the problem that the moving model of high-speed and high-speed maneuvering target can not be established accurately and the observation data is prone to be poorly measured, the filtering algorithm is proposed. The algorithm derives a new ST-SRCKF structure based on the orthogonality principle and introduces multiple fading factors. The fading factor solving method and action location are different from the existing ST- SRCKF. According to the statistical characteristics of interest, that is, the covariance matrix of interest covariance matrix from the chi-square distribution, an improved CS-Jerk model is established, which describes the target maneuver more accurately. Compared with the modified ST-SRCKF algorithm Combined with the realization of the high-speed high-speed maneuvering target tracking. The simulation results show that the improved algorithm has better tracking performance for high speed and high maneuvering targets.