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本文研究了跟踪多个机动目标时,由滤波算法所获得的新息向量范数的统计性质,关联区域的大小以及接收正确回波的概率。借助拉蒙特卡洛方法,考察了不同的目标状态模型、目标机动加速度及状态噪声方差等因素对所研究的问题的影响。研究表明,文献[1]所提出的机动目标状态模型及相应的自适应算法具有较好的适应目标机动的能力,关联区域的大小及接收正确回波的概率均较为稳定。
In this paper, the statistical properties of the new interest vector norm obtained by the filtering algorithm, the size of the associated region and the probability of receiving the correct echo when tracking multiple maneuvering targets are studied. With the help of the Monte-Carlo method, the influences of different target state models, target maneuvering accelerations and state noise variances on the studied problems are investigated. The research shows that the maneuvering goal state model proposed by [1] and the corresponding adaptive algorithm have a good ability to adapt to the target maneuver, and the size of the associated area and the probability of receiving correct echoes are relatively stable.