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提出一种基于量测驱动的自适应目标新生强度PHD/CPHD滤波算法.该算法认为新生目标是不可检测的,有效地克服了归一化失衡问题;同时,基于量测驱动自适应设计目标新生强度,利用PHD/CPHD滤波分别递归估计存活目标和新生目标的状态及其数目.最后,在序列蒙特卡罗框架下实现了该PHD/CPHD滤波算法.算例结果表明,改进算法可以有效地实时跟踪多个机动目标的状态和数目,应用前景较好.
This paper proposes a PHD / CPHD filtering algorithm based on measurement-driven adaptive target newborn intensity, which considers that the nascent target is undetectable and effectively overcomes the normalized imbalance problem. Meanwhile, based on the measurement-driven adaptive design target newborn And the PHD / CPHD filter is used to recursively estimate the states and their numbers of surviving and newborn targets respectively.Finally, the PHD / CPHD filtering algorithm is implemented in the framework of the sequence Monte Carlo.Experimental results show that the improved algorithm can effectively implement real- Tracking the status and number of multiple maneuvering targets, the application prospect is better.