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针对多传感器协同探测多个低可观测目标问题,提出一种基于强度叠加的多传感器高斯混合概率假设密度(SIM-GM-PHD)滤波器,并提出目标状态的两步提取策略.首先,利用跟踪门对预测强度函数中每个高斯分量选择有效传感器集合;然后,利用各传感器量测数据更新其对应的高斯分量,叠加所有传感器的局部后验强度以及全局漏检强度得到融合后验强度;最后,提出目标状态的两步提取策略对目标的个数与状态进行估计.仿真结果验证了所提出算法的有效性.
Aimed at the problem of multi-sensor cooperative detection of multiple low-observable targets, a multi-sensor Gaussian mixture probability hypothesis density (SIM-GM-PHD) filter based on intensity superposition is proposed and a two-step target extraction strategy is proposed.Firstly, Then, the corresponding Gaussian components are updated with each sensor measurement data, the local posterior strength of all sensors is superposed, and the global leakage strength is superposed to obtain the fusion posterior strength; Finally, the two-step strategy of target state is proposed to estimate the number and state of the target.The simulation results verify the effectiveness of the proposed algorithm.