【摘要】 拖曳线列阵声纳是反潜战的重要船载装备,能够远距离发现水上和水下的目标,而船载ARPA雷达主要用于探测水上目标。基于此,本文研究利用拖曳线列阵声纳和ARPA雷达的信息融合,实现对探测目标的水上和水下位置的分选。首先,本研究选用分布式信息融合模型,先分别对声纳和雷达数据进行空间配准,然后使用自适应的α-β滤波算法进行时间配准,接着采用最近领域法对多目标进行航迹关联,最终实现水上与水下目标分选。通过MATLAB建模与仿真表明:与一般的方法相比较,本文提出的方法在空间复杂度和时间复杂度上表现更好,能够实时对多目标进行分选。更多还原

【Abstract】 The towed array sonar has become an important shipborne equipment in modern antisubmarine by its ability to discover water and underwater targets in a long distance. Similarly,the ARPA radar is also a vital shipborne device to detect water targets. On these basis,this paper proposes a new method to sort water and underwater targets based on information fusion of the towed array sonar and ARPA radar. First,on basis of the distributed information fusion model selected in this study,spatial registration of the data of towed array sonar and ARPA radar are separately conducted. Then,the adaptive[ α-β ]filtering algorithm and nearest domain method are used for time registration and multi-objective track association,respectively. Finally,the sorting of water and underwater targets can be effectively realized. By MATLAB modeling and simulation,it is shown that compared with general methods,the proposed method performs better in terms of spatial complexity and time complexity,and can be used to sort multi-target in real-time.更多还原