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基于组合序列波动性的异步航迹关联算法

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针对传统异步航迹关联算法效率低、目标靠近传感器附近关联性能下降的问题,提出一种基于离散数据波动性的异步雷法航迹关联算法。提出分段划分方法,根据航迹长度将不等长序列转化为等长序列,以适应实际航迹轨迹的复杂变化。定义混合离散数据集的加权方差,描述同源航迹序列数据集合的波动性,以此进行关联判定。实验结果表明,与传统异步航迹关联算法相比,所提算法的正确关联率更高、耗时更低,且不受雷达随机误差分布及目标运动位置的影响,算法稳定性较强。
Asynchronous Track Association Algorithm Based on Combination Sequence Volatility
A asynchronous radar track association algorithm based on discrete data volatility is proposed to address the issues of low efficiency and decreased correlation performance near sensors of traditional algorithms.A segmentation method is proposed to convert unequal length sequences into equal length sequences based on the track length,in order to adapt the complex changing of actual tracks.The weighted variance of a mixed discrete dataset is defined for correlation judgment,describing the volatility of the same origin track sequence dataset.The experiment results show that compared with traditional asynchronous track correlation algo-rithms,the proposed algorithm has a higher correct correlation rate,lower time consumption,and is not affected by radar error dis-tribution and target motion position,with stronger stability.

track correlationasynchronous trackweighted variance

张敬艳

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海军装备部 北京 100080

航迹关联 异步航迹 加权方差

2024

舰船电子工程
中国船舶重工集团公司第709研究所 中国造船工程学会 电子技术学术委员会

舰船电子工程

CSTPCD
影响因子:0.243
ISSN:1627-9730
年,卷(期):2024.44(7)