A Track Correlation Algorithm Based on New Space-time Cross-point Feature
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摘要: 为有效解决实际工程中的航迹关联问题,该文定义了广义时空交叉点,并提出了以航迹对时空交叉点为特征,通过特征匹配来实现航迹抗差关联的新方法。实测数据验证结果表明:在雷达航迹不完全匹配且存在时空差异误差的情况下,该方法可有效实现雷达航迹的抗差关联,并且几乎不受时空差异误差大小的影响,具有强鲁棒性和稳定性,可有效解决实际工程中的航迹关联问题,消除冗余航迹,提供统一态势。
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关键词:
- 航迹关联 /
- 时空交叉点 /
- 特征匹配 /
- 假设检验 /
- Hausdorff距离
Abstract: To solve the problem of track correlation in practical engineering effectively, a new concept of generalized space-time cross point of track pair is defined in this paper. Then a new algorithm which utilize space-time cross-point as feature points and realizes the track correlation through feature point matching is proposed in this paper. The test experiments with measured data illustrate the proposed algorithm of which the performance is effective, stable and robust, can eliminate redundant tracks and provide a unified situation. -
表 1 测试数据1下傅里叶算法关联结果
雷达1批号 11 12 雷达2批号 21 22 空间误差估计(m) 580.14 878.56 580.14 878.56 表 2 测试数据1下交叉点算法关联结果
雷达1批号 15 13 11 12 雷达2批号 25 23 21 22 关联系数 0.657 0.657 0.648 0.503 时间误差估计(s) 30.31 30.31 25.42 29.57 空间误差估计(m) 525.22 819.61 525.22 819.61 571.18 813.87 468.00 825.56 表 3 测试数据2下傅里叶算法关联结果
雷达1批号 13 雷达2批号 23 空间误差估计(m) 5310.32 8605.41 表 4 测试环境2下交叉点算法关联结果
雷达1批号 13 15 14 雷达2批号 23 25 24 关联系数 0.845 0.845 0.835 时间误差估计 89.03 89.03 86.17 空间误差估计 4876.42 7953.41 4876.42 7953.41 5053.34 8036.30 表 5 测试环境3下交叉差算法关联结果
雷达1批号 17 12 11 18 14 13 16 15 雷达2批号 27 22 21 28 24 23 26 25 表 6 测试环境3下傅里叶算法关联结果
雷达1批号 11 18 16 雷达2批号 21 28 26 -
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