基于距离检测的自动识别系统和对海雷达航迹抗差关联算法

齐林; 崔亚奇; 熊伟; 王聪

doi:10.11999/JEIT141472

基于距离检测的自动识别系统和对海雷达航迹抗差关联算法

doi: 10.11999/JEIT141472

基金项目:

山东省自然科学基金青年基金(ZR2012FQ004)和飞行器测控与通信教育部重点实验室开放基金(CTTC-FX201302)

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- 被引次数: 0
出版历程
- 收稿日期: 2014-11-24
- 修回日期: 2015-04-10
- 刊出日期: 2015-08-19

Anti-bias Association Algorithm for Automatic Identification System and Radar Based on Bias Detection

摘要

摘要: 现有的多传感器航迹抗差关联算法，如基于图像配准技术、基于参照拓扑关系的关联算法，计算流程复杂，难以在工程实践中实时应用。该文结合海面舰船目标航迹分布特点，基于单元平均恒虚警检测原理，提出了适用于自动识别系统(AIS)和雷达航迹数据的可信关联算法，为对海雷达系统误差配准和海战场多传感器信息融合的快速有效实现提供保证。蒙特卡洛仿真结果表明，可信关联算法在海面目标环境下具有较高的关联准确性；算法的平均耗时与现有抗差关联算法相比显著降低；基于航迹可信关联结果完成对雷达的自动标校，将雷达量测数据的平均误差降低了近90%。
- 对海雷达 /
- 抗差关联 /
- 自动识别系统 /
- 单元平均恒虚警检测 /
- 实时性
Abstract: The classical multi-sensor anti-bias association algorithms require complex calculation procedure, can not be used in real-time condition, for instance the algorithms based on image matching and reference topology feature. On the basis of tracks distribution feature on sea surface and Cell-Average Constant False Alarm Rate (CA-CFAR) detection theory, a real-time anti-bias association algorithm for Automatic Identification System (AIS) and the data track of radar is proposed, named confidential-association algorithm, to make real-time radar systematic error registration and multi-sensor information fusion come true. Monte-Carlo simulation results show that the accuracy of confidential-association algorithm maintains on a high level on the sea-surface environment, it has the superiority of simply calculation procedure and substantially reduces run-time in comparison to current anti-bias association algorithms. Radar automatically registration technique based on confidential-association algorithm reduces average error of the measured data by nearly 90%.
- Radar for sea /
- Anti-bias association /
- Automatic Identification System (AIS) /
- Cell-Average Constant False Alarm Rate (CA-CFAR) detection /
- Real-time

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