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海军大连舰艇学院,辽宁 大连 116018
警海警学院,浙江 宁波 315801
Received:08 May 2025,
Online First:25 December 2025,
Published:2026-03
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MENG Hao, ZHANG Lihua, HU Hai, et al. A Rapid Calculation Method for the Correct Target Discrimination Probability of Maritime Aircraft Terminal Guidance Radar Based on 3D Models of Marine Geographical Features[J]. Acta Armamentarii, 2026, 47(3): 250356.
MENG Hao, ZHANG Lihua, HU Hai, et al. A Rapid Calculation Method for the Correct Target Discrimination Probability of Maritime Aircraft Terminal Guidance Radar Based on 3D Models of Marine Geographical Features[J]. Acta Armamentarii, 2026, 47(3): 250356. DOI: 10.12382/bgxb.2025.0356.
针对现有海洋飞行器末制导雷达正确分辨目标概率计算方法未基于海洋地理景物(Marine Geographical Feature,MGF)三维模型考虑其对雷达视线(Line of Sight,LOS)遮挡和雷达目标粘连(Radar Target Adhesion,RTA)的综合影响,且计算速度较慢的问题,提出一种基于MGF三维模型的雷达正确分辨目标概率计算方法,并通过简化MGF数据提高计算效率。在三维空间中建立雷达正确分辨水面目标的判定标准,综合分析来自水面目标、海洋飞行器和MGF三方面的误差,最后利用蒙特卡洛法仿真计算雷达正确分辨水面目标概率,并通过简化MGF数据提升计算效率。理论推导与仿真实验结果表明:所提方法综合考虑了MGF对雷达LOS遮挡和RTA的影响,计算结果更加符合实际;MGF数据简化前后的计算结果差值平均值小于0.03,最大值小于0.09,计算时间缩短约78倍,在保证精度的基础上有效提升了计算效率。
The existing methods for calculating the correct target discrimination probability of terminal guidance radar in maritime aircraft do not take into account the combined effects of marine geographical features(MGFs)on radar line of sight(LOS)occlusion and radar target adhesion(RTA)
and their calculation speed is relatively slow A calculation method based on 3D models of MGFs is proposed for the correct target discrimination probability of terminal guidance radar
and the calculation efficiency is improved by simplifying the MGF data. Firstly
a discrimination criteria of surface targets in 3D space is established
and the errors from aircraft
target and MGF are comprehensively analyzed. Finally
the result was calculated using the Monte Carlo simulation
with the efficiency enhanced by simplifying the MGF data. Theoretical derivations and simulated results indicate that the proposed method takes into account the combined effects of MGFs on LOS occlusion and RTA
and the calculated results are more consistent with reality. The average difference between the calculated results before and after MGF data simplification is less than 0.03
the maximum value is less than 0.09
and the calculation time is reduced by about 78 times
effectively improving the calculation efficiency while ensuring accuracy.
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