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飞行流量增加及航迹的不确定性加大了目标间冲突的可能性,针对目标间冲突检测与解脱时大量无关联监视目标造成冗余运算问题,提出一种冲突检测前预处理方法。将ADS-B IN监视范围内的目标规划到26个区域,每一个区域中依据设定的专门规则判别目标与本机的相关性,关联目标将参与冲突检测等后续运算,无关联目标的后续处理则被阻塞。算法能有效减少本机周围交通态势安全评估时的运算量,坚持宁虚警、不漏警原则,从而确保安全为首要目标。最后通过蒙特卡罗实验检验了算法各项性能。实验表明,随机产生的30个目标中,不少于30%的目标被判定为无冲突关联而被阻塞,算法能有效检测目标间的相关性。
The increase of flight flow and the uncertainty of track increase the possibility of conflict between targets. Aiming at the redundant operation problem of a large number of uncorrelated monitoring targets in the conflict detection and release between targets, a pre-conflict detection method is proposed. The target within the ADS-B IN surveillance area is planned to 26 areas. Each area determines the relevance between the target and the local machine according to the set special rules. The related objects will participate in the follow-up operations such as conflict detection. Follow-up of unrelated targets Processing is blocked. The algorithm can effectively reduce the computational complexity of traffic situation safety assessment around this machine, and insist on using the principle of avoiding false alarms and ensuring no leakage, so as to ensure safety as the primary objective. Finally, the Monte Carlo experiment tests the performance of the algorithm. Experiments show that among 30 random targets, not less than 30% of the targets are judged to be non-conflicting and blocked, and the algorithm can effectively detect the correlation between targets.