{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:28:39Z","timestamp":1740202119669,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>The probability of flight conflict is increased because of the increasing of flight flow and uncertainty of flight route. Considering the problem that redundant operation which caused by a large number of non-related targets. A preprocessing algorithm before conflict detection was proposed. Aircrafts within the surveillance scope of Automatic Dependent Surveillance-Broadcast (ADS-B) IN were divided into 26 different regions, and the correlation between targets was distinguished by special rule of each region. Then the correlated targets were further processed, but uncorrelated ones were blocked. So the calculation of conflict analysis for surveilling surrounding targets was decreased. Above all, the processing principle that security first should be followed, and rather false alarm but never leakage alarm. Finally, the necessity and validity of the proposed algorithm is examined by using Monte Carlo experiment. The simulation results show that not less than 30% of 30 random objects are blocked. The proposed algorithm is effective and accurate for detecting the correlation of them.<\/jats:p>","DOI":"10.3233\/978-1-61499-785-6-8","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:26:53Z","timestamp":1740133613000},"source":"Crossref","is-referenced-by-count":0,"title":["A Preprocessing Algorithm Before Conflict Detection Based on Hybrid Surveillance"],"prefix":"10.3233","author":[{"family":"Wang Yu-bo","sequence":"additional","affiliation":[]},{"family":"Wang Hai-jun","sequence":"additional","affiliation":[]},{"family":"Jiao Wei-dong","sequence":"additional","affiliation":[]},{"family":"Zhou Bo","sequence":"additional","affiliation":[]},{"family":"Shen Xiao-yun","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Information Technology and Intelligent Transportation Systems"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:37:21Z","timestamp":1740137841000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-784-9&spage=8&doi=10.3233\/978-1-61499-785-6-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-785-6-8","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2017]]}}}