{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:50:38Z","timestamp":1760241038923,"version":"build-2065373602"},"reference-count":11,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2019,11,15]],"date-time":"2019-11-15T00:00:00Z","timestamp":1573776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Targeted information sources include radar and ADS (Automatic Dependent Surveillance) for civil ATM (Air Traffic Management) systems, and the new navigation system based on satellites has the capability of global coverage. In order to solve the surveillance problem in mid-and-high altitude airspace and approaching airspace, this paper proposes a filter-based covariance matrix weighting method, measurement variance weighting method, and measurement-first weighted fusion method weighting integration algorithm to improve the efficiency of data integration calculation under fixed accuracy. Besides this, this paper focuses on the technology of the integration of a multi-radar surveillance system and automated related surveillance system in the ATM system and analyzes the constructional method of a multigeneration surveillance data integration system, as well as establishing the targeted model of sensors and the target track and designing the logical structure of multi-radar and ADS data integration.<\/jats:p>","DOI":"10.3390\/s19224975","type":"journal-article","created":{"date-parts":[[2019,11,15]],"date-time":"2019-11-15T11:24:32Z","timestamp":1573817072000},"page":"4975","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm"],"prefix":"10.3390","volume":"19","author":[{"given":"Yi","family":"Mao","sequence":"first","affiliation":[{"name":"State Key Laboratory of Air Traffic Management System and Technology, Nanjing 210000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4235-4769","authenticated-orcid":false,"given":"Yi","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Air Traffic Management System and Technology, Nanjing 210000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxin","family":"Hu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Air Traffic Management System and Technology, Nanjing 210000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,15]]},"reference":[{"key":"ref_1","first-page":"114","article-title":"Investigation for main problem of ADS-B implementation in ATM","volume":"15","author":"Zhang","year":"2003","journal-title":"Appl. Electron. Tech."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2984","DOI":"10.1109\/JSEN.2017.2696054","article-title":"Fusion of RSS and phase shift using the Kalman filter for RFID tracking","volume":"17","author":"Ma","year":"2017","journal-title":"IEEE Sens. J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"8669","DOI":"10.1109\/TVT.2015.2508456","article-title":"Consensus-based distributed mixture Kalman filter for maneuvering target tracking in wireless sensor networks","volume":"65","author":"Yu","year":"2016","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2984","DOI":"10.1109\/JSEN.2012.2204976","article-title":"Real-time data fusion and MEMS sensors fault detection in an aircraft emergency attitude unit based on Kalman filtering attitude unit based on Kalman filtering","volume":"12","author":"Carminta","year":"2012","journal-title":"IEEE Sens. J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1049\/iet-spr.2015.0205","article-title":"Comparison of centralized scaled unscented Kalman filter and extended Kalman filter for multisensory data fusion architectures","volume":"10","author":"Xing","year":"2016","journal-title":"IET Signal Process."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/JPHOT.2017.2780197","article-title":"Fusion of visible light indoor positioning and inertial navigation based on particle filter","volume":"9","author":"Li","year":"2017","journal-title":"IEEE Photonics J."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ristic, B., Arulampalam, S., and Gordon, N. (2004). Beyond the Kalman Filter: Particle Filters for Tracking Applications, Artech House.","DOI":"10.1155\/S1110865704405095"},{"key":"ref_8","first-page":"1518","article-title":"Particle filter-based recursive data fusion with sensor indexing for large core neutron flux estimation","volume":"64","author":"Tamboli","year":"2017","journal-title":"IEEE Trans. Nucl. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1016\/j.automatica.2007.07.024","article-title":"Box particle filtering for nonlinear state estimation using interval analysis","volume":"44","author":"Abdallah","year":"2008","journal-title":"Automatica"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2138","DOI":"10.1109\/TSP.2012.2184538","article-title":"Bernoulli particle\/box-particle filters for detection and tracking in the presence of triple measurement uncertainty","volume":"60","author":"Gning","year":"2012","journal-title":"IEEE Trans. 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Mag."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/22\/4975\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:34:40Z","timestamp":1760189680000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/22\/4975"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,15]]},"references-count":11,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["s19224975"],"URL":"https:\/\/doi.org\/10.3390\/s19224975","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,11,15]]}}}