{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T10:48:12Z","timestamp":1761648492610,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2017,11,13]],"date-time":"2017-11-13T00:00:00Z","timestamp":1510531200000},"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>Automatic Dependent Surveillance\u2013Broadcast (ADS-B) is the direction of airspace surveillance development. Research analyzing the benefits of Traffic Collision Avoidance System (TCAS) and ADS-B data fusion is almost absent. The paper proposes an ADS-B minimum system from ADS-B In and ADS-B Out. In ADS-B In, a fusion model with a variable sampling Variational Bayesian-Interacting Multiple Model (VSVB-IMM) algorithm is proposed for integrated display and an airspace traffic situation display is developed by using ADS-B information. ADS-B Out includes ADS-B Out transmission based on a simulator platform and an Unmanned Aerial Vehicle (UAV) platform. This paper describes the overall implementation of ADS-B minimum system, including theoretical model design, experimental simulation verification, engineering implementation, results analysis, etc. Simulation and implementation results show that the fused system has better performance than each independent subsystem and it can work well in engineering applications.<\/jats:p>","DOI":"10.3390\/s17112611","type":"journal-article","created":{"date-parts":[[2017,11,13]],"date-time":"2017-11-13T11:12:36Z","timestamp":1510571556000},"page":"2611","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Integrated Display and Simulation for Automatic Dependent Surveillance\u2013Broadcast and Traffic Collision Avoidance System Data Fusion"],"prefix":"10.3390","volume":"17","author":[{"given":"Yanran","family":"Wang","sequence":"first","affiliation":[{"name":"School of Aeronautics and Astronautics, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China"}]},{"given":"Gang","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Aeronautics and Astronautics, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China"}]},{"given":"Zhouyun","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Aeronautics and Astronautics, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,11,13]]},"reference":[{"key":"ref_1","unstructured":"Aeronautics, R.T.C.F. (2006). Minimum Aviation System Performance Standards for Automatic Dependent Surveillance Broadcast (ADS-B), RTCA Incorporated. RTCA-DO-242A."},{"key":"ref_2","unstructured":"Aeronautics, R.T.C.F. (2009). Minimum Operational Performance Standards for Traffic Alert and Collision Avoidance System II (TCAS II), RTCA Incorporated. RTCA-DO-185B."},{"key":"ref_3","unstructured":"Kunzi, F. (2011). ADS-B Benefits to General Aviation and Barriers to Implementation. [Ph.D. Dissertation, Massachusetts Institute of Technology]."},{"key":"ref_4","first-page":"277","article-title":"The traffic alert and collision avoidance system","volume":"16","author":"Kuchar","year":"2007","journal-title":"Linc. Lab. J."},{"key":"ref_5","first-page":"11","article-title":"An adaptive sampling VB-IMM based on ADS-B for TCAS Data fusion with benefit analysis","volume":"49","author":"Dai","year":"2017","journal-title":"J. Aeronaut. Astronaut. Aviat."},{"key":"ref_6","unstructured":"Wang, X.G. (2014). The Design and Implementation of Air Traffic Control System Based on ADS-B Technology. [Master\u2019s Thesis, University of Electronic Science and Technology of China]."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.ijcip.2011.06.001","article-title":"Security analysis of the ADS-B implementation in the next generation air transportation system","volume":"4","author":"Mccallie","year":"2011","journal-title":"Int. J. Crit. Infrastruct. Prot."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Mueller, K.T., and Krozel, J. (2000, January 14\u201317). Aircraft ADS-B intent verification based on a Kalman tracking filter. Proceedings of the AIAA Guidance, Navigation and Control Conference, Dever, CO, USA.","DOI":"10.2514\/6.2000-4067"},{"key":"ref_9","first-page":"33","article-title":"The CPR algorithm of 1090es automatic dependent surveillance\u2014Broadcast (ADS-B) system","volume":"28","author":"Peng","year":"2010","journal-title":"J. Civ. Aviat. China"},{"key":"ref_10","unstructured":"Purton, L., Abbass, H., and Alam, S. (2010). Identification of ADS-B System Vulnerabilities and Threats, Australian Transport Research Forum."},{"key":"ref_11","first-page":"218","article-title":"Research on ADS-B and TCAS II data fusion algorithm","volume":"51","author":"Ni","year":"2015","journal-title":"Comput. Eng. Appl."},{"key":"ref_12","first-page":"1154","article-title":"Data fusion algorithm of TCAS and ADS-B combined monitoring system based on current statistical model","volume":"53","author":"Xu","year":"2013","journal-title":"Telecommun. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Ramasamy, S., Sabatini, R., and Gardi, A. (2014, January 29\u201330). Avionics sensor fusion for small size unmanned aircraft sense-and-avoid. Proceedings of the 2014 IEEE Metrology for Aerospace (MetroAeroSpace), Benevento, Italy.","DOI":"10.1109\/MetroAeroSpace.2014.6865933"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"355","DOI":"10.4028\/www.scientific.net\/AMM.629.355","article-title":"A laser obstacle warning and avoidance system for unmanned aircraft sense-and-avoid","volume":"629","author":"Sabatini","year":"2014","journal-title":"Appl. Mech. Mater."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Chen, R.H., Gevorkian, A., Fung, A., Chen, W.-Z., and Raska, V. (2011, January 29\u201331). Multi-sensor data integration for autonomous sense and avoid. Proceedings of the AIAA Infotech@Aerospace Technical Conference, St. Louis, MO, USA.","DOI":"10.2514\/6.2011-1479"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1109\/7.640267","article-title":"Interacting multiple model methods in target tracking: A survey","volume":"34","author":"Mazor","year":"1998","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Lu, Y., Liu, C., and Liu, P. (2012, January 29\u201331). An improved tracking method based on data mining in ADS-B for surface surveillance. Proceedings of the 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Chongqing, China.","DOI":"10.1109\/FSKD.2012.6233884"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Jaakkola, T. (2001). 10 tutorial on variational approximation methods. Advanced Mean Field Methods: Theory and Practice, MIT Press.","DOI":"10.7551\/mitpress\/1100.003.0014"},{"key":"ref_19","unstructured":"Beal, M.J. (2003). Variational Algorithms for Approximate Bayesian Inference. [Ph.D. Thesis, University of London]."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1109\/TAC.2008.2008348","article-title":"Recursive noise adaptive kalman filtering by variational bayesian approximations","volume":"54","author":"Sarkka","year":"2009","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/S1005-8885(13)60016-3","article-title":"Maneuvering target tracking by adaptive statistics model","volume":"20","author":"Jin","year":"2013","journal-title":"J. China Univ. Posts Telecommun."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2184","DOI":"10.1049\/iet-cta.2009.0583","article-title":"New interacting multiple model algorithms for the tracking of the manoeuvring target","volume":"4","author":"Fu","year":"2010","journal-title":"IET Control Theory Appl."},{"key":"ref_23","first-page":"1195","article-title":"Information fusion Kalman filter with complex coloured noise for descriptor systems","volume":"34","author":"Song","year":"2013","journal-title":"Chin. J. Sci. Instrum."},{"key":"ref_24","unstructured":"Zhou, H. (1991). Maneuvering Target Tracking, National Defense Industry Press."},{"key":"ref_25","first-page":"026","article-title":"An improved target tracking algorithm based on the \u201ccurrent\u201d statistical model","volume":"2","author":"Li","year":"2008","journal-title":"J. Proj. Rockets Missiles Guid."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.csda.2014.10.006","article-title":"Adaptive metropolis algorithm using variational bayesian adaptive kalman filter","volume":"83","author":"Mbalawata","year":"2015","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"986","DOI":"10.1109\/TAES.2005.1541443","article-title":"Imm estimator versus optimal estimator for hybrid systems","volume":"41","author":"Challa","year":"2005","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Mallick, M., and La Scala, B.F. (2006, January 10\u201313). IMM estimator for ground target tracking with variable measurement sampling intervals. Proceedings of the 2006 9th International Conference on Information Fusion, Florence, Italy.","DOI":"10.1109\/ICIF.2006.301763"},{"key":"ref_29","unstructured":"Hempe, D. (2010). Airworthiness Approval of Automatic Dependent Surveillance-Broadcast (ADS-B) Out Systems."},{"key":"ref_30","unstructured":"Gu, B. (2012). The Simulation Algorithm of Civil Aircraft\u2019s Air Traffic Collision Avoidance System. [Master\u2019s Thesis, Shanghai Jiaotong University]."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2611\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:49:17Z","timestamp":1760208557000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2611"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,13]]},"references-count":30,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2017,11]]}},"alternative-id":["s17112611"],"URL":"https:\/\/doi.org\/10.3390\/s17112611","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2017,11,13]]}}}