{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T14:50:24Z","timestamp":1779893424802,"version":"3.53.1"},"reference-count":30,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T00:00:00Z","timestamp":1681776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science and Technology (MOST)","award":["MOST 111-2221-E-324-018"],"award-info":[{"award-number":["MOST 111-2221-E-324-018"]}]},{"name":"Ministry of Science and Technology (MOST)","award":["MOST-111-2637-E-150-001"],"award-info":[{"award-number":["MOST-111-2637-E-150-001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>In wireless sensor networks (WSNs), the target positioning and tracking are very important topics. There are many different methods used in target positioning and tracking, for example, angle of arrival (AOA), time of arrival (TOA), time difference of arrival (TDOA), and received signal strength (RSS). This paper uses an artificial fish swarm algorithm (AFSA) and the received signal strength indicator (RSSI) channel model for indoor target positioning and tracking. The performance of eight different method combinations of fixed or adaptive steps, the region segmentation method (RSM), Hybrid Adaptive Vision of Prey (HAVP) method, and a Dynamic AF Selection (DAFS) method proposed in this paper for target positioning and tracking is investigated when the number of artificial fish is 100, 72, 52, 24, and 12. The simulation results show that using the proposed HAVP total average positioning error is reduced by 96.1%, and the positioning time is shortened by 26.4% for the target position. Adopting HAVP, RSM, and DAFS in target tracking, the positioning time can be greatly shortened by 42.47% without degrading the tracking success rate.<\/jats:p>","DOI":"10.3390\/info14040246","type":"journal-article","created":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T05:18:13Z","timestamp":1681795093000},"page":"246","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Target Positioning and Tracking in WSNs Based on AFSA"],"prefix":"10.3390","volume":"14","author":[{"given":"Shu-Hung","family":"Lee","sequence":"first","affiliation":[{"name":"School of Intelligent Manufacturing and Automotive Engineering, Guangdong Business and Technology University, Zhaoqing 526020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6656-8921","authenticated-orcid":false,"given":"Chia-Hsin","family":"Cheng","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National Formosa University, Yunlin 632301, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chien-Chih","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National Formosa University, Yunlin 632301, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3337-3551","authenticated-orcid":false,"given":"Yung-Fa","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Engineering, Chaoyang University of Technology, Taichung 413310, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,18]]},"reference":[{"key":"ref_1","unstructured":"Rajaravivarma, V., Yang, Y., and Yang, T. (2003, January 16\u201318). An overview of Wireless Sensor Network and applications. Proceedings of the 35th Southeastern Symposium on System Theory, Morgantown, WV, USA."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1903","DOI":"10.1109\/JPROC.2010.2068530","article-title":"Environmental Wireless Sensor Networks","volume":"98","author":"Corke","year":"2010","journal-title":"IEEE"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Suo, H., Wan, J., Huang, L., and Zou, C. (2012, January 23\u201325). Issues and Challenges of Wireless Sensor Networks Localization in Emerging Applications. Proceedings of the 2012 International Conference on Computer Science and Electronics Engineering, Hangzhou, China.","DOI":"10.1109\/ICCSEE.2012.44"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1109\/TMC.2011.262","article-title":"Target Tracking and Mobile Sensor Navigation in Wireless Sensor Networks","volume":"12","author":"Xu","year":"2011","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_5","first-page":"1","article-title":"Wireless Sensor Networks Localization Algorithms: A Comprehensive Survey","volume":"5","author":"Mesmoudil","year":"2013","journal-title":"Int. J. Comput. Netw. Commun."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1155\/2012\/962523","article-title":"A Survey of Localization in Wireless Sensor Network","volume":"8","author":"Cheng","year":"2012","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"La, H.-M., Nguyen, T.-H., Hguyen, C.-H., and Nguyen, H.N. (2009, January 11\u201314). Optimal Flocking Control for a Mobile Sensor Network Based a Moving Target Tracking. Proceedings of the IEEE International Conference on System, Man, and Cybernetics, San Antonio, TX, USA.","DOI":"10.1109\/ICSMC.2009.5346069"},{"key":"ref_8","unstructured":"Laaraiedh, M., Yu, L., Avrillon, S., and Uguen, B. (2011, January 27\u201329). Comparison of Hybrid Localization Schemes using RSSI, TOA, and TDOA. Proceedings of the IEEE Wireless Conference 2011-Substainalbe Wireless Technologies (European Wireless) 11th Europeanm, Vanna, Austria."},{"key":"ref_9","first-page":"1099","article-title":"Indoor Robot Localization Based on Wireless Sensor Networks","volume":"57","author":"Cheng","year":"2011","journal-title":"IEEE Trans. Comput. Electron."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Chugunov, A., Petukhov, N., and Kulikov, R. (2020, January 6\u201312). ToA Positioning Algorithm for TDoA System Architecture. Proceedings of the International Russian Automation Conference (RusAutoCon), Sochi, Russia.","DOI":"10.1109\/RusAutoCon49822.2020.9208169"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ahmed, S., Abbasi, A., and Liu, H. (2021, January 4\u20137). A Novel Hybrid AoA and TDoA Solution for Transmitter Positioning. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Barcelona, Spain.","DOI":"10.1109\/IPIN51156.2021.9662606"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"399","DOI":"10.14257\/ijca.2014.7.8.36","article-title":"Three-dimentional Sensor Node Localization based on AFSA-LSSVM","volume":"7","author":"Xu","year":"2014","journal-title":"Int. J. Control. Autom."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"64","DOI":"10.3991\/ijoe.v12i1.5180","article-title":"A Novel WSNs Localization Algorithm Based on Artificial Fish Swarm Algorithm","volume":"12","author":"Yang","year":"2016","journal-title":"Int. J. Online Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"106102","DOI":"10.1117\/1.OE.57.10.106102","article-title":"High-precision indoor three-dimensional positioning system based on visible light communication using modified artificial fish swarm algorithm","volume":"57","author":"Wen","year":"2018","journal-title":"Opt. Eng."},{"key":"ref_15","first-page":"32","article-title":"An Optimizing Method Based on Autonomous Animats: Fish-swarm Algorithm","volume":"22","author":"Li","year":"2002","journal-title":"Chin. J. Circuits Syst."},{"key":"ref_16","first-page":"1","article-title":"Studies on Artificial Fish Swarm Optimization Algorithm based on Decomposition and Coordination Techniques","volume":"8","author":"Li","year":"2003","journal-title":"Chin. J. Syst. Eng. Theory Pract."},{"key":"ref_17","unstructured":"Shan, X.-J., Jiang, M.-Y., and Li, J.-P. (2006, January 21\u201323). The Routing Optimization Based on Improved Artificial Fish Swarm Algorithm. Proceedings of the 6th World Congress on Intelligent Control and Automation, Dalian, China."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"He, S., Hamam, N.B.H., and Bouslimani, Y. (2009, January 24\u201326). Fuzzy Clustering with Improved Artificial Fish Swarm Algorithm. Proceedings of the International Joint Conference on Computational Sciences and Optimization, Sanya, China.","DOI":"10.1109\/CSO.2009.367"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Jiang, M.-Y., Yuan, D.-F., and Cheng, Y.-M. (2009, January 14\u201316). Improved Artificial Fish Swarm Algorithm. Proceedings of the Fifth International Conference on Natural Computation, Tianjin, China.","DOI":"10.1109\/ICNC.2009.343"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Cheng, Y.-M., Jiang, M.-Y., and Yuan, D. (2009, January 14\u201316). Novel Clustering Algorithm Based on Improved Artificial Fish Swarm Algorithm. Proceedings of the FSK 09. Sixth International Conference on Fuzzy System and Knowledge Discovery, Tianjin, China.","DOI":"10.1109\/FSKD.2009.534"},{"key":"ref_21","unstructured":"Fernandes, E.M.G.P., Martins, T.F.M.C., and Rocha, A.M.A.C. (July, January 30). Fish Swarm Algorithm for Bound Constrained Global Optimization. Proceedings of the International Conference on Computational and Mathematical Methods in Science and Engineering, Asturias, Spain."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhang, C., Zhang, F.-M., Li, F., and Wu, H.-S. (2014, January 9\u201311). Improved Artificial Fish Swarm Algorithm. Proceedings of the 9th IEEE Conference on Industrial Electronics and Applications, Hangzhou, China.","DOI":"10.1109\/ICIEA.2014.6931262"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1007\/s10462-012-9342-2","article-title":"Artificial fish swarm algorithm: A survey of the state-of-the-art, hybridization, combinatorial and indicative applications","volume":"42","author":"Neshat","year":"2014","journal-title":"Artif. Intell. Rev."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Fang, Z., Zhao, Z., Geng, D., Xuan, Y.-D., Du, L.-D., and Cui, X.-X. (2010, January 20\u201323). RSSI Variability Characterization and Calibration Method in Wireless Sensor Network. Proceedings of the IEEE International Conference on Information and Automation, Harbin, China.","DOI":"10.1109\/ICINFA.2010.5512318"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Xiong, J.-Q., Qin, Q., and Zheng, K.-M. (2014, January 13\u201314). A Distant Measurement Wireless Localization Correction Algorithm Based on RSSI. Proceedings of the Seventh International Symposium on Computation Intelligence and Design, Hangzhou, China.","DOI":"10.1109\/ISCID.2014.246"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Barsocchi, P., Lenzi, S., Chessa, S., and Giunta, G. (2009, January 26\u201329). A Novel Approach to Indoor RSSI Localization by Automatic Calibration of the Wireless Propagation Model. Proceedings of the IEEE 69th Vehicular Technology Conference, Barcelona, Spain.","DOI":"10.1109\/VETECS.2009.5073315"},{"key":"ref_27","unstructured":"Mahmud, M.I., Abdelgawad, A., Yanambaka, V.P., and Yelamarthi, K. (July, January 14). Packet Drop and RSSI Evaluation for LoRa: An Indoor Application Perspective. Proceedings of the IEEE 7th World Forum on Internet of Things (WF-IoT), New Orleans, LA, USA."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Yao, L., Peng, X., Shi, D., and Liu, B. (2021, January 9\u201311). Design of Indoor Positioning System Based on RSSI Algorithm. Proceedings of the International Conference on Management Science and Software Engineering (ICMSSE), Chengdu, China.","DOI":"10.1109\/ICMSSE53595.2021.00039"},{"key":"ref_29","unstructured":"Hu, X.T., Zhang, H.Q., Li, Z.C., Huang, Y.A., and Yin, Z.P. (2013, January 10\u201312). A Novel Self-Adaptation Hybrid Artificial Fish-Swarm Algorithm. Proceedings of the 2013 IFAC, Hangzhou, China."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Lee, S.-H., Cheng, C.-H., Lin, C.-C., and Huang, Y.-F. (2023). PSO-Based Target Localization and Tracking in Wireless Sensor Networks. Electronics, 12.","DOI":"10.3390\/electronics12040905"}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/14\/4\/246\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:18:05Z","timestamp":1760123885000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/14\/4\/246"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,18]]},"references-count":30,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["info14040246"],"URL":"https:\/\/doi.org\/10.3390\/info14040246","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,18]]}}}