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To overcome this problem, we introduce the modified current statistical (MCS) model, which incorporates the input-acceleration transition matrix into the augmented state transition matrix, to predict the motion state of a maneuvering target. Based on this, a robust resource allocation strategy is developed for maneuvering target tracking (MTT) in a netted opportunistic array radar (OAR) system under uncertain conditions. The mechanism of the strategy is to minimize the total transmitting power conditioned on the desired tracking performance. The predicted conditional Cram\u00e9r\u2013Rao lower bound (PC-CRLB) is deemed as the optimization criterion, which is derived based on the recently received measurement so as to provide a tighter lower bound than the posterior CRLB (PCRLB). For the uncertainty of the target reflectivity, we encapsulate the determined resource allocation model with chance-constraint programming (CCP) to balance resource consumption and tracking performance. A hybrid intelligent optimization algorithm (HIOA), which integrates a stochastic simulation and a genetic algorithm (GA), is employed to solve the CCP problem. Finally, simulations demonstrate the efficiency and robustness of the presented algorithm.<\/jats:p>","DOI":"10.3390\/rs16183499","type":"journal-article","created":{"date-parts":[[2024,9,23]],"date-time":"2024-09-23T09:15:07Z","timestamp":1727082907000},"page":"3499","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Resource Allocation of Netted Opportunistic Array Radar for Maneuvering Target Tracking under Uncertain Conditions"],"prefix":"10.3390","volume":"16","author":[{"given":"Qinghua","family":"Han","sequence":"first","affiliation":[{"name":"School of Electronics & Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"College of Artificial Intelligence, Zaozhuang University, Zaozhuang 277160, China"},{"name":"Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weijun","family":"Long","sequence":"additional","affiliation":[{"name":"School of Electronics & Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Zaozhuang University, Zaozhuang 277160, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xishang","family":"Dong","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Zaozhuang University, Zaozhuang 277160, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1703-4218","authenticated-orcid":false,"given":"Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electronics & Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiheng","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Precision Instrument, School of Mechanical Engineering, Tsinghua University, Beijing 100084, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,20]]},"reference":[{"key":"ref_1","unstructured":"Kocaman, \u0130. 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