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Adaptive passive sensor selection for maneuvering target localization and tracking using a multisensor surveillance system

Hosseini, S. N ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1080/23311916.2020.1798580
  3. Publisher: Cogent OA , 2020
  4. Abstract:
  5. This paper investigates maneuvering-target tracking problem based on a multisensor system and interacting multiple model (IMM). The estimation is performed by a novel particle filter (PF) with a capability to deal with the state-dependent noises and interference of the sensors’ coverage environment. An adaptive sensor selection algorithm, where some sensors are selected in each stage based on the signal-to-interference pulse noise ratio (SINR) and participate in the state estimation, is proposed. To deal with the effect of interference, we focus on designing and implementing the sensor selection algorithm, where a multisensor system with nonuniform arrays is derived by solving a convex optimization problem. On this basis, a nonuniform array of sensors is selected in each time interval aiming at maximizing the SINR of the received information from the undercoverage area. This would allow tracking in practical environments experiences interference. This method also is able to reduce the tracking error rate. © 2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license
  6. Keywords:
  7. Adaptive sensor selection ; Interacting multiple models ; Interference ; Maneuvering target tracking ; Particle filter ; SINR maximization
  8. Source: Cogent Engineering ; Volume 7, Issue 1 , 2020
  9. URL: https://www.tandfonline.com/doi/full/10.1080/23311916.2020.1798580