loading page

Robust CPHD Fusion for Distributed Multitarget Tracking Using Asynchronous Sensors
  • Benru Yu ,
  • Tiancheng Li ,
  • Hong Gu
Benru Yu
Nanjing University Of Science and Technology, Nanjing University Of Science and Technology

Corresponding Author:[email protected]

Author Profile
Tiancheng Li
Author Profile


This paper concentrates on tracking multiple targets using an asynchronous network of sensors with different sampling rates. First, a timely fusion approach is proposed for handling measurements from asynchronous sensors. In the proposed approach, the arithmetic average fusion of the estimates provided by local cardinalized probability hypothesis density filters is recursively carried out according to the network-wide sampling time sequence. The corresponding intersensor communication is conducted by a partial flooding protocol, in which either cardinality distributions or intensity functions pertinent to local posteriors are disseminated among sensors. Moreover, both feedback and non-feedback fusion-filtering modes are provided to meet the performance and real-time requirements, respectively. Second, an extension of the timely fusion approach referred to as robust bootstrap approach is presented, which can deal with unknown clutter and detection parameters by exploiting a local bootstrap filtering scheme. Finally, numerical simulations are performed to test the proposed approaches.
01 Jan 2022Published in IEEE Sensors Journal volume 22 issue 1 on pages 1030-1040. 10.1109/JSEN.2021.3128226