Track Extraction for Accelerated Targets in Dense Environments Using Variable Gating MLPDA

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概要

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• MLPDA (Maximum Likelihood Probabilistic Data Association) has attracted a great deal of attention as an effective target track extraction method in high false density environments. However, to extract an accelerated target track on a 2-dimensional plane, the computational load of the conventional MLPDA is extremely high, since it needs to search for the most-likely position, velocity and acceleration of the target in 6-dimensional space. In this paper, we propose VG-MLPDA (Variable Gating MLPDA), which consists of the following two steps. The first step is to search the target's position and velocity among candidates with the assumed acceleration by using variable gates, which take into account both the observation noise and the difference between assumed and true acceleration. The second step is to search the most-likely position, velocity and acceleration using a maximization algorithm while reducing the gate volume. Simulation results show the validity of our method.

著者

• Kameda Hiroshi

  Information Technology R & D Center Mitsubishi Electric Corporation

• Matsuzaki Takashi

  Information Technology R & D Center Mitsubishi Electric Corporation

• MORI Masanori

  Information Technology R&D Center, Mitsubishi Electric Corporation

• UMEZAWA Toru

  Kamakura Works, Mitsubishi Electric Corporation

関連論文

• A Target Positioning Algorithm Using Asynchronous TDOA/FDOA Measurements in the Distributed Sensor Network(WSANE 2008 (Workshop for Space, Aeronautical and Navigational Electronics))
• A Method of Judging Target Extinction Using PDA Tracking, Vol.J86-B,No.3, pp.536-551
• Maximum Likelihood Track Extraction Using Sliding Window in High False Density Environments(ICSANE 2012 (International Conference on Space, Aeronautical and Navigational Electronics))
• Track Extraction for Accelerated Targets in Dense Environments Using Variable Gating MLPDA

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