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Liu Quanzhou, Jia Pengfei, Li Zhanqi, Wang Qipei, Wang Shuyong. Research on Vehicle Radar Data Processing with Improved Interactive Kalman Filter[J]. Mechanical Science and Technology for Aerospace Engineering. doi: 10.13433/j.cnki.1003-8728.20200111
Citation: Liu Quanzhou, Jia Pengfei, Li Zhanqi, Wang Qipei, Wang Shuyong. Research on Vehicle Radar Data Processing with Improved Interactive Kalman Filter[J]. Mechanical Science and Technology for Aerospace Engineering. doi: 10.13433/j.cnki.1003-8728.20200111

Research on Vehicle Radar Data Processing with Improved Interactive Kalman Filter

doi: 10.13433/j.cnki.1003-8728.20200111
  • Received Date: 2020-02-11
    Available Online: 2020-12-29
  • In order to reduce the influence of noise on millimeter wave radar data, an interactive Kalman filter algorithm is used to process the collected data and the optimal value of the data is obtained. The motion state equation of the target vehicle was constructed according to its motion trajectory, and the state matrix and observation matrix in different states were determined. Interactive multi-model filter was designed. The virtual traffic scene was built with dSPACE scene simulation software. The data acquisition of moving targets was realized with hardware-in-the-loop technology, and the radar data noise was analyzed and calculated. During the filtering process, the genetic algorithm was used to continuously optimize the process noise and measurement noise. The filtering performance of the algorithm was verified by the set target motion trajectory. The average error of the radar data obtained by the filtering algorithm was less than 0.1 m. The noise of the radar data was reduced, the positioning and tracking capabilities of the target vehicle were improved.
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