秦川, 陶忠, 桑蔚, 张鹏, 海云波, 梅甫麟. 基于粒子滤波的运动目标光电定位仿真研究[J]. 应用光学, 2020, 41(1): 10-17. DOI: 10.5768/JAO202041.0101002
引用本文: 秦川, 陶忠, 桑蔚, 张鹏, 海云波, 梅甫麟. 基于粒子滤波的运动目标光电定位仿真研究[J]. 应用光学, 2020, 41(1): 10-17. DOI: 10.5768/JAO202041.0101002
QIN Chuan, TAO Zhong, SANG Wei, ZHANG Peng, HAI Yunbo, MEI Fulin. Simulation on photoelectric positioning of moving targets based on particle filter[J]. Journal of Applied Optics, 2020, 41(1): 10-17. DOI: 10.5768/JAO202041.0101002
Citation: QIN Chuan, TAO Zhong, SANG Wei, ZHANG Peng, HAI Yunbo, MEI Fulin. Simulation on photoelectric positioning of moving targets based on particle filter[J]. Journal of Applied Optics, 2020, 41(1): 10-17. DOI: 10.5768/JAO202041.0101002

基于粒子滤波的运动目标光电定位仿真研究

Simulation on photoelectric positioning of moving targets based on particle filter

  • 摘要: 运动目标的光电定位不能像静止目标那样简单做均值滤波,鉴于此,引入粒子滤波算法,它不仅可以应用于线性系统,而且还适用于非线性系统。结合光电定位需求,详细推导了计算公式及初值和参数选取公式,对只含测量噪声以及含有测量和运动噪声等的海面运动目标光电无源定位算法进行了仿真计算,验证了算法的有效性,讨论了噪声强度对滤波效果的影响,滤波参数选择对滤波效果的影响,目标运动方式对滤波跟随性的影响,重采样算法对滤波效果的影响等。所得结论为:粒子滤波可用于运动目标光电定位过程,可有效降低定位误差;粒子滤波算法具有较强鲁棒性,适用于噪声较大、目标运动形态变化大等情况。

     

    Abstract: The photoelectric positioning of moving targets cannot do the mean filtering as simple as the stationary targets. In view of this, the particle filter algorithm was introduced, which could be applied in both linear and nonlinear systems. Firstly, based on the requirements of photoelectric positioning, the calculation formulas as well as the initial value and parameter selection formulas were deduced in detail. Secondly, the photoelectric passive positioning algorithm of sea moving targets with only measurement noise and with the measurement and motion noises was simulated, which verified the validity of algorithm. Finally, the influence of noise intensity on filtering effect, the influence of filtering parameters selection on filtering effect, the influence of target motion mode on filtering following performance and the resampling algorithms on filtering effect were discussed. The conclusions are as follows: ① the particle filter can be used in the photoelectric positioning process of moving targets to effectively reduce the positioning error; ② the particle filter algorithm has strong robustness, which is suitable for the situations such as large noise, big changes of target motion morphology, etc.

     

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