排序方式: 共有8条查询结果,搜索用时 15 毫秒
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采用重要性重采样技术改进了标准粒子滤波算法,通过设定有效采样尺度来减少权值较小的粒子数目,在一定程度上克服了退化现象。仿真结果表明,采用PF跟踪机动目标,其跟踪精度要高于IMM,说明PF具有较强的处理非线性系统的能力;对标准PF采用重要性重采样策略后,PF的跟踪精度和平稳性都得到了进一步改善。 相似文献
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在非线性条件下,扩展Kalman 滤波( EKF)的应用最为广泛。但是,由于它采用了Taylor展开的线性变换来近似非线性模型,因而存在计算量大、实时性差、估计精度低等缺点。粒子滤波( PF)用一些带有权值的随机样本(粒子)来表示所需要的后验概率密度,并通过这些粒子的加权来估计目标运动的状态,从而得到基于物理模型的近似最优数值解,具有精度高、收敛速度快等特点。通过仿真实验将PF与EKF的性能进行了对比,并且研究了噪声协方差与粒子数对PF的影响。 PF与EKF的对比实验结果表明,在强非线性条件下,PF比EKF跟踪精度更高,误差更低。 相似文献
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在直方图重采样的基础上,以直方图拟合选取最佳阈值对经灰度化处理的印鉴图像进行二值化分割;进一步对二值化印鉴图像进行基于数学形态学的增强处理;利用修剪算法对细化的印鉴图像进行处理提取其形态学骨架;对印鉴的骨架图像进行了链码编码。 相似文献
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This study considers advanced statistical approaches for sequential data assimilation. These are explored in the context of nowcasting and forecasting using nonlinear differential equation based marine ecosystem models assimilating sparse and noisy non-Gaussian multivariate observations. The statistical framework uses a state space model with the goal of estimating the time evolving probability distribution of the ecosystem state. Assimilation of observations relies on stochastic dynamic prediction and Bayesian principles. In this study, a new sequential data assimilation approach is introduced based on Markov Chain Monte Carlo (MCMC). The ecosystem state is represented by an ensemble, or sample, from which distributional properties, or summary statistical measures, can be derived. The Metropolis-Hastings based MCMC approach is compared and contrasted with two other sequential data assimilation approaches: sequential importance resampling, and the (approximate) ensemble Kalman filter (including computational comparisons). A simple illustrative application is provided based on a 0-D nonlinear plankton ecosystem model with multivariate non-Gaussian observations of the ecosystem state from a coastal ocean observatory. The MCMC approach is shown to be straightforward to implement and to effectively characterize the non-Gaussian ecosystem state in both nowcast and forecast experiments. Results are reported which illustrate how non-Gaussian information originates, and how it can be used to characterize ecosystem properties. 相似文献
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为保证对目标轨迹跟踪的实时性,提高其精度,提出双重采样粒子滤波模型。首先,利用粒子聚合技术对状态空间的粒子权值进行加权平均处理,形成聚合粒子,使得粒子在状态空间内分布更为合理。然后,利用线性优化方法重新产生新的粒子,优化粒子在状态空间的分布特性,增加粒子的多样性,提高算法的精确性。经仿真验证,本文提出的算法较准确,鲁棒性也较高。 相似文献
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