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IMM Bernoulli Gaussian Particle Filter ?

机译:IMM Bernoulli高斯粒子滤波器

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摘要

The Bernoulli filter (BF) in the interacting multiple model (IMM) framework is proposed for detecting and tracking a maneuvering target. The BF is implemented as a particle filter and embedded in the IMM structure. The communication between the IMM and the BF is achieved through a Gaussian layer. Particles are drawn from the mixture densities at each recursion and the model likelihoods are computed from the filter innovations. Simulations show that the proposed filter outperforms the single model variant and it can effectively choose the correct motion model and estimate the state of the tracked object.
机译:建议在交互多模型(IMM)框架中的Bernoulli滤波器(BF)用于检测和跟踪机动目标。 BF被实现为颗粒过滤器并嵌入IMM结构中。 IMM和BF之间的通信通过高斯层实现。从每个递归的混合物密度绘制颗粒,并且从过滤器创新计算模型似然。模拟表明,所提出的滤波器优于单一模型变体,它可以有效地选择正确的运动模型并估计跟踪对象的状态。

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