近似粒子滤波中的error propagation分析
Analysis of error propagation in particle filters with approximation
摘要：
本文探讨了在资源受限的平台上实现粒子滤波器时所需的近似步骤的影响。我们认为粒子滤波器执行间歇性近似，无论是通过子采样的粒子或通过生成一个参数近似。对于这样的算法，我们推导出时间一致的弱意义上的$L_p$错误的界限，并提出相关的指数不等式。我们激励的理论分析，考虑领导节点的粒子滤波器和目前的数值实验探索其性能和误差界的关系。
英文摘要：
This paper examines the impact of approximation steps that become necessary when particle filters are implemented on resource-constrained platforms. We consider particle filters that perform intermittent approximation, either by subsampling the particles or by generating a parametric approximation. For such algorithms, we derive time-uniform bounds on the weak-sense $L_p$ error and present associated exponential inequalities. We motivate the theoretical analysis by considering the leader node particle filter and present numerical experiments exploring its performance and the relationship to the error bounds.
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