In multiple sensor extended target tracking problems, asynchronous measurements are inevitable, since sensors usually have distinct sampling rates and initial sampling times. This paper presents a new distributed extended target tracking algorithm with asynchronous measurements for multiple sensor scenarios. A distributed Bayesian estimation scheme for asynchronous measurements using random matrix framework is derived. We also proposed an effective implementation using particle filtering. Compressed Gaussian Mixture approximations of extended state distributions are exchanged and fused between neighbor sensors. The temporal evolution of elliptic extent parameters can be obtained explicitly in our algorithm. Simulations show reasonable performance with a significant reduction of communication costs for small size systems compared with the centralized algorithm.

中文翻译：

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使用分布式测量扩展目标跟踪的随机矩阵方法

在多传感器扩展目标跟踪问题中，异步测量是不可避免的，因为传感器通常具有不同的采样率和初始采样时间。本文提出了一种新的分布式扩展目标跟踪算法，具有针对多个传感器场景的异步测量。导出了一种使用随机矩阵框架进行异步测量的分布式贝叶斯估计方案。我们还提出了使用粒子滤波的有效实现。扩展状态分布的压缩高斯混合近似在相邻传感器之间交换和融合。椭圆范围参数的时间演化可以在我们的算法中明确获得。