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Distributed Asynchronous Extended Target Tracking Using Random Matrix
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DOI：10.1109/JSEN.2019.2944280.png)
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Abstract
En 中文
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.
Keywords:
Random matrix model
extended target tracking
asynchronous measurements
state estimation
multiple sensors
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