Reduction of computational load for implementing iJIPDA filter
Yifan Xie, Hyoung Won Kim, Hyung June Kim, Taek Lyul Song · 2017
The conventional multi-target tracking (MTT) algorithms usually suffer from computational intractability problem. The appearance of Iterative Joint Integrated Probabilistic Data Association (iJIPDA) filter solves this problem by providing a tradeoff between the tracking performance and computational cost for computational resource management of sensor systems. However, the iJIPDA filter essentially involves repetitive computation which makes it impractical to perform at high levels. Thus we provide an improved iJIPDA filter which prevents repetitive computations and increases the computational efficiency such that better performances can be obtained within limited time.