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Multi-target state estimation and track continuity for the particle PHD filter

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2 Author(s)
Clark, D.E. ; Heriot-Watt Univ., Edinburgh ; Bell, J.

Particle filter approaches for approximating the first-order moment of a joint, or probability hypothesis density (PHD), have demonstrated a feasible suboptimal method for tracking a time-varying number of targets in real-time. We consider two techniques for estimating the target states at each iteration, namely k-means clustering and mixture modelling via the expectation-maximization (EM) algorithm. We present novel techniques for associating the targets between frames to enable track continuity.

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Aerospace and Electronic Systems, IEEE Transactions on  (Volume:43 ,  Issue: 4 )