Particle PHD filter multiple target tracking in sonar image

Clark, D., Ruiz, I.T., Petillot, Y. and Bell, J. (2007) Particle PHD filter multiple target tracking in sonar image. IEEE Transactions on Aerospace and Electronic Systems, 409-416. (doi:10.1109/TAES.2007.357143).

Record type: Article

Abstract

Two contrasting approaches for tracking multiple targets in multi-beam forward-looking sonar images are considered. The first approach is based on assigning a Kalman filter to each target and managing the measurements with gating and a measurement-to-track data association technique. The second approach uses the recently developed particle implementation of the multiple-target probability hypothesis density (PHD) filter and a target state estimate-to-track data association technique. The two approaches are implemented and compared on both simulated sonar and real forward-looking sonar data obtained from an autonomous underwater vehicle (AUV) and demonstrate that the PHD filter with data association compares well with traditional approaches for multiple target tracking

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