Abstract
The probability hypothesis density (PHD) is the expectation intensity in a point in state space. The intensity integral in any region of the state space is the expected number of targets contained in that region. In this paper, we propose a target measurement intensity (TMI) filter. Compared with the existing methods, the proposed approach is simpler. Since the conventional PHD filter can not directly deal with the shape target detection and tracking, we give the detection and tracking algorithm based on the TMI filter by modeling the parameter dynamics and measurement function of the shape target.
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Liu, W., Wen, C., Ding, S. (2014). A Shape Target Detection and Tracking Algorithm Based on the Target Measurement Intensity Filter. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8795. Springer, Cham. https://doi.org/10.1007/978-3-319-11897-0_27
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DOI: https://doi.org/10.1007/978-3-319-11897-0_27
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