Abstract
The common probability hypothesis density (PHD) fiter is derived under the single sensor condition. The multisensor PHD (MPHD) filter is remarkably complex and thus is impractical to use. Mahler proposed a MPHD filter under the assumption of independence of all senors. This paper studies the linear multisensor-multitarget system. We propose a linear multisensor probability hypothesis density (LMPHD) filter. By combining measurement dimension extension (MDE) approach, we consider linear correlation of all sensors. A simulation is finally proposed to verify the effective of the L-MPHD filter.
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Liu, W., Wen, C. (2011). A Linear Multisensor PHD Filter Using the Measurement Dimension Extension Approach. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds) Advances in Swarm Intelligence. ICSI 2011. Lecture Notes in Computer Science, vol 6729. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21524-7_60
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DOI: https://doi.org/10.1007/978-3-642-21524-7_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21523-0
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