Abstract
Although the particle multi-target filter introduced in the previous chapter provides a general solution for the multi-target Bayesian recursion, due to the combinatorial complexity of multi-target Bayesian recursion, the computational load is too heavy. Hence, this filter is typically only suitable for relatively ideal scenarios where the number of targets is small or the signal to noise ratio is high for example.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2023 National Defense Industry Press
About this chapter
Cite this chapter
Wu, W., Sun, H., Zheng, M., Huang, W. (2023). Probability Hypothesis Density Filter. In: Target Tracking with Random Finite Sets. Springer, Singapore. https://doi.org/10.1007/978-981-19-9815-7_4
Download citation
DOI: https://doi.org/10.1007/978-981-19-9815-7_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-9814-0
Online ISBN: 978-981-19-9815-7
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)