问：PHD和CPHD是最优或次最优滤波器？
答：PHD是最优滤波器。
This type of approach allows the problem of estimating multiple targets in clutter and uncertain associations to be cast in a Bayesian filtering framework [16], which in turn results in an optimal multi-target Bayesian filter [1].
With finite set statistics (FISST), Mahler introduced a set theoretic approach in which targets and measurements are modeled using random finite sets (RFS). The approach allows multiple target tracking in the presence of clutter and with uncertain associations to be cast in a Bayesian framework [11], resulting in an optimal multi-target Bayes filter [2].
[1]. Granstrom, K., et al. (2012). "Extended Target Tracking using a Gaussian-Mixture PHD Filter." IEEE Transactions on Aerospace and Electronic Systems 48(4): 3268-3286.
[2]. Granstrom, K. and U. Orguner (2012). "A phd Filter for Tracking Multiple Extended Targets Using Random Matrices." IEEE Transactions on Signal Processing 60(11): 5657-5671.