An empirical exploration of a simple deghosting method for multistatic radars

Wei, Tan; Lun, Yap Han

doi:10.1109/radar.2015.7131221

Cited by 4 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are many solutions for the deghosting problem available in the literature [4][5][6][7][8]. A deghosting algorithm based on the evaluation of all possible bistatic track pair combinations with modified clustering is available in [9].…”

Section: Introductionmentioning

confidence: 99%

Reversible Jump MCMC for Deghosting in MSPSR Systems

Kulmon

2021

Sensors

View full text Add to dashboard Cite

This paper deals with bistatic track association and deghosting in the classical frequency modulation (FM)-based multi-static primary surveillance radar (MSPSR). The main contribution of this paper is a novel algorithm for bistatic track association and deghosting. The proposed algorithm is based on a hierarchical model which uses the Indian buffet process (IBP) as the prior probability distribution for the association matrix. The inference of the association matrix is then performed using the classical reversible jump Markov chain Monte Carlo (RJMCMC) algorithm with the usage of a custom set of the moves proposed by the sampler. A detailed description of the moves together with the underlying theory and the whole model is provided. Using the simulated data, the algorithm is compared with the two alternative ones and the results show the significantly better performance of the proposed algorithm in such a simulated setup. The simulated data are also used for the analysis of the properties of Markov chains produced by the sampler, such as the convergence or the posterior distribution. At the end of the paper, further research on the proposed method is outlined.

show abstract