Particle Filtering Based TBD in Single Frequency Network

Wen SUN  Lin GAO  Ping WEI  Hua Guo ZHANG  Ming CHEN  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E101-A   No.2   pp.521-525
Publication Date: 2018/02/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E101.A.521
Type of Manuscript: LETTER
Category: Digital Signal Processing
particle filter (PF),  track-before-detect (TBD),  single frequency network (SFN),  point measurement model,  

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In this paper, the problem of target detection and tracking utilizing the single frequency network (SFN) is addressed. Specifically, by exploiting the characteristics of the signal in SFN, a novel likelihood model which avoids the measurement origin uncertain problem in the point measurement model is proposed. The particle filter based track-before-detect (PF-TBD) algorithm is adopted for the proposed SFN likelihood to detect and track the possibly existed target. The advantage of using TBD algorithm is that it is suitable for the condition of low SNR, and specially, in SFN, it can avoid the data association between the measurement and the transmitters. The performance of the adopted algorithm is examined via simulations.