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Journal Article Joint Estimation of Multi-target Signal-to-noise Ratio and Dynamic States in Cluttered Environment
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Authors
Seung-Hwan Bae, Jongyoul Park, Kuk-Jin Yoon
Issue Date
2017-03
Citation
IET Radar, Sonar and Navigation, v.11, no.3, pp.539-549
ISSN
1751-8784
Publisher
IET
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1049/iet-rsn.2016.0416
Project Code
16MS2400, Development of High Performance Visual BigData Discovery Platform, Park Kyoung
Abstract
In this study, the authors consider a multi-target tracking (MTT) problem in a cluttered environment. Due to the difficulty of the problem, the methods relying only on spatial information such as range, bearing and Doppler velocity can be unreliable. To overcome this, they additionally exploit the amplitude information, commonly provided by radar and sonar, for MTT. However, the usage of amplitude information is not straightforward because the signal-to-noise ratio (SNR) should be known in advance or estimated at the same time. To this end, they first propose a novel SNR estimation algorithm based on a maximum a posteriori approach, which helps the tracker to exploit the amplitude information effectively. Based on the estimated SNR, they then propose a complete framework for MTT, which is mainly composed of data association and track state update parts. They extensively evaluate the proposed system in a series of challenging scenarios, and the experimental results verify the effectiveness and robustness of the authors' methods.
KSP Keywords
Amplitude information, Cluttered environment, Data association, Doppler velocity, Joint Estimation, SNR Estimation, Signal noise ratio(SNR), Signal-to-Noise, State update, estimation algorithm, maximum a posteriori