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Content Provider | IEEE Xplore Digital Library |
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Author | Bin Wu Hao Yan |
Copyright Year | 2011 |
Abstract | A novel track-before-detect filtering algorithm is proposed for small dim infrared targets with low signal-to-noise ratio under complex backgrounds. A new particle filter called Quasi-Monte Carlo sampling based Gaussian particle filter(QMC-GPF) is developed to estimate on-line the standard kinematic parameters of the target, including position and velocity, as well as the amplitude of the target. The convergence characteristic of the covariance matrix of the posterior densities propagated in the QMC-GPF is used to determine whether it is the true target. The algorithm is tested with a synthetic target in IR image sequences, and it is proved that the algorithm is capable of performing sufficiently well for dim target of SNR¨R1dB. |
Starting Page | 103 |
Ending Page | 106 |
File Size | 325206 |
Page Count | 4 |
File Format | |
ISBN | 9781612843148 |
e-ISBN | 9781612843148 |
DOI | 10.1109/CMSP.2011.27 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-05-14 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Algorithm design and analysis IR image sequence. Track-before-detect Target tracking Signal processing algorithms Particle filters Covariance matrix Approximation methods Quasi-Monte Carlo |
Content Type | Text |
Resource Type | Article |
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