一种新的红外弱小目标检测前跟踪算法

doi:10.3969/j.issn.1001-2400.2011.03.017

Abstract

Abstract:

A novel track-before-detect filtering algorithm is proposed for the dim infrared target with a low signal-to-noise ratio in complex backgrounds. A new particle filter called the Quasi-Monte Carlo sampling based Gaussian particle filter(QMC-GPF) is developed to estimate on-line the standard kinematic parameters of the target, including the position and velocity, as well as the amplitude of the target. The convergence characteristic of the covariance of the posterior densities propagated in the QMC-GPF is used to construct the logical rules for soft-decision detection of a possible 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 the dim target of SNR≥1dB.

Key words: track-before-detect, quasi-Monte Carlo, Gaussian particle filter, IR image sequence

CLC Number:

TP391

WU Bin；LI Peng. Novel track-before-detect algorithm for small infrared target[J].J4, 2011, 38(3): 107-113.

References

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Novel track-before-detect algorithm for small infrared target

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