基于约束序贯M估计的时空域融合红外杂波抑制

doi:CNKI:11-1929/V.20110517.0903.001

Abstract

Abstract: Research is conducted on the intense clutter background removal so as to detect infrared small dim target. An adaptive spatial-temporal fused filtering algorithm for infrared clutter suppression is proposed based on restricted parametric sequential M-estimation. Firstly, an improved spatial-temporal fused prediction model for clutter background is presented on the analysis of the mismatch between the sequential images. And the image intensity is estimated by means of two-dimensional fast discrete Fourie transform (2DFT) and bilinear interpolation. Secondly, the model parameters are adaptively reckoned on restricted sequential M-estimation as the data sampled to double thresholds. Meanwhile, the forget factor and control factor are introduced to improve the robustness.The experiments show that the proposed algorithm not only perfectly removes the background under common circumstance but also effectively filters the intense clutter and preserves the targets signal,which holds fairly better performance and robust accommodation to environment than the existing ones.

Key words: infrared clutter suppression, target detection, sequential M-estimation, spatial-temporal fusion, image registration

CLC Number:

V248
TP391

LONG Yunli, XU Hui, AN Wei, LIN Liangkui. Spatial-temporal Fused Filtering for Infrared Clutter Suppression Based on Restricted Sequential M-estimation[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2011, 32(8): 1531-1541.

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Spatial-temporal Fused Filtering for Infrared Clutter Suppression Based on Restricted Sequential M-estimation

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