多伯努利滤波的快速红外弱小目标检测与跟踪

doi:10.3969/j.issn.1001-2400.2016.04.013

Abstract

Abstract:

In view of the problems of tracking instability and non real-time and highly nonlinear measurement model for the detection and tracking of multiple Infrared(IR) dim targets under the complicated background, a fast detection and tracking algorithm based on multi-Bernoulli filter is presented. Firstly, the improved Robinson Guard filter suppresses the background clutter in order to avoid the suppression of the target in the strong background image. Then, the square-root cubature Kalman filter (SCK) performs the multi-Bernoulli track-before-detect (MB-TBD). It can perform real-time tracking in the highly nonlinear model. The numerical instability caused by a negative definite covariance matrix is avoided. The experiments with some real IR background images show that the improved Robinson Guard algorithm can suppress the background clutter effectively and preserve the dim target information. It is also shown that SCK-MB-TBD can estimate the number and states of targets accurately and stably so as to complete target detection and tracking.

LI Cuiyun;LI Ning;JI Hongbing. Fast IR dim small targets detection and tracking based on the multi-Bernoulli filter[J].Journal of Xidian University, 2016, 43(4): 69-74+190.

References

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Fast IR dim small targets detection and tracking based on the multi-Bernoulli filter

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