一种参数化轨迹增强的TBD算法

doi:10.3969/j.issn.1001-2400.2015.06.004

Abstract

Abstract:

To address the problem of detection and tracking in the environment of a low SNR, we propose a new multi-frame track-before-detect algorithm. First of all, the nonparametric tracking initial is made based on the unthresholded multi-frame data. The target's plots can be obtained. Then the track enhancement operator is designed making use of the parameter of the target's state and the measurement imprecision error. Finally, using the designed operator to do the parameterized track enhancement, the results of tracking can be obtained. The algorithm possesses the characteristics of close loop feedback between the state of the target's trajectory and the track enhancement operator, which can improve the accuracy of detection and tracking and realize joint detection and tracking in a low SNR environment. Simulation results show that compared with the traditional track-before-detect the proposed method can obtain similar performance. The method can track stably in the case where the signal-to-noise ratio is 6dB.

Key words: target tracking, track-before-detect, multi-frame detection, track initial, edge detection

HE Jiayi;LIAO Guisheng;YANG Zhiwei;SUN Cunguang. Efficient track-before-detect algorithm based on the parameterized track enhancement[J].J4, 2015, 42(6): 17-22.

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Efficient track-before-detect algorithm based on the parameterized track enhancement

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