Hidden Markov Model Based on Target Narrow Pulse Laser Transient Characteristics

Yali Hou, Hong Su, Bo Tian, Tie Li
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Abstract

Aiming at the fact that the narrow pulse laser transient characteristics of target have not been applied in target recognition, a hidden Markov model (HMM)based on transient characteristics is proposed. For the scattering characteristics of each target in different poses, the reliable model parameters of each target were completed by using the training samples, and each hidden Markov model was established. The maximum likelihood of the test samples for each model was calculated, the target feature class corresponding to the largest probability value was selected as the output category. The result shows that target recognition by hidden Markov model has better performance in terms of calculation speed and accuracy. This method is fast and effective.
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基于目标窄脉冲激光瞬态特性的隐马尔可夫模型
针对窄脉冲激光目标瞬态特性在目标识别中尚未得到应用的问题,提出了一种基于瞬态特性的隐马尔可夫模型。针对各目标在不同姿态下的散射特性,利用训练样本完成各目标的可靠模型参数,建立各隐马尔可夫模型。计算每个模型的测试样本的最大似然,选择概率值最大对应的目标特征类作为输出类别。结果表明,基于隐马尔可夫模型的目标识别在计算速度和精度上都有较好的表现。该方法快速有效。
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