Ship Formation Target Recognition Based on Spatial and Temporal Fusion Hidden Markov Model
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摘要: 基于末制导雷达搜索舰艇编队目标时获得的目标大角域高分辨距离像(HRRP)信息,该文建立了描述单个HRRP样本内向量之间统计关系的各态历经空间隐马尔可夫模型(SHMM)和描述HRRP样本之间统计关系的从左到右时间隐马尔可夫模型(THMM)。与对一类目标全方位角训练数据只建立一个THMM模型的方法相比,该方法充分利用目标的大角域HRRP信息,提高了识别性能。通过对5类舰船目标的仿真和3类民用船只的外场实测数据分析表明该方法的有效性。Abstract: Based on the target large angle domain High Resolution Range Profile (HRRP) information of the ship formation obtained by the terminal guidance radar during its search phase, this study establishes an ergodic Spatial Hidden Markov Model (SHMM) which describes statistical relationship between the vectors in a single HRRP sample and a left to right Temporal HMM (THMM) which describes statistical relationship between HRRP samples. In comparison with the method that it only establishes a THMM model with the training data of all-round angle of one target, the proposed method makes full use of the target HRRP information of large angle domain and can improve the recognition performance. Through the simulation of the five types of ship target and the field measured data analysis of three kinds of civilian vessels show that the effectiveness of the proposed method.
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