| 摘要: |
| 针对传统时频原子在雷达信号分解中计算复杂度比较高的问题,提出了一种基于免疫克隆选择算法的时频原子快速分解方法。首先将Chirplet原子库分解为小原子库,然后并行地在每一个小原子库中搜索最佳原子,搜索过程建模为多参数寻优问题,通过免疫克隆选择算法的克隆、变异、记忆、替换等操作求解最优值,最后比较每一个小原子库中的最佳原子,将相似度最大的原子作为分解的最佳原子。仿真实验表明,该方法能够用较少的时频原子表示信号,在大幅减少时频原子搜索时间的同时,有效地抑制了噪声和交叉项的干扰。 |
| 关键词: 雷达信号 时频原子分解 免疫克隆选择法 |
| DOI： |
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| 基金项目: |
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| Application of immune clonal selection algorithm in time-frequency atom decomposition for radar signals |
| HU Xinlei,ZHANG Guoyi,TIAN Runlan |
| () |
| Abstract: |
| In view of high computational complexity in traditional time-frequency atom decomposition of radar signals,a fast decomposition method based on immune clonal selection algorithm is proposed. Firstly,Chirplet atom dictionary is divided into small atom dictionaries. Then,the best atom is concurrently searched in every small atom dictionary and the searching process is built as an optimization problem,which is solved through cloning,mutation,memory and substitution in immune clonal selection algorithm. Finally,the best atom in every small atom dictionary is compared and the most similar atom is selected as the best decomposition atom. Simulation indicates that this method can extract the feature of signals through few atoms and it decreases the computational time while effectively suppressing noise and time-frequency cross-terms. |
| Key words: radar signals time-frequency atom decomposition immune clonal selection algorithm |
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