| 摘要: |
| Ozaktas算法因其运算复杂度低、精度高、提出时间早而成为目前对LFM信号进行处理
时最为常用的离散分数阶Fourier变换算法，但其附加的量纲归一化对LFM信号参数估计存在
影响。为此，在对LFM信号参数估计建模基础上，分析了基于Ozaktas算法的参数估计二维离
散网格效应，并进一步得到了影响初始频率和调频率估计精度的因素。可以发现：在满足采
样定理条件下，基于Ozaktas算法的LFM信号参数估计能保持较好的估计精度，且在一定程度
上可以通过增大采样频率或减小采样时长来进一步提高估计精度。最后，通过仿真分析验
证了上述理论推导的正确性。 |
| 关键词: 离散分数阶Fourier变换 Ozaktas算法 LFM信号 参数估计 估计精度 |
| DOI： |
|
| 基金项目:国家自然科学基金资助项目（60902054）；中国博士后科学基金
资助项目(201003758,20090460114)；山东省“泰山学者”建设工程项目 |
|
| Error analysis of LFM signal parameter estimation based on Ozaktas algorithm |
| DENG Bing,CUI Shi-qi,WANG Xu |
| () |
| Abstract: |
| Ozaktas algorithm is the most popular discrete fractional Fourier trans
form algorithm used to process LFM signals, for its low computation complexity,
high accuracy and earlier appearance. However, its additive dimensional normaliz
ation may affect parameter estimation of LFM signals. Therefore, 2-D discrete g
rid effect is analyzed for parameter estimation using Ozaktas algorithm based
on the parameter estimation model of LFM signals. Further, those factors influen
cing estimation accuracy are obtained. It can be found that parameter estimatio
n based on Ozaktas algorithm can keep high accuracy only if sampling follows t
he sampling theorem. Increasing sampling frequency or decreasing sampling durati
on can improve estimation accuracy to some extent. Finally, the simulations are
made to prove the above-mentioned theories. |
| Key words: discrete fractional Fourier transform Ozaktas algorithm LFM signal parameter est
imation estimation accuracy |
