在天气雷达信号处理器中用IQ信号消减地物杂波

地物杂波的检测和处理对雷达数据质量有重要的影响。常规的地物杂波检测依赖于晴空条件下的杂波图，人工判别，后来采用GAMP滤波器进行全程自适应滤波处理，该法在对地物抑制的同时对天气信号的损失较大，现探究比较多的方案是先自动识别地物，后结合滤波器对地物进行处理，在抑制地物的同时减少对天气信号的损耗。该算法基于IQ信号，利用已在C波段天气雷达中进行实验的SCI算法的4个判别因子，引入模糊逻辑理论，重新设计算法识别流程，并应用于我国S波段天气雷达中。通过实例对比杂波消减决策（CMD）算法对同一天气过程的识别与抑制的结果，发现该算法对气象回波的误判率低于CMD算法，对地物的识别率与CMD算法相当。

Using IQ Signals to Mitigate Ground Clutter in Signal Processors

Detection and processing of ground clutter have an important influence on the quality of radar data. The early detection of ground clutter depends on clutter maps under the clear air condition or artificial discrimination. With the improvement of processing capacity, the frequency domain filter in the whole process is adapted for adaptive filtering, especially after the realization of the GAMP filter. However, in actual operation, it is found that the algorithm weakens high elevation weather signals with velocity being zero. The scheme of real time identification of ground clutter and dealing it with a filter becomes a trend. It can restrain ground clutter while reducing the loss of weather signals. The described algorithm is based on IQ data. Four parameters obtained from the SCI algorithm, which has been tested on C band weather radar, are employed as the inputs of fuzzy logic theory. After redesigned the algorithm flaw, the SCI algorithm is introduced into S band weather radar. Through example analysis and comparison with the CMD algorithm, it is found that the SCI algorithm has lower misjudgment rate than the CMD algorithm, and the recognition rate is nearly the same as that of CMD algorithm.