用自适应预测误差滤波器抑制雷达杂波

On Improving Suppression of Radar Clutter in China with Adaptive Prediction Error Filter

研究了ＦＴＦ算法和ＬＳＬ算法实现的预测误差滤波器对雷达地杂波和气象杂波的抑制性能，计算了杂波滤波器的改善因子。计算机仿真结果表明，ＬＳＬ和ＦＴＦ算法可以对杂波进行较大抑制，当用于目标检测时，ＦＴＦ算法具有较高的信杂比改善能力。

Detection of weak signals, especially from stealth planes, when background clutter exists, has attracted much attention. It is desirable to raise efficiency in suppressing clutter as much as possible to meet China's needs. So, the authors present the results of their study on two algorithms that are better than commonly used LMS algorithm.The two algorithms arc LSL(least squares lattice) and FTF(fast transversal filtering). They are used to make prediction error filter adaptive. Average improvement factor(AIF) can be computed for each of the three algorithms. AIFs computed with FTF and LSL algorithms are higher than that for LMS, indicating that FTF and LSL arc better than LMS in clutter sup[)ression. Compared with LSL and LMS algorithms, FTF algorithm exhibits the best performance of improving signal to clutter ratio(SCR) for detecting target in two specific clutter backgrounds. It is shown that for the two backgrounds maximum AIF values of FTF filter are about 19 dB and 12 dB respectively. This technique of clutter supprcssion can be cxpcctcd to be used in main clutter rckction system and moving target detection system of Chinese air traffic control radar.