MTM算法在全固态天气雷达LFM信号中的应用

Application of MTM Algorithm in all Solid-state Weather Radar with LFM Signal Transmission

全固态天气雷达具有较高的可靠性和较好的可维护性,但由于发射功率受到固态发射器件的限制,通常需采用脉冲压缩技术来解决探测距离与距离分辨力之间的矛盾。LFM信号因其具有对目标的多普勒频移不敏感的特性而被用作脉冲压缩体制雷达的发射信号。经过脉压后的LFM信号一般通过汉明窗加权来降低过高的旁瓣,但由于脉压信号频谱菲涅尔波纹的存在使得输出信号功率图起伏严重,从而对雷达的多目标检测能力产生影响。根据多正弦窗的平滑特性,基于多窗谱估计算法(MTM)提出了一种将多正弦窗加权网络与汉明函数相结合的新的加权处理方法,并将此种方法运用于LFM脉压信号处理的详细过程进行了介绍。通过计算机仿真实验表明:将多正弦窗加权网络应用到LFM信号的脉冲压缩技术中在有效降低旁瓣的同时能起到平滑功率图噪声基底,控制主瓣展宽宽度的效果,并且在实际的外场试验中验证能达到应用需求。

All solid-state weather radar has high reliability and maintainability. However, the low peak power of solid- state transmitter degrades the detection distance and range resolution. A Linear Frequency Modulated （LFM） signal is commonly used in pulse compression radar system because it is not affected by Doppler shift during compression of the radar echoes in the matched filter. Nevertheless, the main drawbacks of pulse compression is high range sidelobes. The most common way of suppressing sidelobes is to use weighting functions. The Fresnel wave is subsistent on the frequency spectrum of compressed signal, it makes the power diagram of output signal serious fluctuation and serious impact the de- tection performance of weather radar. This paper presents a new weighting network which is based on the muhitaper method （MTM） and the characteristics of multiple sinusoidal window and Hamming window. This method will be intro- duced in detail and has been implemented in the compressed LFM signal. The computer simulation experiments show that： multiple sinusoidal weighted network can effective reduce the side lobe, control the main lobe width and smooth noise base in the used of compressed LFM signal. In addition, it can meet the application requirements in the field ex- periments.