CHONG Jin-song1,2, WEI Xiang-fei1,2,3
（1. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China； 2. National Key Laboratory of Science and Technology on Microwave Imaging, Beijing 100190, China； 3. University of Chinese Academy of Sciences, Beijing 100190, China）
Abstract： A millimeter-wave linear frequency modulated continuous wave (LFMCW) radar is applied to water surface detection.This paper presents the experiment and imaging algorithm. In imaging processing, water surface texture can hardly be seen in the results obtained by traditional imaging algorithm.To solve this problem, we propose a millimeter-wave LFMCW radar imaging algorithm for water surface texture. Different from the traditional imaging algorithm, the proposed imaging algorithm includes two improvements as follows: Firstly, the interference from static targets is removed through a frequency domain filter; Secondly, the multiplicative noises are reduced by the maximum likelihood estimation method, which is used to estimate the azimuth spectrum parameters to calculate the energy of water surface echo. Final results show that the proposed algorithm can obtain water surface texture, which means that the proposed algorithm is superior to the traditional imaging algorithm.
Key words： millimeter-wave LFMCW radar； water surface texture； imaging algorithm； maximum likelihood estimation
CLD number： TN957.52Document code： A
Article ID： 1674-8042（2017）01-0046-08 doi： 10.3969/j.issn.1674-8042-2017-01-008
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毫米波LFMCW雷达水面探测实验及其成像算法
种劲松1,2， 魏翔飞1,2,3
（1. 中国科学院电子学研究所， 北京 100190； 2. 微波成像国家重点实验室， 北京 100190；3. 中国科学院大学， 北京 100190）
摘要:本文将毫米波线性调频连续波（Linear frequency modulated continuous wave， LFMCW）雷达用于水面探测， 并介绍了水面探测实验及其成像算法。 在成像处理中， 采用传统的成像算法很难获取水面纹理。 为解决该问题， 本文提出了一种针对水面纹理的毫米波LFMCW雷达水面成像算法。 相对于传统成像算法， 本文算法做了以下两点改进： 首先， 采用频域滤波法去除静止目标回波的干扰； 其次， 采用最大似然估计算法估计方位频谱参数， 计算水面回波能量， 减小乘性噪声干扰。 成像结果表明， 该算法能够获取水面纹理， 且优于传统成像算法。
关键词:毫米波LFMCW雷达； 水面纹理； 成像算法； 最大似然估计
引用格式：CHONG Jin-song, WEI Xiang-fei. Millimeter-wave LFMCW radar water surface detection experiment and its imaging algorithm. Journal of Measurement Science and Instrumentation, 2017, 8(1)： 46-53. ［doi： 10.3969／j.issn.1674-8042.2017-01-008］
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