电子测量与仪器学报

杨明洋,向长波,房鹏飞.基于相关峰的理论样本干涉仪测向算法[J].电子测量与仪器学报,2021,35(10):33-40

基于相关峰的理论样本干涉仪测向算法

Direction finding algorithm of theoretical correlativeinterferometer based on correlation peak

DOI：

英文关键词:theoretical samples correlative interferometer correlative peak evaluation coefficient direction finding

基金项目:国家重大科学仪器设备开发专项(2018YFF01014302)资助

作者	单位
杨明洋	1.中国电子科技集团公司第四十一研究所
向长波	1.中国电子科技集团公司第四十一研究所
房鹏飞	1.中国电子科技集团公司第四十一研究所

Author	Institution
Yang Mingyang	1.The 41st Institute of China Electronics Technology Group Corporation
Xiang Changbo	1.The 41st Institute of China Electronics Technology Group Corporation
Fang Pengfei	1.The 41st Institute of China Electronics Technology Group Corporation

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中文摘要:

相关干涉仪是一种无源测向算法,具有计算复杂度低、抗干扰能力较强、样本依赖性较大的特点。为了减少相关干涉仪算法样本对环境的依赖,提高实际环境的测向精度,提出了一种基于理论样本的改进算法。该算法通过搜索相关矩阵的局部峰值、建立理论相关峰、计算相关峰评价系数(包含方差、峰度、偏度)、二次相关匹配的方法,在仅使用理论样本的条件下即可对来波信号进行精准测向。经过外场实验表明,在频段 340 MHz~ 3 GHz、信噪比 29 ~ 60 dB 区间内,改进算法的精度比传统采样算法在城市环境的测向精度高 0. 8°,且测向性能稳定,多次实验的精度偏离未超过 1°。改进算法计算复杂度较高,测向时间为传统算法的 3~ 4 倍,在无高时效性要求的场景具有良好的实用价值。

英文摘要:

Correlation Interferometer is a passive direction finding algorithm, which has the characteristics of low computational complexity, strong anti-interference ability and sample’s environment dependence. In order to reduce the dependence of the sample on the environment and improve the accuracy in actual working environment, an improved algorithm based on theoretical samples is proposed in this paper. By searching the local peak value of correlation matrix, establishing theoretical correlation peak system, calculating correlation peak evaluation coefficient ( including variance, kurtosis, skewness), and quadratic correlation matching, the algorithm can accurately detect the direction of arrival signal with theoretical samples. Field experiments show that in the frequency band 340 MHz~ 3 GHz and the signal-to-noise ratio 29 ~ 60 dB, the accuracy of the improved algorithm is 0. 8° higher than that of the traditional sampling algorithm in the urban environment. At the same time, the overall accuracy difference of many experiments is less than 1°. The improved algorithm has high computational complexity, and the cost of time is 3~ 4 times that of the traditional algorithm, and it has good practical value in scenarios without high timeliness requirements.

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