交会对接微波雷达高精度测角算法

徐秋锋; $2; 孙 武; $2

引用本文:	徐秋锋，邓晓东，孙武，柯腾伦. 交会对接微波雷达高精度测角算法[J]. 雷达科学与技术, 2021, 19(1): 28-34.[点击复制]
	XU Qiufeng, DENG Xiaodong, SUN Wu, KE Tenglun. High Precision Angle Measurement Algorithm for Rendezvous and Docking Microwave Radar[J]. Radar Science and Technology, 2021, 19(1): 28-34.[点击复制]

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交会对接微波雷达高精度测角算法
徐秋锋，邓晓东，孙武，柯腾伦
北京遥感设备研究所，北京 100854

摘要:

交会对接微波雷达需要完成100km至20m距离范围内、（±60°）×（±60°）宽视场范围内的角度测量，且测角精度要求在0.05°以内。针对兼具远近距离和宽视场测角需求，本文提出一种十形干涉仪几何对消测角算法。针对远距离测角精度无法满足精度要求的问题，采用基于当前统计模型的自适应Kalman滤波算法来提高测角精度。模拟试验、暗室试验和外场挂飞试验表明：干涉仪几何对消测角算法有效、可行，Kalman滤波后的角度测量结果优于高精度交会对接任务需求,已成功应用于月球轨道交会对接。

关键词: 交会对接微波雷达十形干涉仪几何对消测角 Kalman滤波

DOI：10.3969/j.issn.1672-2337.2021.01.005

分类号:TN953

基金项目:国家重大科技专项

High Precision Angle Measurement Algorithm for Rendezvous and Docking Microwave Radar

XU Qiufeng, DENG Xiaodong, SUN Wu, KE Tenglun

Beijing Institute of Remote Sensing Equipment,Beijing 100854,China

Abstract:

The rendezvous and docking microwave radar needs to operate from 100km to 20m in （±60°）×（±60°） wide field of view, and the angle measurement accuracy is within 0.05°. Aiming at the requirement of wide field of view angle measurement at long and short distances, an angle measurement algorithm of cross-shaped interferometer based on geometric cancellation is presented. In order to improve the accuracy of angle measurement, an adaptive Kalman filtering algorithm based on current statistic model is proposed. The results of simulation test, anechoic chamber experiment and airborne flight test show that the angle measurement algorithm of cross-shaped interferometer based on geometric cancellation is effective and feasible, and the angle measurement accuracy after Kalman filtering is better than the requirement of high-precision rendezvous and docking task. High-precision angle measurement algorithm for rendezvous and docking microwave radar has been successfully applied to the lunar orbit rendezvous.

Key words: rendezvous and docking microwave radar angle measurement algorithm of cross-shaped interferometer based on geometric cancellation Kalman filter