张轶^1,,,
翟盛华¹,
陶海红²
1.中国空间技术研究院西安分院 西安 710100
2.西安电子科技大学雷达信号处理国家重点实验室 西安 710071
基金项目:国家自然科学基金(61771015)

详细信息

作者简介:张轶：男，1986年生，工程师，研究方向为干扰检测与定位处理
翟盛华：男，1978年生，研究员，研究方向为卫星通信与测控技术
陶海红：女，1976年生，教授，研究方向为雷达信号处理、运动目标检测

通讯作者:张轶　zhangyi1290@163.com

中图分类号:TN927

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被引次数:0

出版历程

收稿日期:2020-04-24
修回日期:2020-12-04
网络出版日期:2020-12-19
刊出日期:2021-07-10

Multi-target Interference Localization Using Single Satellite Multi-beam Antenna Based on Compressive Sensing

Yi ZHANG^1,,,
Shenghua ZHAI¹,
Haihong TAO²
1. China Academy of Space Technology (Xi’an), Xi’an 710100, China
2. National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
Funds:The National Natural Science Foundation of China (61771015)


摘要
摘要:针对卫星干扰处理中的多目标定位问题，该文提出基于压缩感知的定位方法。该方法利用目标的空间稀疏性，以及多波束天线在不同信号源方向上的增益不同，仅需要测量接收信号强度便可实现多个干扰的位置识别。研究结果表明，定位性能与节点分布、目标个数、波束覆盖半径、判决门限有关。在给定参数及原对偶内点算法下，该方法可实现1～4个干扰源的空域定位，在信噪比为20 dB时定位精度达到7.7 km，优于经典的旋转干涉仪和空间谱估计测向方法。
关键词:压缩感知/
单星定位/
多目标/
多波束天线/
接收信号强度
Abstract:To cope with the issue of locating multi-target in mitigating satellite interference, a localization method is proposed based on Compressive Sensing (CS). The sources of satellite interference can be identified by using Received Signal Strength (RSS) measurement only, relying on the spatial sparsity of the target source and the fact that multi-beam antenna has different gain at the position of interference. The conclusions show that positioning performance is related to node distribution, target number, coverage radius and decision threshold. Furthermore, over the Primal-Dual Interior Point (PDIP) algorithm, the simulation result represents that the target number is four under certain conditions, and the position accuracy is closed to 7.7 km with SNR of 20 dB. In addition, the study result also confirms that the proposed algorithm is better than the classic methods of Rotating Interferometer (RI) and Direction Of Arrival (DOA) estimation
Key words:Compressive Sensing (CS)/
Single satellite localization/
Multi-target/
Multi-beam antenna/
Received Signal Strength (RSS)



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