Multi-target Interference Localization Using Single Satellite Multi-beam Antenna Based on Compressive Sensing
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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。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
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表 1 仿真参数配置
固定参数 取值 调整参数 取值 波束数M 19 载波频率f(GHz) 3.60~3.75 天线口径D(m) 14 功率系数k 1~5 天线效率$\eta $ 0.6 节点数N 400 蜂窝边长l(km) 240 干扰数K 4 区域半径R(km) 1050 覆盖半径r(km) 4l 搜索半径s(km) 30 判决门限T 0.2 参考功率P0 1 信噪比(dB) 20 表 2 评价指标与关键参数对应关系
定位成功率$\rho $ 定位误差$\delta $ 节点数N – – 干扰数K – + 覆盖半径r + – 判决门限T – / -
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