Design Method of Dynamic Channelization for Space-based Spectrum Sensing
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摘要: 随着全球在轨电磁设备的增长, 电磁频谱感知能力成为衡量国家综合科技实力的重要指标. 动态信道化技术是实现天基宽带频谱感知的关键技术, 具备宽带信号实时分解与并行处理能力, 可以缓解星上计算与数据处理压力. 针对频谱感知中宽带信号的跨信道问题, 设计了具有完全重构特性的多相滤波器组, 建立了分析–综合联合处理系统, 并提出优化的恒虚警率检测(Optimized-Constant False Alarm Rate, Optimized-CFAR)算法, 结合时频域联合跨信道判决方法, 实现了跨信道信号的自适应融合与精确重构. 该算法系统整体框架包括信道化滤波器组、子带频谱检测及跨信道判决三个核心模块. 实验结果表明, 15 dB信噪比条件下, 系统检测概率提升至98.6%, 重构信号保真度达0.972, 为天基频谱监测应用提供了高效解决方案.Abstract: The proliferation of electromagnetic devices in orbital environments has made electromagnetic spectrum sensing a critical capability for modern space-based systems. As space-based communication networks expand and electromagnetic interference becomes increasingly complex, advanced spectrum monitoring solutions are essential. This paper addresses the cross-channel signal processing challenge in wideband spectrum sensing, particularly for space-based platforms with limited computational resources and stringent real-time processing requirements. A dynamic channelization system incorporating perfect reconstruction polyphase filter banks is proposed to enable efficient wideband signal decomposition and parallel processing. The architecture features an analysis-synthesis joint processing framework that reduces onboard computational complexity while preserving signal integrity. An Optimized Constant False Alarm Rate (Optimized-CFAR) detection algorithm is developed to improve detection performance under varying noise conditions. The system employs a time-frequency domain joint cross-channel decision method for precise reconstruction of signals spanning multiple frequency channels. The polyphase filter bank design minimizes aliasing and distortion while ensuring computational efficiency for satellite implementation. Experimental results demonstrate significant performance improvements. At a 15 dB signal-to-noise ratio, the system achieves 98.6% detection probability, substantially outperforming conventional methods. The reconstructed signal fidelity reaches 0.972, indicating excellent preservation of signal characteristics. The cross-channel decision algorithm effectively resolves signal boundary ambiguities, enabling accurate identification and reconstruction of wideband signals exceeding individual channel bandwidths. The proposed system provides an efficient solution for space-based spectrum monitoring applications. The integration of Optimized-CFAR detection with polyphase filtering techniques offers a scalable framework for real-time wideband spectrum analysis suitable for orbital deployment, enhancing electromagnetic spectrum awareness capabilities for space-based communication and surveillance systems.
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表 1 信道化滤波器组乘法器消耗对比
Table 1. Comparison of multiplier in channelized filter banks
设计方法 乘法器数量 比例/(%) 本方法 687 2.6 LPFB 25920 100 PPFB 1652 6.37 FRM 822 3.17 表 2 不同通道下处理实时性对比
Table 2. Comparison of real-time processing in different channels
信道数 系统吞吐率/GSPS 处理延迟/μs 功耗/W 16 1.6 1.72 2.8 32 3.2 3.45 4.5 64 4.0 6.84 8.2 表 3 不同信道数下资源消耗占比
Table 3. Resource consumption proportion under different channels
信道数 DSP48使用率/(%) BRAM使用率/(%) LUT使用率/(%) 16 8.6 12.3 14.7 32 17.3 25.7 28.9 64 34.6 48.2 52.3 -
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饶嘉成 男, 2000年5月出生于江西省抚州市, 现为中国科学院国家空间科学中心硕士研究生, 专业为电磁场与微波技术, 主要研究方向为空间综合电子技术
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