宽带时域智能测试技术研究进展及未来展望OA
Research progress and future perspectives of intelligent broadband time-domain measurement technologies
在核爆轰试验、电子对抗、6G通信测试和芯片测试等领域,超宽带复杂信号的精确测试是评估系统性能、反演物理过程和发现故障目标的重要基础,也是宽带时域测试仪器核心能力的重要体现.然而,随着电子信号向超宽带、大动态、短时突发和强随机方向发展,传统测试技术受限于固定采样架构、有限实时处理能力以及单域分析模式,面临以下 3个主要挑战:1)宽带稀疏信号测试受带宽与分辨率相互制约,难以兼顾高带宽与高精度;2)极高速数据流中偶发异常易被海量正常数据淹没,难以实现实时捕获;3)复杂信号特征分布于时域、频域、调制域等信息空间,传统单域分析难以实现多域信息同步测试.针对上述问题,该文提出时频幅混合交织可重构采样架构,研究目标特征驱动的智能采样、偶发异常智能捕获和多域智能分析方法.通过自主学习信号多域特征分布,动态优化采样资源、检测资源和分析策略,实现超宽带复杂信号高精度采样、偶发异常无遗漏捕获和多域智能分析.研究推动宽带时域测试仪器由固定配置、被动采集向自适应采集、自主感知和智能分析演进,为新一代智能测试仪器发展提供理论与技术支撑.
In nuclear explosion tests,electronic warfare,6G communication testing,and chip testing,the accurate measurement of ultra-wideband(UWB)complex signals is fundamental for system performance evaluation,physical process reconstruction,and fault target identification,and represents a core capability of broadband time-domain test instruments.However,as electronic signals evolve toward ultra-wide bandwidth,large dynamic range,short-duration bursts,and strong randomness,conventional measurement techniques are constrained by fixed sampling architectures,limited real-time processing capability,and single-domain analysis,leading to three major challenges:1)broadband sparse signal measurement suffers from the trade-off between bandwidth and resolution,making it difficult to achieve both wide bandwidth and high accuracy;2)sporadic anomalies in ultra-high-speed data streams are easily overwhelmed by massive normal data,preventing reliable real-time capture;and 3)signal characteristics are distributed across multiple information domains,including the time,frequency,and modulation domains,making conventional single-domain analysis difficultly to achieve synchronized multi-domain measurement.To address these challenges,this paper proposes a reconfigurable hybrid interleaved sampling architecture in the time,frequency,and amplitude domains,together with target feature-driven intelligent sampling,anomaly capture,and multi-domain analysis methods.By autonomously learning the multi-domain feature distribution of signals,the proposed approach dynamically optimizes sampling resources,detection resources,and analysis strategies,enabling high-precision acquisition,lossless capture of sporadic anomalies,and intelligent multi-domain analysis of UWB complex signals.This work advances time-domain test instruments from fixed-configuration passive acquisition toward adaptive acquisition,autonomous perception,and intelligent analysis,providing theoretical foundations and technical support for next-generation intelligent test instruments.
杨扩军;田书林;叶芃;王厚军;刘科;陈凯
电子科技大学自动化工程学院,成都 611731电子科技大学自动化工程学院,成都 611731电子科技大学自动化工程学院,成都 611731电子科技大学自动化工程学院,成都 611731电子科技大学自动化工程学院,成都 611731电子科技大学自动化工程学院,成都 611731
信息技术与安全科学
宽带时域测试高精度采样异常捕获智能多域分析
broadband time-domain measurementhigh-precision samplingtransient anomalies captureintelligent multidomain analysis
《电子科技大学学报》 2026 (5)
749-764,16
国家自然科学基金(62371097,62201125)
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