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To address the multiple requirements of low cost, low power consumption, and high accuracy (sub-nanosecond level)for time-frequency systems in large-scale low Earth orbit (LEO) navigation constellations, a precision frequency control method based on micro-step adjustment is proposed for oven-controlled crystal oscillators (OCXOs), targeting the mitigation of long-term frequency drift. A quantization noise model was established, and a 48-bit direct digital synthesizer (DDS) was employed to achieve high-resolution real-time frequency correction at 5×10-13 resolution. A constraint framework and frequency adjustment procedure compatible with rapid precise position services were constructed. Experimental results demonstrate that during 24-hour continuous operation, a clock bias accuracy (RMS) of 0.24 ns was achieved. Compared to free-running state, a long-term frequency stability was significantly improved by three orders of magnitude, with a slight degradation of 25% in short-term stability (1 s-20 s). This approach provides a cost-effective, high-precision, and stable time-frequency reference solution for LEO constellation construction.

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针对大规模低轨导航星座部署中时频系统面临低成本、低功耗与高精度(亚纳秒级)的多重需求,本文提出一种基于微步进的恒温晶振(OCXO)时钟频率精细控制方法,解决晶振长期频率漂移问题。通过建立调频量化噪声模型,结合48位直接数字频率综合器(DDS)实现5×10-13分辨率的高精度频率实时校正,构建满足快速精密定位服务的约束框架和调频流程方法。结果表明:该方法在24小时连续测试中,系统钟差精度(RMS)提升至0.24 ns,长期频率稳定度(10 000 s)达3.16×10-14(较自由状态优化3个量级),短期稳定度(1 s~20 s)损失仅25%,为低轨星座建设提供了低成本、高精度、高稳定性时频基准解决方案。

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王冬冬 1982年生,硕士,高级工程师。

廖文和 1965年生,教授,博士生导师。

刘斌 1979年生,博士,研究员。

禹强华 1982年生,硕士,研究员。

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Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210000, China), AuthorCompanyExt(id=1239158385665430056, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, companyId=1239158385652847142, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.南京理工大学机械工程学院 南京 210000)]), AuthorCompany(id=1239158385728344621, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, xref=null, ext=[AuthorCompanyExt(id=1239158385736733229, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, companyId=1239158385728344621, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. Beijing Research Institute of Telemetry, Beijing 100076, China), AuthorCompanyExt(id=1239158385740927534, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, companyId=1239158385728344621, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.北京遥测技术研究所 北京 100076)])], figs=[ArticleFig(id=1239158387888411295, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=EN, label=Fig. 1, caption=System architecture of the precision control with micro-step, figureFileSmall=OF38ntuRGHw9erbTb5oXRA==, figureFileBig=UTyY0Q+tv8oFCQ5/AL3Qog==, tableContent=null), ArticleFig(id=1239158387980685988, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=CN, label=图1, caption=微小步进调频系统架构, figureFileSmall=OF38ntuRGHw9erbTb5oXRA==, figureFileBig=UTyY0Q+tv8oFCQ5/AL3Qog==, tableContent=null), ArticleFig(id=1239158388152652463, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=EN, label=Fig. 2, caption=System flowchart of real-time precision control with micro-step, figureFileSmall=RKFYoJtB3zQKTVL/Jdn7qg==, figureFileBig=Pv49gn/BqGWXgQXf2EvOLw==, tableContent=null), ArticleFig(id=1239158388236538545, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=CN, label=图2, caption=实时精细调频流程, figureFileSmall=RKFYoJtB3zQKTVL/Jdn7qg==, figureFileBig=Pv49gn/BqGWXgQXf2EvOLw==, tableContent=null), ArticleFig(id=1239158388303647409, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=EN, label=Fig. 3, caption=Clock bias for free-running, figureFileSmall=xW3SUVihERQBHTtElsI7xw==, figureFileBig=ncDiH05yoNcZyY6Ep+msGw==, tableContent=null), ArticleFig(id=1239158388391727797, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=CN, label=图3, caption=自由运行下钟差测试结果, figureFileSmall=xW3SUVihERQBHTtElsI7xw==, figureFileBig=ncDiH05yoNcZyY6Ep+msGw==, tableContent=null), ArticleFig(id=1239158388484002489, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=EN, label=Fig. 4, caption=Clock bias under micro-step control, figureFileSmall=Sw1F2ArMtAhSuFWcFCIdKg==, figureFileBig=cI95T0HVFCGyDhIga6yDCg==, tableContent=null), ArticleFig(id=1239158389952008894, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=CN, label=图4, caption=微步进精控制下的钟差测试结果, figureFileSmall=Sw1F2ArMtAhSuFWcFCIdKg==, figureFileBig=cI95T0HVFCGyDhIga6yDCg==, tableContent=null), ArticleFig(id=1239158390035894978, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=EN, label=Fig. 5, caption=Frequency bias for free-running, figureFileSmall=KPpV9IZYSCPRnVY+Z78DJg==, figureFileBig=eofdO4ei9UArNEJ7j86cvg==, tableContent=null), ArticleFig(id=1239158390140752585, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=CN, label=图5, caption=自由运行下频率偏差测试结果, figureFileSmall=KPpV9IZYSCPRnVY+Z78DJg==, figureFileBig=eofdO4ei9UArNEJ7j86cvg==, tableContent=null), ArticleFig(id=1239158390270776014, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=EN, label=Fig. 6, caption=Frequency bias under micro-step control, figureFileSmall=In8bcF3TzvigKwKoGVJM1w==, figureFileBig=WzlOP9BHeNBxndTey9ABVA==, tableContent=null), ArticleFig(id=1239158390358856400, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=CN, label=图6, caption=微步进控制下的频率偏差测试结果, figureFileSmall=In8bcF3TzvigKwKoGVJM1w==, figureFileBig=WzlOP9BHeNBxndTey9ABVA==, tableContent=null), ArticleFig(id=1239158390438548179, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=EN, label=Fig. 7, caption=Frequency stability comparison, figureFileSmall=tkpjb8QOktp+tMUzaXwM8Q==, figureFileBig=1MMZKp42wg3uLWJmc2hP/Q==, tableContent=null), ArticleFig(id=1239158390522434263, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=CN, label=图7, caption=频率稳定度对比测试结果, figureFileSmall=tkpjb8QOktp+tMUzaXwM8Q==, figureFileBig=1MMZKp42wg3uLWJmc2hP/Q==, tableContent=null), ArticleFig(id=1239158390618903259, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=EN, label=Table 1, caption=

A comparison table of frequency stability represented by Allan deviation

, figureFileSmall=null, figureFileBig=null, tableContent=
Averaging Time (s)σyτ
(micro-step control)
σyτ
(free-running)
Improvement Ratio
11.38×10-121.18×10-120.86
21.67×10-121.35×10-120.81
42.21×10-121.72×10-120.78
103.65×10-122.73×10-120.75
204.43×10-123.81×10-120.86
402.95×10-125.42×10-121.84
1001.76×10-128.45×10-124.80
1 0002.46×10–133.22×10-11130.90
2 0001.46×10-134.38×10-11300.00
4 0007.25×10-145.34×10-11736.60
10 0003.16×10-147.88×10-112 493.70
), ArticleFig(id=1239158390736343778, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239158374311448701, language=CN, label=表1, caption=

频率稳定度指标对比分析

, figureFileSmall=null, figureFileBig=null, tableContent=
Averaging Time (s)σyτ
(micro-step control)
σyτ
(free-running)
Improvement Ratio
11.38×10-121.18×10-120.86
21.67×10-121.35×10-120.81
42.21×10-121.72×10-120.78
103.65×10-122.73×10-120.75
204.43×10-123.81×10-120.86
402.95×10-125.42×10-121.84
1001.76×10-128.45×10-124.80
1 0002.46×10–133.22×10-11130.90
2 0001.46×10-134.38×10-11300.00
4 0007.25×10-145.34×10-11736.60
10 0003.16×10-147.88×10-112 493.70
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一种基于微小步进的低轨卫星时钟频率精细控制方法
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王冬冬 1, 2 , 廖文和 1 , 刘斌 2 , 禹强华 2
遥测遥控 | 测控通信与导航 2025,46(6): 95-101
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遥测遥控 | 测控通信与导航 2025, 46(6): 95-101
一种基于微小步进的低轨卫星时钟频率精细控制方法
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王冬冬1, 2, 廖文和1, 刘斌2, 禹强华2
作者信息
  • 1.南京理工大学机械工程学院 南京 210000
  • 2.北京遥测技术研究所 北京 100076
  • 王冬冬 1982年生,硕士,高级工程师。

    廖文和 1965年生,教授,博士生导师。

    刘斌 1979年生,博士,研究员。

    禹强华 1982年生,硕士,研究员。

A Precision-Control Method with Micro-Step for OCXO Clocks in LEO Satellites
Dongdong WANG1, 2, Wenhe LIAO1, Bin LIU2, Qianghua YU2
Affiliations
  • 1. Dept. Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210000, China
  • 2. Beijing Research Institute of Telemetry, Beijing 100076, China
doi: 10.12347/j.ycyk.20250707001
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针对大规模低轨导航星座部署中时频系统面临低成本、低功耗与高精度(亚纳秒级)的多重需求,本文提出一种基于微步进的恒温晶振(OCXO)时钟频率精细控制方法,解决晶振长期频率漂移问题。通过建立调频量化噪声模型,结合48位直接数字频率综合器(DDS)实现5×10-13分辨率的高精度频率实时校正,构建满足快速精密定位服务的约束框架和调频流程方法。结果表明:该方法在24小时连续测试中,系统钟差精度(RMS)提升至0.24 ns,长期频率稳定度(10 000 s)达3.16×10-14(较自由状态优化3个量级),短期稳定度(1 s~20 s)损失仅25%,为低轨星座建设提供了低成本、高精度、高稳定性时频基准解决方案。

低轨卫星  /  恒温晶振  /  量化噪声  /  微小步进  /  频率稳定度

To address the multiple requirements of low cost, low power consumption, and high accuracy (sub-nanosecond level)for time-frequency systems in large-scale low Earth orbit (LEO) navigation constellations, a precision frequency control method based on micro-step adjustment is proposed for oven-controlled crystal oscillators (OCXOs), targeting the mitigation of long-term frequency drift. A quantization noise model was established, and a 48-bit direct digital synthesizer (DDS) was employed to achieve high-resolution real-time frequency correction at 5×10-13 resolution. A constraint framework and frequency adjustment procedure compatible with rapid precise position services were constructed. Experimental results demonstrate that during 24-hour continuous operation, a clock bias accuracy (RMS) of 0.24 ns was achieved. Compared to free-running state, a long-term frequency stability was significantly improved by three orders of magnitude, with a slight degradation of 25% in short-term stability (1 s-20 s). This approach provides a cost-effective, high-precision, and stable time-frequency reference solution for LEO constellation construction.

Low Earth Orbit (LEO) satellites  /  Oven-controlled crystal oscillator (OCXO)  /  Quantization noise  /  Micro-step  /  Frequency stability
王冬冬, 廖文和, 刘斌, 禹强华. 一种基于微小步进的低轨卫星时钟频率精细控制方法. 遥测遥控, 2025 , 46 (6) : 95 -101 . DOI: 10.12347/j.ycyk.20250707001
Dongdong WANG, Wenhe LIAO, Bin LIU, Qianghua YU. A Precision-Control Method with Micro-Step for OCXO Clocks in LEO Satellites[J]. Journal of Telemetry, Tracking and Command, 2025 , 46 (6) : 95 -101 . DOI: 10.12347/j.ycyk.20250707001
低轨导航星座作为国家空间基础设施的重要组成部分,可提供实时厘米级定位服务,而星载时频系统是决定系统定位精度的关键因素。大规模星座部署要求时频系统具有低成本、小体积和低功耗的特点。相较于原子钟,恒温晶振(OCXO)以体积小、功耗低(<3W)、成本优(<铷钟的30%)的优势成为卫星系统首选时钟源。但其长期频率漂移较差,导致钟差以50~100 ns/h的速度累积,且利用卫星自身GNSS接收机进行钟差实时计算修正时,受卫星处理资源约束,钟差估计精度为ns级,无法满足实时精密单点定位(PPP)需求。
为提高导航卫星定位服务性能,对卫星钟差的高精度控制研究,多集中在原子钟相关技术方面[1-6],采用高阶多项式或超短时预报进行钟差更新,实时钟差精度维持在纳秒级。同时,凭借地面监测系统对时钟校准,多采用卡尔曼滤波[7-12]或最小二乘法[13]技术对时钟进行修正,仍为纳秒级同步精度,难以满足实时精密单点定位(PPP)服务对亚纳秒钟差的要求。也有融合多GNSS观测数据[14]、星间链路数据和地面站时间基准参考[15]的校正技术,需要分钟级收敛时间,实时性不足。现有研究多聚焦于PPS相位或频率偏差校正,校正精度和周期无法满足实时高精度服务下对OCXO频率源精细控制的需求。本文提出基于微步进的频率精细控制方法,建立调频量化噪声模型,为调频参数提供量化依据。在钟差阈值触发的策略下,采用48位直接数字频率综合器(DDS),实现晶振频率漂移的实时精细补偿,最后对比无驯服状态(自由运行状态)的时钟性能进行控制效果评估。
实验表明:本方法在维持OCXO原有的优异短期稳定度基础上,将钟差精度(RMS)由纳秒级提高至亚纳秒级,同时长期稳定度(10 000 s)可提升至10-14量级,较自由运行状态优化3个量级,为低轨导航星座提供了有效的低成本高精度时频系统方案。
本文提出的精细控制方法,其核心思想为构建“状态估计-参数约束-高分辨率执行”的闭环控制模型。
首先建立时钟状态空间模型,为频率漂移控制提供理论基准。其次是建立实时状态估计器,采用卡尔曼滤波(KF)融合GNSS观测值,动态输出最优估计值。实时厘米级定位服务下结合信号连续性和频率稳定性的需求,建立系统调频参数约束模型,通过高分辨率调频单元执行频率精细调整,以阈值触发策略驱动闭环控制流程。
采用时钟偏差φk)与频率偏差fk)的双状态变量[16],离散时间下恒温晶振时钟状态空间模型如下:
式中:为系统状态向量,uk)为tk时刻的频率调整量,A为状态转移矩阵,B为控制输入矩阵,τ是采样间隔,ωk是过程噪声,主要由晶振自身噪声构成,是均值为零的高斯随机过程,服从N(0,Q)分布。
采用幂律谱模型,其包含五种不同的独立噪声项,用噪声叠加方法表示过程噪声ωk的功率谱密度Syf)如下:
式中,fH是高频截止频率,是频率随机游走噪声强度,h-1是调频闪烁噪声强度,h0是调频白噪声强度,h1是调相闪烁噪声强度,h2是调相白噪声强度。
对每一类幂律谱噪声积分计算,阿仑方差为各类噪声贡献方差的叠加,有如下:
式中,γ≈0.577 2,为欧拉常数,fH是高频截止频率,满足fHτ≫1/2π。
根据公式(2),利用最小二乘法求解h-2h-1h0h1h2的值[17]。结合每一类噪声贡献特点[18],利用系统状态变量传播关系进行积分计算,构建系统协方差矩阵Q,其中频率偏差方差用Q22表示为:
本文采用卡尔曼滤波方法进行系统钟差实时估计[18-20]。系统状态观测方程为:
式中:yk是通过GNSS观测量测得的钟差值,C=[1 0]是观测矩阵,vk是测量噪声,服从N(0,R)分布,是零均值方差为R的高斯白噪声。
卡尔曼滤波通过迭代更新状态估计值及协方差Pkk,最小化估计误差的过程[18-20]如下:
系统状态预测
预测协方差Pk+1/k
卡尔曼增益Kkalman计算:
系统状态更新
协方差更新Pk+1/k+1
式中,I是单位矩阵。
卡尔曼滤波器收敛[21]后,输出最优状态估计结果[22],其作为控制计算的输入得到频率调整量uk
频率调整过程中,需保证导航射频信号的相位缓慢连续变化,每次频率校正不能引起过大的相位阶跃或波动,地面接收机可正常捕获跟踪[23],依此建立信号连续性约束模型。
导航射频信号频率fRF与参考晶振频率fref的关系为:
由最大调频步进umax引起的射频变化量∆fRF为:
定义射频信号相位变化率为dϕt)/dt,有如下公式:
为保证接收机对信号的稳定跟踪,需满足:
最终,最大调频步进为:
对于地面接收机,最大可容忍相位变化率dϕ/dtmax为0.1 rad/s。
工程实际应用中,频率调整量需经过数字量化,调整量表现为离散的步进值。
实际频率调整量是最小频率调整步进umin的整数倍,其具有离散化特性表示为:
频率调整精度为最小调频步进umin的1/2,量化误差εk为:
该量化误差εk在步进调频控制系统中表现为量化噪声,服从均匀分布εk~u(-umin/2,+umin/2),其均值为零,可得量化噪声协方差Qε为:
晶振自身的过程噪声和外部调频量化噪声是相互独立的噪声源,调频控制后的系统频率偏差方差定义为Q22_ctrl,其晶振噪声频率偏差方差Q22与调频量化噪声协方差Qε之和,有如下关系:
在短时更新的钟差估计中,频率偏差方差Q22与晶振阿伦方差σosc2τ)的关系如下:
量化噪声对频率稳定度的影响控制在一定范围以内,用比例因子K约束。由量化噪声分析,可得出最小调频步进umin应满足:
最小调频步进umin越大,注入的噪声越大,对系统频率稳定度影响越大。
在快速精密定位服务中,亚纳秒级钟差估计精度要求晶振短期稳定度在10-12量级[17],根据晶振稳定度指标,K取值范围设置为0.1~0.4。
基于微小步进的精细调频系统架构如图1所示。
①高精度GNSS接收机:高精度GNSS接收机提供伪距和载波相位观测值,采样率为1 Hz,用于钟差计算单元解算本地时钟偏差;
②钟差估计单元:通过卡尔曼滤波器(KF)实时估计时钟偏差φk)和频率偏差fk);
③频率调整量计算及检测单元:根据如下公式计算频率调整量uk
其中,a是调整系数,fk)是系统频率偏差,a取值范围在0.45~0.85,根据系统状态动态设置;调整单元实时进行调整量约束检测,确保频率调整量在限制范围内。
④频率量化解析单元:对频率调整量uk进行离散化处理,得到工程可执行的量化调整量uk*,完成调整量转换为OCXO时频系统中的控制信息。
⑤高分辨率时频单元:以OCXO为原始基准,采用直接数字频率综合器(DDS)实现高分辨率的OCXO频率调整,调整后的信号作为系统高精度时频基准信号。其中DDS的工作时钟fCLK与频率调节的分辨率ustep,关系如下:
根据约束模型计算,DDS的位数N取值为48,满足最小频率步进需求。
根据调频系统架构和参数约束模型,频率实时精细控制流程如图2所示。经过频率准确度的初始校准,频率准确度调整到一定范围内。根据钟差估计结果和设定的比例系数a进行调整量计算。当钟差超过设定的阈值时,触发频率调整。调整量计算后进入约束检测阶段,当频率调整量小于下限umin时,取umin为本次调整量;当频率调整量超出上限umax时,取umax为本次调整量。最后由高分辨率DDS单元执行完成频率的精细调整。
本文实验以铷原子钟为参考基准输入,对时频系统中的恒温晶振频率进行精细调整测试。GNSS信号模拟源模拟产生高精度导航信号。高精度GNSS接收机对导航信号进行伪距和载波相位测量获得本地钟差测量数据[24,25],GNSS数据采样率为1次/秒。实时精密定位服务需求下,实验用的恒温晶振频率10 MHz,导航射频信号中心频点1 176.45 MHz。根据公式(17)和公式(23),确定调频步进的最小和最大边界,实现信号连续性和短期稳定度维持。本文选取最小调频步进为5E-13,最大调频步进为|uk*|≤1E-11。实验系统连续72 h运行,选取连续24 h实验结果对时频信号进行性能评估。
晶振自由运行系统钟差变化过程如图3所示,初始时刻钟差值0.5 ns,运行20 000 s后钟差快速累积达530 ns,钟差累积速度约为95 ns/h。对比文献[26]采用多项式拟合和校正窗口优化后的原子钟校正方法,其在线实时校正后钟差精度为1.81 ns,本文方法频率经微小步进实时调整后,结果如图4所示,扣除系统固有相位偏差,钟差峰峰值波动范围在0.5 ns内,钟差精度(均方根)达到0.24 ns。
图5所示,自由运行下,晶振初始频率准确度2E-11,受频率漂移影响,24 h内频率偏差最大达到8.4E-11。经过微步进调频控制后,频率准确度如图6所示,频率偏差维持在5E-12水平。调整后频率偏差曲线基本符合零均值高斯白噪声特性,频率准确度较自由状态提高1个数量级。
图7所示,微步进频率控制后,输出信号1 s~20 s的短期频率稳定度略有不同程度下降,但20 s以上受控晶振频率稳定度显著提升,如表1所示,精细控制后,时频系统10 000 s的中长期频率稳定度由自由状态的7.88×10-11提高至3.16×10-14,提高3个数量级,有效抑制频率漂移特性。
调整前后的频率稳定度指标如表1所示,受调频量化噪声影响,输出信号1 s~20 s的短期频率稳定度略有不同程度下降,10 s的频率稳定度由原来的2.73×10-12下降到3.65×10-12,频率稳定度损失为25%,但最终实现的3.65×10-12短期稳定度仍满足精密定位对频率稳定性的容限要求。
基于上述研究结果与讨论,可得出以下结论:
①本文以快速精密定位服务为顶层约束,实现了频率精细控制的理论指导和定量化依据;
②本文方法显著提升了系统钟差精度,有效抑制了晶振频率漂移特性,调整过程平稳精准;
③以最小成本获取高稳定性和高精度控制效果为目标,为低轨导航卫星构建基于恒温晶振的高精度时频系统提供了高效可行的解决途径。
为满足复杂的空间环境适应性,可进一步开展在轨自适应调频参数寻优设计。
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doi: 10.12347/j.ycyk.20250707001
  • 接收时间:2025-07-07
  • 首发时间:2026-03-13
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  • 收稿日期:2025-07-07
  • 修回日期:2025-07-23
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    1.南京理工大学机械工程学院 南京 210000
    2.北京遥测技术研究所 北京 100076
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
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