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时间:2020-06-20
《低信噪比条件下快变多普勒频偏捕获算法.pdf》由会员上传分享,免费在线阅读,更多相关内容在行业资料-天天文库。
1、第54卷第5期电讯技术Vo1.54No.52014年5月TelecommunicationEngineeringMav2014doi:10.3969/j.issn.1001—893x.2014.05.005引用格式:赵睿,王彦文.低信噪比条件下快变多普勒频偏捕获算法[J].电讯技术,2014,54(5):553-558.[ZHAORui,WANGYan—wen.AFastChangingDopplerFrequencyOffsetAcquisitionAlgorithmunderLowSNR[J].TelEngineering,2014,54(5):553-558.]低信噪比
2、条件下快变多普勒频偏捕获算法赵睿料,王彦文(中国矿业大学(北京)机电与信息工程学院,北京100091)摘要:针对卫星移动通信低信噪比条件下快变多普勒频偏捕获提出了一种新的算法即基于搜索空间压缩的谱线循环平移算法。首先,介绍了现有的载波频偏捕获技术,分析其不能适应快变多普勒频偏条件的原因;其次,分析了多普勒变化率对载波频偏捕获的影响,主要考虑一次变化率与二次变化率将严重限制低信噪比情况下对载波频偏估计时非相干累加的有效性;最后,在此基础上,提出了低信噪比条件下快变多普勒频偏捕获的基于搜索空间压缩的谱线循环平移算法。对算法进行的Matlab仿真结果表明,其具有2~3dB的改善增益
3、,与最大似然算法相比,在性能仅有0.2dB损失的情况下运算量大大减少。关键词:低地球轨道星座;卫星移动通信;高动态信号;载波捕获;快变多普勒频偏;低信噪比中图分类号:TN911.72;TN914.42文献标志码:A文章编号:1001—893X(2014)05—0553-06AFastChangingDopplerFrequencyOfsetAcquisitionAlgorithmunderLowSNRZHAORui,WANGYan-wen(DepartmentofMechanicalElectrical&InformationEngineering,ChinaUniversi
4、tyofMining&Technology(Beijing),Beijing100091,China)Abstract:Anewalgorithmorthespectrumlinecircleshiftalgorithmbasedoncompressedsearchingspaceisproposedf_0rfastchangingDoppler~equencyoffsetacquisitionunderlowsignal—to—n0iseratio(SNR)forsatellitemobilecommunication.Firstly,currentcarrier~eque
5、ncyoffsetacquisitiontechnologiesarein—troduced,andthereasonwhythesetechnologiescannotadapttofastchangingDoppler~equencyoffsetac—quisitionisanalyzed.Then,theeffectofchangingrateofDoppler~equencyoffsetoncarrier~equencyoff-setacquisitionisanalyzed.Thesituationthatthefirstorderchangingrateandse
6、condorderchangingrateaffectcarrieracquisitionisconsideredemphatically.ThechangingrateofDoppler~equencyoffsetserious—lyreducestheeffectivenessofnon——coherentaccumulationduringcarrier~equencyoffsetestimationatlowSNR.Finally,onthisbase,thespectrumlinecircleshiftalgorithmbasedonthecompressedsea
7、rchingspaceisprovidedandsimulatedwithMatlab.Theresultshowsthatthealgorithmhasgainimprovementof2—3dB.Comparedwithmaximumlikelihood(ML),theproposedalgorithmlosses0.2dBperformance,however,amountofcalculationisgreatlyreduced.Keywords:lowearthorbitconstellati
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