基于BO-XGBoost的弯道交通微波识别与预警技术研究

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中图分类号：TN709-34 文献标识码：A 文章编号：1004-373X（2026）09-0185-06

BO-XGBoost-based microwave recognition and early warning technology for bend traffic

Yan Chengfeng，Xiong Lun，Lu Yongxiong （SchoolofOptical InformationandEnergyEngineering，WuhanInstituteofTechnology，Wuhan43O2o5，China）

Abstract：Machinelearningand microwaverecognitiontechnologycanofersmarter solutions forbend warning systems.A low-cost10.52GHzmicrowaveradarisusedtodetectmovingtargetsontheroad.Byanalyzingtheradarechocharacteristicsof vehicles，two-whelers，andpedestrians，12featureparametersaredefinedandextractedfromthesignal'stime-frequency diagram，frequency-amplitudeplot，andinstantaneousDoplerfrequency-timecurve，soastoconstructfeaturevectors.A three-classdatasetiscreatedwithpedestrians，two-wheelers，andvehiclesastheargetcategories，andtheSMOTE（synthetic minorityoversamplingtechnique）algorithmisappliedtoeliminatetheclassimbalanceof thedataset.TheXGBoost（extreme gradientboosting）algorithmmodelisexamined，andafteroptimizationusingtheBayesianoptimizationalgorithm（BOA），its macro-averageaccuracyatefortargetrecognitionreaches95.1%.Finallanintellgentbendwaringsystemisdesignedbased on this microwave identification technology.To sum up，this scheme has a certain practical value.

Keywords：microwave radar;feature extraction; machine learning; XGBoost; Bayesianoptimization;bend warning

0 引言

弯道使道路使用者产生视野盲区，成为交通事故常发地点。（剩余7354字）