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Research On The Method Of Radar Speed Estimation And Target Detection On Non-Stationary Platform

Posted on:2022-03-16Degree:MasterType:Thesis
Country:ChinaCandidate:Y ZhaoFull Text:PDF
GTID:2518306575483054Subject:Control Engineering
Abstract/Summary:PDF Full Text Request
The traditional radar target detection algorithm is only suitable for the detection of moving targets when the radar is stationary.If the radar is on a moving platform,it will cause great interference to the target detection work when the platform speed is unintelligible.Aiming at the problem of false alarms in the two-dimensional target detection algorithm when the speed of the radar moving platform is unknown and the radar cannot work normally,a method for estimating the speed of the non-stationary platform radar and target based on clutter spectrum statistics is proposed.Linear Frequency Modulated Continuous Wave(LFMCW)radar uses Constant False Alarm Rate(CFAR)to improve target detection performance under a non-stationary motion platform.At the same time,it collects clutter spectrum data to obtain the radar.The speed of the moving platform and the target.Through the field test,under four kinds of environments,two human simulate two simultaneous moving targets.One target puts a 24 GHz radar on the body to simulate a motion platform,the other is a moving target,and two The targets move in the same direction.Experimental results show that the algorithm has an average root mean square error(Root Mean Square Error,RMSE)of 0.056 m/s for the speed of the radar moving platform in four different scenarios,and an average RMSE of 0.073 m/s for the target speed.According to different scenarios,the Clutter pattern on the spectrogram is different,the deep learning algorithm is used to realize the scene recognition and platform speed estimation of the radar platform.The experimental results of comparing different algorithms show that the average classification accuracy of the Visual Geometry Group(VGG)model can reach 96.96%.the Faster Region with Convolutional Neural Network Features(Faster Region with Convolutional Neural Network Features,Faster R-CNN)algorithm to achieve clutter detection and platform speed estimation,the experimental results show that the radar motion platform speed estimation in four different scenarios,The average RMSE is 0.034m/s.Figure 52;Table 20;Reference 49...
Keywords/Search Tags:spectrum statistics, speed estimation, scene recognition, clutter detection
PDF Full Text Request
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