Research on signal processing algorithm of Doppler speed measurement radar under clutter background
Doppler speed measurement radar has the advantages of wide range of speed measurement,high speed measurement accuracy and strong reliability,and is widely used in the field of wheel-rail and maglev transportation in China.It is necessary to consider the interference of clutter to Doppler signal in the process of speed measurement radar,so it is important to study the signal processing method under the background of track ground clutter to improve the accuracy of speed measurement and ensure the safety of driving.In this paper,three typical probabilistic and statistical models,namely Kernel distribution,Weibull distribution and Gamma distribution,are theoretically analyzed,clutter measurement experiments are carried out using 77 GHz+24 GHz dual-band vehicle-mounted velocity radar.The results show that the statistical characteristics of the track ground clutter data of the vehicle-mounted speed measurement radar developed in this paper follow the Kernel distribution.In the background of clutter,firstly,the least mean square adaptive filtering method is used to de-noise the measured signal,and the improved Burg algorithm is used to estimate the spectrum to achieve high-precision velocity measurement.Experiments have verified that the proposed algorithm can effectively suppress clutter and improve the signal-to-noise ratio,and the final velocity measurement error is less than 0.5 km/h at low speed and less than 0.5%when the speed is greater than 50 km/h.
Kernel distributionnoise wave peculiarityLMS adaptive filteringimproved Burg algorithmDoppler radar
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NSTL
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