With the development of intelligent transportation systems, traffic supervision radar with wide coverage plays a crucial role in traffic management and vehicle-road coordination. The correlation between Doppler frequency and azimuth has been widely validated in wide coverage traffic supervision radar for high-precision velocity measurement. However, angular glint and noise of the nearby targets lead to a decrease in correlation between the azimuth and Doppler frequency, which negatively impacts the accuracy of velocity estimation. Currently, adopting separate filtering strategies for target azimuth and Doppler frequency has limited performance in enhancing correlation. This paper presents a joint observation model for azimuth and Doppler frequency to achieve the extraction of interrelated components from subspaces, which improves the accuracy of velocity measurement. The effectiveness of this approach is validated using data obtained from X-band and Ku-band sensors.
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