Current Continuous Wave (CW) Doppler radar speed measurement systems lack the ability to distinguish multiple targets. Most systems can only identify the strongest (closest) target or the fastest target.
This dissertation is related to a fusion algorithm for a VIdeo-Doppler-radAR (Vidar) traffic
surveillance system. The Vidar systems uses a robust matching algorithm which iteratively matches
the information from a video camera and multiple Doppler radars corresponding to the same moving
vehicle, and a stochastic algorithm which fuses the matched information from the video camera and
Doppler radars to derive the vehicle velocity and angle information.
We use two heterogeneous sensors of very different modalities, the first a high resolution (1024x768 pixels) video camera operating at 30 Hz with a 1/3″ sony CCD fitted with a narrow field-of-view lens and the other a CW Doppler radar operating in the unlicensed Ka band (35 GHz) with
a maximum detection range of 3000 ft. First, a high resolution Time-Frequency representation of
the radar signal is obtained by employing the method of Time-Frequency reassignment. Then, the
angle information obtained from the video camera is fused with the information from the Doppler
radar to produce a velocity and angle track of the targets within the surveillance region.