Implementation of Hough Transform as track detector

Hough Transform is a convenient tool for features extraction from images. In this paper an implementation of Hough Transform is considered for automatic track initiation in the surveillance radar space. The need of track initiation arises when there are many moving objects in the sensor surveillance volume and when it is not clear which measurement to which target belongs. If the type of target trajectories is known, the trajectories can be easily detected by performing corresponding Hough transform on the track image. Here, the effectiveness of the Hough transform track initiator is discussed. The influence of Hough parameter space granularity upon probability of track detection is analyzed. Analytical expressions for probability of track detection using Hough Transform are derived in the presence of normal distributed additive system noise, measurement noise and without any noises. A new parameter space structure, matching with measurement errors is proposed. The Monte Carlo simulation confirms received analytical result.