A Radio Bursts Detection Method Based on Hough Transform.

We present a simple and fast method for incoherent dedispersion and fast radio burst (FRB) detection based on the Hough transform, which is widely used for feature extraction in image analysis. The Hough transform maps a point in the data maps to a straight line in the parameter space, and points on the same dispersed $f^{-2}$ curve to a bundle of lines all crossing at the same point, thus the curve is transformed to a single point in the parameter space, enabling a simple way for the detection of radio burst. By choosing an appropriate truncation threshold, the method has a complexity of $\text{max}(N_{t}, N_{f}) N_{d}$ where $N_{f}$, $N_{t}$ and $N_{d}$ are the dimension of the data in frequency, time, and dispersion measure, respectively, this is lower than other existing methods. Using simulation data of different noise levels, we studied how the detected peak varies with different truncation thresholds. We also tested the method with some real pulsar and FRB data.