# A Radio Burst Detection Method Based on the Hough Transform

## TL;DR

This paper introduces a rapid and efficient radio burst detection method using the Hough transform, which simplifies identifying dispersed signals in radio astronomy data by transforming curves into points in parameter space.

## Contribution

The paper presents a novel application of the Hough transform for incoherent dedispersion and fast radio burst detection, improving speed and simplicity over traditional methods.

## Key findings

- Method is fast and effective in radio quiet environments.
- Performance tested with simulated noise and real data.
- Detection peaks vary with truncation thresholds.

## Abstract

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 time-frequency data 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 an easier way for the detection of radio burst. By choosing an appropriate truncation threshold, in a reasonably radio quiet environment, i.e. with radio frequency interferences (RFIs) present but not dominant, the computing speed of the method is very fast. 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.