CFAR "Point Cloud"

The information below describes how the “CFAR point cloud” output from a radar is derived from the radar’s view of the environment surrounding it.

This mode is just one approach to extracting features from the scene that the radar presents.

The International Research Journal of Engineering and Technology (IRJET) Volume: 05 Issue: 07 describes Constant False Alarm Rate (CFAR) Detection as

an adaptive algorithm used in Radar systems to detect the target echoes against a background of noise and clutter. The role of the constant false alarm rate circuit is to determine the threshold above which any returning signal or echo can be considered probably to be originated from a target. In most radar systems, the threshold is set to achieve a required false alarm rate (or equivalently, probability of false alarm). Cell-Averaging CFAR (CA - CFAR) is a type of CFAR detection where the threshold is estimated by scanning a block of cells around a cell-under-test (CUT) and calculating the average power level. In CA – CFAR, a target is declared to be present if the power level in the CUT exceeds the average power level found from adjacent block of cells. This paper shows the principle of CA – CFAR detector, threshold factors for CFAR detection, factors affecting CFAR detection and CFAR loss

The subsequent text of that article expands on the technicalities around Cell-Averaging-CFAR.

In very simplistic terms, a single azimuth of radar data is processed. A sliding window approach identifies whether the central datapoint within the window is notably larger (in power terms) than the mean value of data within the window. If the central datapojnt exceeds the local mean by a defined threshold, then the point is considered to be a valid object within the radar’s view.

Note that In order to increase the capability & sensitivity of this approach, (n) datapoints either side of the central point in the window are NOT considered when calculating the local mean.

Radar firmware versions 3.1.0.325 and later support the generation of a Cell-Averaged-CFAR “pointcloud” data output format via a UDP stream
https://navtechradar.atlassian.net/wiki/spaces/PROD/pages/2229239935/UDP+Networking#Point-Cloud-Data.


Cell-Averaging CFAR feature extraction:
Pictorial guide to processing steps

The images below have been captured from a simple CA-CFAR calculation sheet, working with a single azimuth of raw radar output. The calculation sheet can be downloaded here:

  File Modified

Microsoft Excel Spreadsheet CA_CFAR Demo.xlsx

Dec 06, 2023 by John Marshall

Showing a section of a typical raw radar output from a single azimuth (real data)
Radar return (power) as vertical axis vs bin number in horizontal axis

 


 

 

Showing raw radar output (blue) vs a windowed local average (red) calculated from 40 bins' data