Object Detector on Coastal Surveillance Radar Using Two-Dimensional Order-Statistic Constant-False Alarm Rate Algoritm
Abstract: This paper describes
the development of radar object detection using two dimensional constant false
alarm rate (2D-CFAR). Objective of this development is to minimize noise
detection if compared withthe previous algorithm that uses one dimensional
constant false alarm rate (1D-CFAR) algorithm such as order-statistic (OS)
CFAR, cell-averaging (CA) CFAR, AND logic (AND) CFAR and variability index (VI)CFAR
where has been implemented on coastal surveillance radar. The optimum detection
result in coastalsurveillance radar testing when Pfa set to 1e-2, Kth set to
3/4*Nwindow and Guard Cell set to 0. Principle of2D-CFAR algorithm is combining
of two CFAR algorithms for each array data of azimuth and range. Orderstatistic
(OS) CFAR algoritm is implemented on this 2D-CFAR by fusion rule of AND
logic.The algorithm of 2D-CFAR is developed using Microsoft Visual C++ 2008 and
the output of 2D-CFAR is plotted on PPIscope radar using GDI+ library. The
result of 2D-CFAR development shows that 2D-CFAR can minimizenoise detected if
compared with 1D-CFAR with the same parameter of CFAR. Best performance of
2DCFAR in object detection when Nwindow set to 128. The time of software
processing of 2D-CFAR is about two times longer than the 1D-CFAR.
Author: Dayat Kurniawan,
Purwoko Adhi, Arief Suryadi Satyawan, Iqbal Syamsu, Teguh Praludi
Journal Code: jptkomputergg150051
