Bojan Zrnic

The database of radar echoes from various targets with spectral analysis

In this paper we describe a database, noted as RadEch Database, containing radar echoes from various targets. The data has been collected in controlled test environments at the premises of Military Academy — Republic of Serbia. Our goal is to provide a balanced and comprehensive database to enable reproducible research results in the field of classification of ground moving targets (pattern recognition). A time-frequency analysis of radar echoes has been performed, in order to identify the main features of the various targets. The RadEch Database is freely available for download and we hope that our database provides researchers with a valuable tool to benchmark and improve the performance of classification algorithms.

A New Model of CFAR Detector

Abstract This paper presents a new model of the CFAR (Constant False Alarm Rate) detector. Mentioned CFAR detector is named cell-averaging-trimmed-mean CFAR (CATMCFAR), which is a combination of cell-averaging CFAR and trimmed mean CFAR. It is implemented in the receiver of the software defined radar. Expressions for the probability of detection, the probability of false alarm and the average decision threshold are derived. The article presents detection of simulated radar targets in Weibull clutter and real radar targets in real clutter and compares characteristics of new CATM-CFAR with some realized well known CFAR detectors.

Cepstrum-based analysis of radar Doppler signals

The main tasks of ground surveillance radars for security and perimeter protection are detection and classification of moving ground targets. In typical radar systems, target detection is fully automated, but the target classification requires human involvement. In this paper, we consider received radar echoes data of ground moving targets, and corresponding signals using cepstrum coefficients. The objective of the paper is to identify and validate features characterizing the different classes of targets, and subsequently extract features for classification. We will show examples on Radar Echoes Database. This database, named RadEch Database, contains radar echoes that are collected in controlled test enviroments at the premises of Military Academy — Republic of Serbia. Database purpose is to enable reproducible research results in the field of classification of ground moving targets (pattern recognition).

Detection of very close targets by fusion CFAR detectors

In this paper the new application results of Linear and NonLinear Fusion Constant False Alarm Rate (LF-CFAR and NLFCFAR) detectors are presented. Detection of very close targets per azimuth and per range is considered. The entire simulation is done on the basis of the software defined radar receiver. All used CFAR detectors are implemented in mentioned model of the radar receiver. Also, a comparative analysis in detection of very close targets of fusion CFAR detectors versus single CACFAR (Cell Averaging CFAR), OS-CFAR (Ordered Statistic CFAR) and TM-CFAR (Trimmed Mean CFAR) is done. The targets are simulated in a real clutter

Nonlinear fusion CFAR detector

This paper presents a new model of the Nonlinear Fusion Constant False Alarm Rate detector. Mentioned detector is some kind of modification of fusion CFAR detector. Also, it is implemented in the receiver of the software defined radar. Approach of this new detector is based on parallel operation of three well-known types of CFAR detectors: Cell Averaging, Ordered Statistic and the Trimmed Mean CFAR. In this case probability of false alarm rate has not the same value in each single CFAR algorithm, as it was in the realization of linear fusion CFAR detector before. The aim of this work is elimination of the largest possible number of false targets with the least possible disruption of the probability of detection of real radar targets. The paper presents detection of real radar targets in real clutter. Also, we will compare the characteristics of nonlinear with linear fusion CFAR detector.