Milenko Andric

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.

Entropy-based algorithm for speech recognition in noisy environment

This paper presents an entropy-based algorithm for endpoint detection and speech recognition in noisy environments. Entropy was developed to identify the speech segments accurately. Results show that this entropy-based algorithm outperforms the energy-based algorithms in putting the endpoints of speech nearly to its real value.

Estimation and Extraction of Radar Signal Features Using Modified B Distribution and Particle Filters

Abstract The research analyses the application of particle filters in estimating and extracting the features of radar signal time-frequency energy distribution. Time-frequency representation is calculated using modified B distribution, where the estimation process model represents one time bin. An adaptive criterion for the calculation of particle weighted coefficients whose main parameters are frequency integral squared error and estimated maximum of mean power spectral density per one time bin is proposed. The analysis of the suggested estimation application has been performed on a generated signal in the absence of any noise, and consequently on modelled and recorded real radar signals. The advantage of the suggested method is in the solution of the issue of interrupted estimations of instantaneous frequencies which appears when these estimations are determined according to maximum energy distribution, as in the case of intersecting frequency components in a multicomponent signal.

Time–Frequency Distribution Analyses of Ku-Band Radar Doppler Echo Signals

Abstract Real radar echo signals of a pedestrian, vehicle and group of helicopters are analyzed in order to maximize signal energy around central Doppler frequency in time–frequency plane. An optimization, preserving this concentration, is suggested based on three well-known concentration measures. Various window functions and time–frequency distributions were optimization inputs. Conducted experiments on an analytic and three real signals have shown that energy concentration significantly depends on used time–frequency distribution and window function, for all three used criteria.

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).

RESPONSES OF THE IONOSPHERIC D-REGION TO PERIODIC AND TRANSIENT VARIATIONS OF THE IONIZING SOLAR Lyα RADIATION

Solar radiation has the most important role in periodical variation of terrestrial atmospheric properties. Under unperturbed ionospheric conditions, the solar Lyα line has a dominant influence on ionization processes in the lowest ionospheric layer, the so called D-region. In this paper, we present periodical and transient variations in influences of the Lyα radiation on this ionospheric layer. In the case of periodical lower ionospheric changes we consider diurnal, seasonal and solar cycle variations and show analysis of acoustic and gravity waves induced by solar terminator. Influences of solar flares and eclipses on this atmospheric layer are analyzed as examples of sudden ionospheric disturbances. For decades, Very Low Frequency radio signals (3 – 30 kHz) are successfully used as a tool for monitoring of changes in the lower ionosphere, based on radio wave propagation through Earth-ionosphere waveguide along given trajectories and registration of their physical parameters (amplitude and phase delay). For the analysis conducted in this paper, we used records of the VLF DHO signal, emitted on 23.4 kHz frequency from transmitter in Germany and received in Serbia.

Expert system based on hidden Markov models for recognition of radar targets

Design of an expert system based on Hidden Markov Models for recognition of radar targets in a zone of ground surveillance radar is presented in the paper. Parameters of the real radar echo signal represented in a form of autoregressive models are used as an input of the designed expert system. The real radar echoes have been collected for the purpose of this research. Obtained results show that designed system has some certain advantages, but there are also some limitations in recognition of the analyzed sequences.

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

Analysis of human radar echo signal using warped discrete fourier transform

Use of the warped discrete Fourier transform for the time-frequency analysis of the signal on the audio-output of pulse-Doppler radar is examined in this research. The discrete Fourier transform is calculated in points in z-plane that are equidistantly distributed on the unit circle, while the warped discrete Fourier transform is calculated in points that are unevenly distributed on the unit circle. The time-dependent warped discrete Fourier transform for the analysis of the simulated and measured radar signals from a walking human was applied in this research. The results of the time-frequency analysis of radar signals using this transformation are compared with the spectrogram. The results show that the application of the warped discrete Fourier transformation in the radar signal analysis provides a higher concentration of energy around the central Doppler frequency comparing to the spectrogram.