Christo Kabakchiev

Adaptive CFAR PI Processor for Radar Target Detection in Pulse Jamming

A new parallel algorithm for signal processing and a parallel systolic architecture of a CFAR processor with adaptive post detection integration (API) are presented in this paper. The processor proposed is used for effective target detection in a single range resolution cell of a radar when echoes from small airborne targets are performed in conditions of pulse jamming. The main property of the algorithm proposed is its ability automatically to determine and censor the unwanted samples corrupted by pulse jamming in both the two-dimensional reference window and the test cell before noise level estimation. In such a way the influence of pulse jamming environment over adaptive thresholding is reduced to minimum. Statistical analysis of the algorithm for target detection shows that the signal-to-noise ratio losses are insignificant even if the power and the frequency of pulse jamming are extremely high. The systolic architecture of the CFAR API is designed. Basic measures of the systolic architecture are the number of processor elements, the computational time and the speed-up needed for real-time implementation.

Performance of Hough Detectors in Presence of Randomly Arriving Impulse Interference

In the following paper are investigated several types of Hough detectors with CFAR processors in order to choose the most efficient one in the presence clatter and randomly arriving impulse interference environment. The Hough detector with fixed threshold is compared to other five types of Hough detectors. These are one and two-dimensional Hough CFAR detectors - a Hough CA CFAR (Cell Average Constant False Alarm Rate) detector, a Hough EXC (Excision) CFAR detector, a Hough CFAR BI (Binary Integration) detector, a Hough EXC CFAR BI (Excision Constant False Alarm Rate with Binary Integration) detector and a Hough API (Adaptive censoring Post detection Integration) CFAR detector. The achieved results reveal that the Hough detector with the API CFAR algorithm is the most effective. The research work is performed in MATLAB computational environment.

Hough detector with adaptive non-coherent integration for target detection in pulse jamming

It is shown that the Hough transform with binary integration of the data in parameter space may be used for improvement of target detection in the presence of strong pulse jamming (PJ). The algorithm proposed may be used for effective detection of small airborne targets whose trajectories are straight radial lines. The expressions for detection probability evaluation are derived for a target model according to the Swerling case II. The expressions obtained are applied to the typical surveillance radar. The results show that the algorithm proposed allows one sufficiently to reduce the losses in the signal-to noise ratio (SNR) in comparison to the CA CFAR detector with non-coherent integration when the PJ intensity is very strong. It is shown that the algorithm proposed is very effective even if the probability of PJ appearance is very high.

Radar Detection and Track Determination with a Transform Analogous to the Hough Transform

We propose in this paper the standard Hough transform to be changed with analogous polar Hough transform (PHT). The obtained polar Hough detection algorithm is very comfortable for track and target detection because the input parameters of this transform are the output parameters of the search radar. Another important advantage is the transform stability when the target changes its speed and flies at different azimuths.

Techniques for CFAR radar image detection in pulse jamming

The presence of strong pulse jamming in a reference window used by Cell-Averaging CFAR detectors for noise power estimation can cause drastic degradation in performance even if the CA CFAR detectors employ binary integration. The technique for pulse jamming suppression discussed in this work is the use of filters matched to a broadband transmitted pulse in combination with an excision CFAR detector where strong samples are excised from the reference window prior to the cell-averaging operation. In particular, the excision CEAR detector with binary integration is considered in situation when the duration of broadband pulse transmission with phase-code-modulation and the average repetition interval of pulse jamming are commensurable. The mathematical formulas for analysis of the excision CFAR binary integration processor are derived for the case of broadband pulse transmission in the presence of pulse jamming. In addition, the possibility for real-time implementation of the excision CFAR binary integration processor over a multiprocessor system based on signal processors ADSP-21062, is analytically evaluated. The computation cost is defined as the number of signal processors and computation steps necessary for real-time implementation of the excision CFAR binary integration processor.

CFAR radar image detection in pulse jamming

It is shown that the appearance of strong pulse jamming in the reference window causes drastic degradation in the performance of CA CFAR (cell averaging constant false alarm rate) binary integration processors. The technique for pulse jamming suppression employed in this work is the use of filters matched to a broadband pulse with a large time-bandwidth product. In particular, the situation when the duration of broadband pulse transmission with phase-code-modulation and the average repetition interval of pulse jamming are commensurable, is considered in the paper. The mathematical formulas for analysis of the conventional CA CFAR binary integration processor in conditions of pulse jamming are derived for the case when the broadband pulse transmission is used. In addition, the possibility for real-time implementation of the CA CFAR binary integration processor over a multiprocessor system based on signal processors ADSP-21062, is analytically evaluated. The computation cost is defined as the number of signal processors and computation steps necessary for real-time implementation of the CA CFAR binary integration processor.

Detection acceleration in Hough parameter space by K-stage detector

The sequential algorithm for target detection in impulse environment by K-stage processing in polar Hough (PH) space is investigated. This algorithm permits the search radar to minimize the time of target detection, because the sequential detector used minimizes the number of the necessary radar antenna scans, while the conventional detector uses a fix scan number. The aim of our study is to minimize the detection time by minimizing the number of radar scans, when the detectors parameters and characteristics are fixed. The average estimates of the minimal number of scans are obtained using the Monte Carlo simulation approach when the detectors parameters are fixed. The proposed algorithm is simulated in MATLAB environment. The efficiency factor of the investigated detector for radar signal detection and track determination in conditions of binomial distributed impulse interference is obtained by using Monte-Carlo approach. The prepositional detector, compared to the conventional detector, accelerates the detection procedure several times.

Air target detection with a GPS forward-scattering radar

Forward scattering radar (FSR), as a specially configured bistatic radar, is provided with the capabilities of air target detection by using the GPS signal shadow. This paper discusses the experimental results obtained by GPS receiver near to Sofia airport. This research aims to demonstrate the feasibility of the Forward Scattering GPS system to detect air targets.

STAP approach for DOA estimation using microphone arrays

In this paper, the Space-Time Array Processing (STAP) approach is applied to sound source localization using adaptive microphone arrays. Two beamforming methods, conventional and MVDR are used for estimating the direction-of arrival (DOA) of sound signals arrived at the microphone array from different sensors in the observation area. The simulation scenario describes a situation where three sensors generating three different sound signals (warning, alarm and emergency) and one source of natural noise (car) are located at various points in the observation area. The results obtained demonstrate that in contrast to the conventional method of beamforming the MVDR gives accurate estimates of The DOA of all sound signals generated by sensors in the observation area.

Hough detector analysis by means of Monte Carlo simulation approach

In the present paper, an algorithm for target detection that exploits the Hough transform is proposed. The target is detected by the Hough detector. The effectiveness of the algorithm proposed is formulated in terms of a quality parameter - the probability of detection. The quality parameter is estimated using the Monte Carlo simulation approach. We compare the results of detection achieved by both analytical and simulational approaches. The results are obtained for Swerling II target model in conditions of randomly arriving impulse interference.