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

Abstract

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 U. The expressions obtained are applied to the typical surveillance radar. The results show that the algorithm proposed allows 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.

Netted radar Hough detector in randomly arriving impulse interference

“…In such a detector, target detection is declared if the signal sample x 0 exceeds a preliminary determined adaptive threshold H D . In case of Poisson and binominal distribution of impulse interference, the analytical expressions for calculating the detection and false alarm probability are obtained in [3,4,[15][16][17].…”

“…The centralized Hough detector is compared to decentralized Hough detector by detection probability for different binary rules in Hough parameter space; the results are shown on Figure 5. In order to analyze the quality of the Hough detectors we consider radars with equal parameters, similar to those in [2,[9][10][11][15][16][17]. The results have shown that the detection probability of centralized detector is almost twice as much than distributed detector.…”

“…False alarms caused by impulse noise make difficult track detection. The improvement in target and trajectory detection on the non-homogeneous background (impulse interference) is possible by using the HT for CFAR detection [3,4,[15][16][17]. The Hough detection scheme includes a CFAR detector for signal detection in the scan area, the HT for mapping the target distance measurements from the scan area into the parameter space, binary integration of data in the parameter space and, finally, linear trajectory detection.…”

“…The Hough detection scheme includes a CFAR detector for signal detection in the scan area, the HT for mapping the target distance measurements from the scan area into the parameter space, binary integration of data in the parameter space and, finally, linear trajectory detection. These CFAR Hough detectors have been studied in cases when the target moves at a constant velocity in the same azimuth cell [3,4,[15][16][17]. There are modifications of a detection algorithm where the HT is used for image processing after conversion of radar data from the polar coordinate system to the Cartesian system associated with radar [5,19].…”

Detection Acceleration in Hough Parameter Space by K-Stage Detector

“…The use of the standard Hough transform (SHT) for target detection and track determination in white Gaussian noise is introduced by Carlson in [1]. An approach for constant false alarm rate (CFAR) detection by means of SHT for track and target detection in conditions of non-homogeneous background is considered by Behar in [2,3,4]. The Hough detection scheme includes a CFAR signal detector in the area of observation, HT of the target distance measurements from the observation area into the parameter space, binary integration of data in the parameter space and linear trajectory detection.…”