No abstract

The paper introduces a new class of adaptive CFAR methods to cope with the problem of outliers due to the presence of clutter edges and interfering targets. A fundamental distinction between the proposed approach and existing adaptive CFAR approaches is that in order to maintain robust performance the former uses information on positions at which estimated outlier-free cells appear in the full reference window and the statistics of the sample in the cell under test. The performance of one of the possible implementations of new adaptive CFAR methods is studied and compared with that of an existing adaptive CFAR approach. The results show significant advantages of the proposed class of adaptive CFAR methods in both the false alarm regulation property and detection performance.

The paper introduces a new method for eliminating multiple-time-around detections in coherent pulsed radar systems with single constant pulse repetition frequency. The method includes the phase modulation of transmit pulses and corresponding phase demodulation at reception, which is matched to signals from the unambiguous range interval, and subsequent coherent integration followed by successive CFAR processing in range and Doppler domains. The performance of the proposed method is studied by means of statistical simulations. It is shown that the elimination performance can be essentially improved by optimizing the transmit phase modulation code. The optimization problem is formulated in terms of least-square fitting the power spectra of multiple-time-around target signals to a uniform power spectrum. Several optimum biphase codes are designed and used in the performance analysis. The analysis shows that the method can provide very high probability of elimination without noticeable degradation in the detection performance for targets from the unambiguous range interval.

An algorithm for detection of continuous-wave noise jamming in two-dimensional surveillance radar is proposed. The algorithm is highly immune to strong interfering spikes due to using censored video integration of range noise samples collected during dwell time for each azimuth resolution cell. To detect noise jamming the algorithm applies order statistics CFAR to a sequence of azimuthal samples resulted from censored video integration in range. The detection performance of the algorithm in the absence of interference is evaluated numerically by means of an integral equation and verified using statistical simulations. In the presence of infinitely strong spikes the detection and false alarm performances are estimated using statistical simulations.

No abstract