ANALYSIS OF CELL-AVERAGING BASED DETECTORS FOR χ^2 FLUCTUATING TARGETS IN MULTITARGET ENVIRONMENTS

The χ^2 family of signal fluctuation distributions represents the main fluctuation models which most radar targets follow it in their reflections. This family can be categorized as fluctuation distribution with two degrees of freedom and those with four degrees of freedom. The first category represents all important class of fluctuation models which when illuminated by a coherent pulse train, return a train of fully correlated pulses （Swerling Ⅰ model） or fully decorrelated pulses （Swerling Ⅱ model）. The detection of this type of fluctuating targets is therefore of great importance. This paper is devoted to the analysis of Cell-Averaging （CA） based detectors for the case where the radar receiver noncoherently integrates M square-law detected pulses and the signal fluctuation obeys 2 statistics with two degrees of freedom. These detectors include the Mean-Of （MO）, the Greatest-Of （GO） and the Smallest-Of（SO） schemes. In these processors, the estimation of the noise power levels from the leading and the trailing reference windows is based on the CA technique. Exact formulas for the detection probabilities are derived, in the absence as well as in the presence of spurious targets. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with the χ^2 fluctuation model with two degrees of freedom （SWI ＆ SWII）. The numerical results show that the MO version has the best homogeneous performance, the SO scheme has the best multiple-target performance, while the GO procedure does not offer any merits, neither in the absence nor in the presence of outlying targets.

EXACT ANALYSIS OF OS MODIFIED VERSIONS WITH NONCOHERENT INTEGRATION

This paper deals with the exact detection analysis of the Ordered-Statistic(OS) processor along with OS Greatest Of(OSGO) and OS Smallest Of(OSSO) modified versions, for M postdetection integrated pulses when the operating environment is nonhomogeneous. Analytical results are presented in multiple-target case as well as in regions of clutter power transitions. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with the SWII target fluctuation model. As the number of noncoherently integrated pulses increases,lower threshold values and consequently better detection performances are obtained in both homogeneous and multiple target background models. However, the false alarm rate performance of OSSO-CFAR(Constant False Alarm Rate) scheme at clutter edges is worsen with increasing the postdetection integrated pulses. As predicted, the OSGO-CFAR detector accommodates the presence of spurious targets in the reference window, given that their number is within its allowable range in each local window, and controls the rate of false alarm when the contents of the reference cells have clutter boundaries.

ABORT-like detector to combat active deceptive jamming in a network of LFM radars

This paper studies an electronic counter-counter measures（ECCM） scheme combating against deceptive electronic counter measure（ECM） techniques. An adaptive detector exploiting generalized likelihood ratio test（GRLT） criterion is applied to detect the presence of deceptive jamming in fractional Fourier transform（Fr FT） domain. First, the generating mechanism of spurious frequencies is analyzed based on the Volterra serial. The proposed nonlinear distortion model based on power amplifier behavior is robust in distortion analysis when the memory effect is considered.Second, a modified adaptive beamformer orthogonal rejection test（ABORT） like detector in closed form is built. The proposed detector can discriminate the echo and deceptive jamming adaptively by exploiting primary data and secondary data. This ECCM scheme is capable of guaranteeing the performance without the restriction of orthogonality, which is essential for the ABORT detectors. The expansion to radar network is discussed as a special case at the final part of this paper. Numerical simulations demonstrate the effectiveness of the proposed method.