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 d...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.展开更多
To mitigate the deleterious effects of clutter and jammer, modern radars have adopted adaptive processing techniques such as constant false alarm rate(CFAR) detectors which are widely used to prevent clutter and noise...To mitigate the deleterious effects of clutter and jammer, modern radars have adopted adaptive processing techniques such as constant false alarm rate(CFAR) detectors which are widely used to prevent clutter and noise interference from saturating the radar’s display and preventing targets from being obscured.This paper concerns with the detection analysis of the novel version of CFAR schemes(cell-averaging generalized trimmed-mean,CATM) in the presence of additional outlying targets other than the target under research. The spurious targets as well as the tested one are assumed to be fluctuating in accordance with the χ~2-model with two-degrees of freedom. In this situation, the processor performance is enclosed by the swerling models(SWI and SWII). Between these bounds, there is an important class of target fluctuation which is known as moderately fluctuating targets. The detection of this class has many practical applications. Structure of the CATM detector is described briefly. Detection performances for optimal, CAM, CA, trimmed-mean(TM) and ordered-statistic(OS) CFAR strategies have been analyzed and compared for desired probability of false alarm and determined size of the reference window. False alarm rate performance of these processors has been evaluated for different strengths of interfering signal and the effect of correlation among the target returns on the detection and false alarm performances has also been studied. Our numerical results show that, with a proper choice of trimming parameters,the novel model CAM presents an ideal detection performance outweighing that of the Neyman-Pearson detector on condition that the tested target obeys the SWII model in its fluctuation. Although the new models CAS and CAM can be treated as special cases of the CATM algorithm, their multi-target performance is modest even it has an enhancement relative to that of the classical CAcheme. Additionally, they fail to maintain the false alarm rate constant when the operating environment is of type target multiplicity. Moreover, the non-coherent integration of M pulses ameliorates the processor performance either it operates in homogeneous or multi-target environment.展开更多
文摘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.
文摘To mitigate the deleterious effects of clutter and jammer, modern radars have adopted adaptive processing techniques such as constant false alarm rate(CFAR) detectors which are widely used to prevent clutter and noise interference from saturating the radar’s display and preventing targets from being obscured.This paper concerns with the detection analysis of the novel version of CFAR schemes(cell-averaging generalized trimmed-mean,CATM) in the presence of additional outlying targets other than the target under research. The spurious targets as well as the tested one are assumed to be fluctuating in accordance with the χ~2-model with two-degrees of freedom. In this situation, the processor performance is enclosed by the swerling models(SWI and SWII). Between these bounds, there is an important class of target fluctuation which is known as moderately fluctuating targets. The detection of this class has many practical applications. Structure of the CATM detector is described briefly. Detection performances for optimal, CAM, CA, trimmed-mean(TM) and ordered-statistic(OS) CFAR strategies have been analyzed and compared for desired probability of false alarm and determined size of the reference window. False alarm rate performance of these processors has been evaluated for different strengths of interfering signal and the effect of correlation among the target returns on the detection and false alarm performances has also been studied. Our numerical results show that, with a proper choice of trimming parameters,the novel model CAM presents an ideal detection performance outweighing that of the Neyman-Pearson detector on condition that the tested target obeys the SWII model in its fluctuation. Although the new models CAS and CAM can be treated as special cases of the CATM algorithm, their multi-target performance is modest even it has an enhancement relative to that of the classical CAcheme. Additionally, they fail to maintain the false alarm rate constant when the operating environment is of type target multiplicity. Moreover, the non-coherent integration of M pulses ameliorates the processor performance either it operates in homogeneous or multi-target environment.
