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
In radar systems of automatic detection, an estimate of background clutter power is used to set the detection threshold. An interference saturated environment is frequently encountered in these systems (multiple targe...In radar systems of automatic detection, an estimate of background clutter power is used to set the detection threshold. An interference saturated environment is frequently encountered in these systems (multiple target situations). Therefore, the detection of signals in such an environment becomes one of the most important problems to be solved. The double-threshold algorithm is one of the more interesting detectors used in these situations. While the first threshold operation ensures that the calculation of the detection (second) threshold is based on a set of samples which is free of strong interferers and is therefore much more representative of the noise level, the second threshold is used to declare the presence or the absence of the radar target. The object of the present paper is to analyze the performance of such type of CFAR schemes when the radar receiver contains a noncoherent integrator amongst its basic elements. It is found that the processor detectabil ity loss is very low and the performance degradation, caused by interferers is quite small even if the number of outlying targets is large, given that the first threshold is properly chosen.展开更多
The low frequency line components of the radiated noise from an underwater target usually have both high spectrum level and sustained stability. This feature could be used to increase the detection performance of conv...The low frequency line components of the radiated noise from an underwater target usually have both high spectrum level and sustained stability. This feature could be used to increase the detection performance of conventional broadband energy integration method. The required spectrum level is theoretically discussed when the detection performance of the known line detection is better than that of broadband energy integration method. Under the condition of the target can be detected in line spectrum band, the relationship between the line spectrum level and signal to noise ratio （SNR） is also discussed. This paper proposes a line spectrum target detection method that a matrix using DC jump to fluctuations ratios of sub-band spatial spectrum and beam space output is constructed. This matrix acts as a filter that the line spectrum target with certain frequency and azimuth is passed at most. By fusing with the other sub band results, the conventional detection performance can be improved. At the same time, the applicable condition and detection performance are analyzed in the paper. The simulation and the sea trial data processing results show that the algorithm can effectively extract weak goal line spectrum target under the condition of multi-interference. The algorithm doesn＇t need multi-frame statistics and the detection performance is closer to the optimal line spectrum method.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.
文摘In radar systems of automatic detection, an estimate of background clutter power is used to set the detection threshold. An interference saturated environment is frequently encountered in these systems (multiple target situations). Therefore, the detection of signals in such an environment becomes one of the most important problems to be solved. The double-threshold algorithm is one of the more interesting detectors used in these situations. While the first threshold operation ensures that the calculation of the detection (second) threshold is based on a set of samples which is free of strong interferers and is therefore much more representative of the noise level, the second threshold is used to declare the presence or the absence of the radar target. The object of the present paper is to analyze the performance of such type of CFAR schemes when the radar receiver contains a noncoherent integrator amongst its basic elements. It is found that the processor detectabil ity loss is very low and the performance degradation, caused by interferers is quite small even if the number of outlying targets is large, given that the first threshold is properly chosen.
文摘The low frequency line components of the radiated noise from an underwater target usually have both high spectrum level and sustained stability. This feature could be used to increase the detection performance of conventional broadband energy integration method. The required spectrum level is theoretically discussed when the detection performance of the known line detection is better than that of broadband energy integration method. Under the condition of the target can be detected in line spectrum band, the relationship between the line spectrum level and signal to noise ratio （SNR） is also discussed. This paper proposes a line spectrum target detection method that a matrix using DC jump to fluctuations ratios of sub-band spatial spectrum and beam space output is constructed. This matrix acts as a filter that the line spectrum target with certain frequency and azimuth is passed at most. By fusing with the other sub band results, the conventional detection performance can be improved. At the same time, the applicable condition and detection performance are analyzed in the paper. The simulation and the sea trial data processing results show that the algorithm can effectively extract weak goal line spectrum target under the condition of multi-interference. The algorithm doesn＇t need multi-frame statistics and the detection performance is closer to the optimal line spectrum method.
