scholarly journals CFAR Strategy Formulation and Evaluation Based on Fox’s H-function in Positive Alpha-Stable Sea Clutter

2020 ◽  
Vol 12 (8) ◽  
pp. 1273 ◽  
Author(s):  
Xu Liu ◽  
Shuwen Xu ◽  
Shiyang Tang
Keyword(s):  
False Alarm ◽  
Density Function ◽  
Closed Form Expression ◽  
Suitable Model ◽  
Constant False Alarm Rate ◽  
Sea Clutter ◽  
Strategy Formulation ◽  
Non Gaussian ◽  
Probability Density Function Pdf ◽  
Fox’S H Function

The problem of target detection in impulsive non-Gaussian sea clutter has attracted a lot of attention in recent years. The positive alpha-stable (PαS) distribution has been validated as a suitable model for the impulsive non-Gaussian sea clutter. Since the probability density function (PDF) of the PαS variable cannot be expressed as a closed-form expression, the research into constant false alarm rate (CFAR) detectors in PαS distributed sea clutter is limited. This paper formulates and evaluates some CFAR detectors, such as Greatest Of-CFAR (GO-CFAR), Smallest Of-CFAR (SO-CFAR), Order Statistic-CFAR (OS-CFAR) and censored mean level (CML) detectors, in PαS distributed sea clutter. Firstly, the Fox’s H-function is adopted to express the PDF of the PαS variable, and the cumulative density function based on Fox’s H-function is derived in this paper. Then, by use of the properties of the H-function and PαS distribution, exact expressions of the probabilities of false alarm and detection for CFAR detectors in the PαS background are derived. Some CFAR properties of these detectors in the PαS background are also explored. Numerical results based on derived expressions are given and verified by Monte Carlo simulation. Some analyses of detection performance from a practical perspective are also given.

Erratum

1993 ◽  
Vol 46 (3) ◽  
pp. 447-447
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Constant False Alarm Rate ◽  
Sea Clutter ◽  
Signal Differentiation ◽  
Signal Vidéo ◽  
Video Amplifier ◽  
Marine Navigation ◽  
Adaptive Signal

There was an error in Mr Richard Trim's paper, ‘Some causes of problems in the observation of standard racon marine beacons when observed by means of standard marine navigation radars’, which was published in the May 1993 issue of the Journal of Navigation. Section 3, paragraph 4 of page 276 should read:‘A third and very important cause of radar received-signal differentiation arises if a widely used form of automatic anti-sea-clutter processing is employed, since part of this processing is to differentiate the radar-received video so as to remove the d.c. term in the sea clutter echoes as part of the Constant False Alarm Rate (CFAR) processing. When such automatic sea clutter supression facilities are in operation, the gain level applied to the radar receiver video amplifier has an adaptive signal superimposed upon it which, while slow acting, generally follows the shape of the clutter returns on the received signal video, while being largely unaffected by the wanted echo returns such as those from ships, navigation marks, coastlines, etc. This effect may be reduced in the case of the very latest radar designs’.

scholarly journals Inhomogeneous Analysis of Novel Model of CFAR Approaches to Detect Two-Degrees of Freedom Partially-Correlated χ2-Targets

2021 ◽  
Vol 20 ◽  
pp. 28-43
Author(s):  
Mohamed Bakry El-Mashade
Keyword(s):  
False Alarm ◽  
Degrees Of Freedom ◽  
Detection Threshold ◽  
Detection Performance ◽  
Closed Form Expression ◽  
False Alarms ◽  
Artificial Noise ◽  
Constant False Alarm Rate ◽  
Two Degrees Of Freedom ◽  
Novel Strategy

Reliable and high performance radar systems have ubiquitous demand. The operation of such systems is affected by the presence of natural and artificial noise sources. One of the basic radar concepts is to decide whether the target is present or not. Meanwhile, the general objective of all radar detection schemes is to ensure that false alarms don't fluctuate randomly. Thus, to cope with an inhomogeneous changing clutter environment, it is beneficial to be able to detect both high- and low-fidelity targets while maintaining the rate of false alarm fixed. This calls for an adaptive thresholding strategy that vary the detection threshold as a function of the sensed environment, and most modern radars implement this approach automatically. The feature of constant false alarm rate (CFAR) activates the threshold in such a way that it becomes adaptive to the local clutter environment. Many alternatives have been proposed to achieve such demanded property. Owing to the diversity of the radar search environment (target multiplicity & clutter edges), there exists no universal CFAR procedure. This prompts the necessity to investigate the composite architecture as a novel strategy. The goal of this paper is to analyze the fusion of CA, OS, and TM processors in post-detection integration of M-pulses. The primary and outlying targets are assumed to obey χ 2 -distribution with two-degrees of freedom in their fluctuation. Closed-form expression is derived for the detection performance. Our simulation results show robust behavior of the new model in the absence as well as in the presence of outlying targets. In addition, a significant improvement of the detection performance of novel strategy over the individual CFAR detectors is noticed. Moreover, the outweighing, over Neyman-Pearson (N-P) detector, of the fusion model, in ideal background, is evidently demonstrated. This ability to obtain improved performance compared to existing models is the major contribution of this work.

scholarly journals Analysis of FM demodulator output noise with applications to FM telemetry

2006 ◽  
Vol 2006 ◽  
pp. 1-13 ◽  
Author(s):  
Rajendra Kumar
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Noise Power ◽  
Signal To Noise ◽  
Output Noise ◽  
Simplified Analysis ◽  
Modulation Schemes ◽  
Non Gaussian ◽  
Probability Density Function Pdf

We present an analysis for evaluating the probability density function (pdf) of the noise at the output of the frequency demodulator. It is shown that the noise is non-Gaussian and that for low to medium signal-to-noise power ratios, its pdf differs very significantly from the Gaussian pdf commonly assumed in simplified analysis. These results are very important for analyzing the performance of the PCM/FM type of modulation schemes used in telemetry systems as illustrated in the paper.

scholarly journals Robust CFAR Detection for Multiple Targets in K-Distributed Sea Clutter Based on Machine Learning

Symmetry ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 1482
Author(s):  
Jiafei Zhao ◽  
Rongkun Jiang ◽  
Xuetian Wang ◽  
Hongmin Gao
Keyword(s):  
Machine Learning ◽  
False Alarm ◽  
Clustering Algorithm ◽  
Spatial Clustering ◽  
Optimal Parameter ◽  
False Alarm Probability ◽  
Masking Effect ◽  
Constant False Alarm Rate ◽  
Sea Clutter ◽  
Cfar Detection

For K-distributed sea clutter, a constant false alarm rate (CFAR) is crucial as a desired property for automatic target detection in an unknown and non-stationary background. In multiple-target scenarios, the target masking effect reduces the detection performance of CFAR detectors evidently. A machine learning based processor, associating the artificial neural network (ANN) and a clustering algorithm of density-based spatial clustering of applications with noise (DBSCAN), namely, DBSCAN-CFAR, is proposed herein to address this issue. ANN is trained with a symmetrical structure to estimate the shape parameter of background clutter, whereas DBSCAN is devoted to excluding interference targets and sea spikes as outliers in the leading and lagging windows that are symmetrical about the cell under test (CUT). Simulation results verified that the ANN-based method provides the optimal parameter estimation results in the range of 0.1 to 30, which facilitates the control of actual false alarm probability. The effectiveness and robustness of DBSCAN-CFAR are also confirmed by the comparisons of conventional CFAR processors in different clutter conditions, comprised of varying target numbers, shape parameters, and false alarm probabilities. Although the proposed ANN-based DBSCAN-CFAR processor incurs more elapsed time, it achieves superior CFAR performance without a prior knowledge on the number and distribution of interference targets.

scholarly journals Effects of Compound K-Distributed Sea Clutter on Angle Measurement of Wideband Monopulse Radar

2017 ◽  
Vol 2017 ◽  
pp. 1-19
Author(s):  
Hong Zhu ◽  
Yujian Pan ◽  
Weiwei Wu ◽  
Ning Tai ◽  
Naichang Yuan
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Measurement Procedure ◽  
Angle Measurement ◽  
Conditional Probability Density ◽  
Sea Clutter ◽  
Compound K ◽  
Conditional Probability Density Function ◽  
Probability Density Function Pdf

The effects of compound K-distributed sea clutter on angle measurement of wideband monopulse radar are investigated in this paper. We apply the conditional probability density function (pdf) of monopulse ratio (MR) error to analyze these effects. Based on the angle measurement procedure of the wideband monopulse radar, this conditional pdf is first deduced in detail for the case of compound K-distributed sea clutter plus noise. Herein, the spatial correlation of the texture components for each channel clutter and the correlation of the texture components between the sum and difference channel clutters are considered, and two extreme situations for each of them are tackled. Referring to the measured sea clutter data, angle measurement performances in various K-distributed sea clutter plus noise circumstances are simulated, and the effects of compound K-distributed sea clutter on angle measurement are discussed.

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