Optimal radar threshold determination in Weibull clutter and Gaussian noise

Morgan, Charles G.; Moyer, Lee R.; Wilson, Robert R.

doi:10.1109/62.486736

Cited by 7 publications

(3 citation statements)

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“…McMillan [13] used a similar approach to calculate the probability of achieving a given minimum power density on a target in a laser weapon scenario, and McMillan and Kohlberg [14], in unpublished work, considered the probability of achieving a minimum power on a radar receiver for fluctuating targets in atmospheric scintillation. Related work was done by Farina, Russo, and Studer [15], who studied radar detection in lognormal clutter, and by Morgan, Moyer, and Wilson [16], who developed a method for determining the optimal radar threshold in Weibull clutter and Gaussian noise. We consider the theory used to develop the probabilistic SCNR in two parts: Part 1 develops the signal (numerator) portion of this ratio, and Part 2 derives the clutter and noise portion (denominator).…”

Section: Theory: Determination Of the Signal Levelmentioning

confidence: 99%

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Atmospheric turbulence effects on radar systems

McMillan¹

2010

Proceedings of the IEEE 2010 National Aerospace &Amp; Electronics Conference

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Atmospheric turbulence has been shown to have measurable effects on several aspects of radar performance. In this paper we discuss the perturbation of the angle-ofarrival (AOA) of radar beams caused by the atmosphere, the effects of lognormal-and Weibull-distributed clutter on detection performance, and the detection probability of ultrawideband pulses propagated through the atmosphere in the presence of turbulence and Gaussian noise. We find that AOA effects are on the order of a few microradians, which is a negligible level for most applications, but that clutter and noise, when combined with turbulent fluctuations, give some surprising results when the ratio of signal to clutter and noise is calculated. The detection of ultrawideband pulses is analogous to the "needle in a haystack" problem. In this paper, we present theories describing each of these phenomena, together with calculated results. For AOA, we have made measurements for one-way propagation that agree well with this theory, but the other phenomena have yet to be measured.

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Section: Theory: Determination Of the Signal Levelmentioning

confidence: 99%

“…In the second integral, let (15) then n and . At W = W R , , and at Making these substitutions gives (16) The parameter W* is given by where is the average value of W [24]. Now let , where K is the fraction of the power W R required for some level of nominal performance.…”

Section: Theory: Determination Of the Signal Levelmentioning

confidence: 99%

Atmospheric turbulence effects on radar systems

McMillan¹

2010

Proceedings of the IEEE 2010 National Aerospace &Amp; Electronics Conference

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“…A widely used target detector type is the constant false alarm rate (CFAR) target detector [1][2][3][4][5][6][7] . CFAR detectors attempt to take advantage of the fact that the radar cross-section of a target is higher than the surrounding clutter.…”

Section: Introductionmentioning

confidence: 99%

Target detection based on multiresolution fractal analysis

Charalampidis

Stein

2007

SPIE Proceedings

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SAR imaging has been extensively used in several applications including automatic target detection and recognition. In this paper, a wavelet/fractal (WF)-based target detection technique is presented. The technique computes a fractal-based feature on an edge image, as opposed to existing fractal methods that compute the fractal dimension on the original image. The edge image is produced through the use of wavelets. The technique is evaluated for target detection in SAR images, and compared with a previous fractal-based approach, namely the extended fractal (EF) model. Experimental results illustrate that WF provides lower false alarm rates for the same probability of detection compared to EF. Furthermore, it is shown that WF provides higher spatial resolution capabilities for the detection of closely located targets.

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