On the false alarm probability for an overlapped FFT processor

Maranda, B.H.

doi:10.1109/7.543866

Cited by 32 publications

(10 citation statements)

References 5 publications

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“…Similar to the method discussed in reference [5], the probability of false alarm for the CA-CFAR detector is derived as T T T T 1 2 2 2 1 2 , , , , ,…”

Section: False Alarm Probability In Practical Conditionsmentioning

confidence: 99%

False Alarm Probability of the Digital Channelized Receiver Based CA-CFAR Detector

Jia

Cheng

2011

Web Information Systems and Mining

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Abstract. This paper studies the effect of the correlated noise responses on the false alarm probability of the digital channelized receiver based CA-CFAR detector. The statistic characteristics of the digital channelized receiver are firstly discussed in additive white Gaussian noise. Two different expressions are then derived for the false alarm probability of the CA-CFAR detector when the noise responses are correlative and assumed independent, respectively. Finally, the above expressions are compared by simulation. The simulation experiments show that the detection performance of the CA-CFAR detector in assumed conditions is very similar to the one in practical conditions. Hence, the assumption that the noise responses are statistically independent is reasonable in practical engineering.

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“…Similar to the method discussed in reference [5], the probability of false alarm for the CA-CFAR detector is derived as T T T T 1 2 2 2 1 2 , , , , ,…”

Section: False Alarm Probability In Practical Conditionsmentioning

confidence: 99%

False Alarm Probability of the Digital Channelized Receiver Based CA-CFAR Detector

Jia

Cheng

2011

Web Information Systems and Mining

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“…Reference [5] has obtained the false alarm probability formula on real input signal. We can extend the condition to complex signal, and obtain the false alarm probability on frame-overlapping process according to [5] as NT <T s req (12) When we determine the FFT length N in practice, the presented five criteria should be rational applied based on system demands. One can use the most crucial criterion to figure out N, and then check it with other criteria.…”

Section: Criterion 5 (Synchronization Criterion)mentioning

confidence: 99%

“…As data is overlapped between the two neighbored frames, it will result in correlation between the FFT results of nearby frames, thus it can apparently affect the performance of the incoherent integration. Reference [5] has analyzed the effects of overlap on incoherent integration and derived a false alarm probability formula in the case of overlap factor less than 0.5. Based on the previous its results, this paper would focuses on the rational design of overlap factor in PD radar spectrum analysis application.…”

Section: Introductionmentioning

confidence: 99%

Frame-overlapped Zoom-FFT Optimization in PD Radar Application

Fan

Sheng

Chen

et al. 2006

2006 CIE International Conference on Radar

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This paper addresses a frame-overlapped zoom-FFT method applied to Pulse Doppler (PD) radar echo spectrum analysis. The method can achieve high resolution of local spectrum, and improve the gain of coherent integration, so it can enhance the detection probability and the precision of parameter estimation for poor echo signal. Firstly this paper introduces the principal of frame-overlapped zoom-FFT. Then it addresses the parameter design criterions in high pulse repeat frequency (HPRF) PD radar application. Furthermore based on analyzing the effects on incoherent integration and target detection due to frame overlap, it illustrates the parameter design process by an example of PD radar spectrum analysis application and gives the comparison of overlap processing and no-overlap processing. Finally, a real-time spectrum analysis system implementation adopting the frame-overlapped zoom-FFT method is proposed.

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“…1 has long been used in applications such as civilian spectrum monitoring and military surveillance. Its precise mathematical definition is given in [1], [2], whose assumptions and definitions, including the additive white Gaussian channel noise model, are followed here in this paper. Let 0 ≤ γ ≤ 1/2 be the input data overlap ratio and let σ 2 be the variance of the additive white Gaussian channel noise.…”

Section: Introductionmentioning

confidence: 99%

Application of Imhof formula in the computation of the normalized detection threshold for the FFT summation detector

Wang¹,

Inkol²,

Patenaude

2011

2011 24th Canadian Conference on Electrical and Computer Engineering(CCECE)

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The FFT summation detector is a technique that has been widely used in civilian spectrum monitoring and military radio surveillance for detecting narrowband signals in noise. In practical implementations of the FFT summation detector, the detection threshold is set as the product of the channel noise power, which is often adaptively estimated from the FFT filter bank output, and the normalized detection threshold T n , which is usually computed by solving a nonlinear equation. The golden section search algorithm is an ideal procedure for solving the nonlinear equation as it does not involve function derivative evaluations which can be a major source of numerical difficulties. However, for overlapped input data blocks, even the golden section search algorithm often breaks down, especially for relatively large values of P fa . In this paper, an alternative technique based on the Imhof formula is investigated for the computation of T n . It is shown that, for many cases of practical interest, the Imhof formula can be used to compute T n reliably for overlapped input data blocks when the technique based on the numerical solution of an algebraic equation fails.Index Terms-FFT filter bank, spectrum analysis, detection and estimation, constant probability of false alarm, normalized detection threshold, Imhof formula, golden section search

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On the false alarm probability for an overlapped FFT processor

Cited by 32 publications

References 5 publications

False Alarm Probability of the Digital Channelized Receiver Based CA-CFAR Detector

False Alarm Probability of the Digital Channelized Receiver Based CA-CFAR Detector

Frame-overlapped Zoom-FFT Optimization in PD Radar Application

Application of Imhof formula in the computation of the normalized detection threshold for the FFT summation detector

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