• Title/Summary/Keyword: probability of detection

Search Result 1,127, Processing Time 0.029 seconds

An Analysis on the Identification Rate of Detection System Using Non-Homogeneous Discrete Absorbing Markov Chains (비 동질성 이산시간 흡수마코프체인을 활용한 탐지체계의 식별률 분석에 관한 연구)

  • Kim, Seong-Woo;Yoon, Bong-Kyoo
    • Journal of the Korean Operations Research and Management Science Society
    • /
    • v.40 no.2
    • /
    • pp.31-42
    • /
    • 2015
  • The purpose of airborne radars is to detect and identify approaching targets as early as possible. If the targets are identified as enemies, detection systems must provide defense systems with information of the targets to counter. Though many previous studies based on the detection theory of the target have shown various ways to derive detection probability of each radar, optimal arrangement of radars for effective detection, and determination of the search pattern, they did not reflect the fact that most military radar sites run multiple radars in order to increase the accuracy of identifications by radars. In this paper, we propose a model to analyze the probability of identification generated by the multiple radars using non-homogeneous absorbing markov chains. Our results are expected to help the military commanders counter the enemy targets effectively by using radars in a way to maximize the identification rate of targets.

Watermark Detection Algorithm Using Statistical Decision Theory (통계적 판단 이론을 이용한 워터마크 검출 알고리즘)

  • 권성근;김병주;이석환;권기구;권기용;이건일
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.40 no.1
    • /
    • pp.39-49
    • /
    • 2003
  • Watermark detection has a crucial role in copyright protection of and authentication for multimedia and has classically been tackled by means of correlation-based algorithms. Nevertheless, when watermark embedding does not obey an additive rule, correlation-based detection is not the optimum choice. So a new detection algorithm is proposed which is optimum for non-additive watermark embedding. By relying on statistical decision theory, the proposed method is derived according to the Bayes decision theory, Neyman-Pearson criterion, and distribution of wavelet coefficients, thus permitting to minimize the missed detection probability subject to a given false detection probability. The superiority of the proposed method has been tested from a robustness perspective. The results confirm the superiority of the proposed technique over classical correlation- based method.

False Alarm Probability of the Spectrum Sensing Scheme Using the Maximum of Power Spectrum (전력 스펙트럼의 최대값을 사용한 스펙트럼 감지 방식의 오경보 확률)

  • Lim, Chang Heon
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.51 no.1
    • /
    • pp.37-41
    • /
    • 2014
  • Recently, a lot of research efforts has been directed toward spectrum sensing techniques exploiting the some characteristics of power spectrum. Among them, a sensing technique employing the maximum of power spectrum as a test statistic has appeared in the literature and its false alarm probability was also derived under the assumption that the test statistic follows the Gaussian distribution. This paper provides an exact form of the false alarm probability without using the assumption and compares it with the previous work.

A Technique for the Quantitative Analysis of the Noise Jamming Effect (잡음재밍 효과에 대한 정량적 분석 기법)

  • Kim, Sung-Jin;Kang, Jong-Jin
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.8 no.4 s.23
    • /
    • pp.91-101
    • /
    • 2005
  • In this paper, a technique for the quantitative analysis of the noise jamming effect is proposed. This technique based upon the mathematical modeling for noise jammers and the probability theory for random processes analyses the jamming effect by means of the modeling of the relationship among jammer, radar variables and radar detection probability under noise jamming environment. Computer simulation results show that the proposed technique not only makes the quantitative analysis of the jamming effect possible, but also provides the basis for quantitative analysis of the electronic warfare environment.

Excision GO-CFAR Detectors (Excision GO-CFAR 검출기)

  • 한용인;김태정
    • Journal of the Korean Institute of Telematics and Electronics B
    • /
    • v.29B no.1
    • /
    • pp.50-57
    • /
    • 1992
  • This paper proposes and analyzes a new CFAR(Constant False Alarm Rate) detector called the EXGO(Excision Greatest Of)-CFAR. This is the combination of the EXCA(Excision Cell Averaging)-CFAR that shows a good performance under the influence of interferences and the GO(Greatest Of)-CFAR that fights well with clutter edges. For the performance analysis, the formulas for the detection probability and the false alarm probability are derived and computed, and the results are compared with other existing CFAR detectors. Our analysis shows that the proposed EXGO-CFAR considerably improves the false-alarm-rate performance of the EXCA-CFAR at clutter edges while maintaining the high detection probability performance of the EXCA-CFAR in the homogeneous and/or interference noise environment.

  • PDF

Spliced Image Detection Using Characteristic Function Moments of Co-occurrence Matrix (동시 발생 행렬의 특성함수 모멘트를 이용한 접합 영상 검출)

  • Park, Tae-Hee;Moon, Yong-Ho;Eom, Il-Kyu
    • IEMEK Journal of Embedded Systems and Applications
    • /
    • v.10 no.5
    • /
    • pp.265-272
    • /
    • 2015
  • This paper presents an improved feature extraction method to achieve a good performance in the detection of splicing forged images. Strong edges caused by the image splicing destroy the statistical dependencies between parent and child subbands in the wavelet domain. We analyze the co-occurrence probability matrix of parent and child subbands in the wavelet domain, and calculate the statistical moments from two-dimensional characteristic function of the co-occurrence matrix. The extracted features are used as the input of SVM classifier. Experimental results show that the proposed method obtains a good performance with a small number of features compared to the existing methods.

Multimedia Watermark Detection Algorithm Based on Bayes Decision Theory (Bayes 판단 이론 기반 멀티미디어 워터마크 검출 알고리즘)

  • 권성근;이석환;김병주;권기구;하인성;권기룡;이건일
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.27 no.7A
    • /
    • pp.695-704
    • /
    • 2002
  • Watermark detection plays a crucial role in multimedia copyright protection and has traditionally been tackled using correlation-based algorithms. However, correlation-based detection is not actually the best choice, as it does not utilize the distributional characteristics of the image being marked. Accordingly, an efficient watermark detection scheme for DWT coefficients is proposed as optimal for non-additive schemes. Based on the statistical decision theory, the proposed method is derived according to Bayes decision theory, the Neyman-Pearson criterion, and the distribution of the DWT coefficients, thereby minimizing the missed detection probability subject to a given false alarm probability. The proposed method was tested in the context of robustness, and the results confirmed the superiority of the proposed technique over conventional correlation-based detection method.

Double-Talk Detection Based on Soft Decision for Acoustic Echo Suppression (음향학적 반향 제거를 위한 Soft Decision 기반의 동시통화 검출)

  • Park, Yun-Sik;Chang, Joon-Hyuk
    • The Journal of the Acoustical Society of Korea
    • /
    • v.28 no.3
    • /
    • pp.285-289
    • /
    • 2009
  • In this paper, we propose a novel double-talk detection (DTD) technique based on soft decision in the frequency domain. In the proposed method, global near-end speech presence probability (GNSPP) considering the statistical model assumption and voice activity detection (VAD) decision of the near-end and far-end signal are applied to the DTD algorithm in the frequency domain instead of the traditional hard decision scheme using cross-correlation coefficients. The performance of the proposed algorithm is evaluated by the objective test under various environments, and yields better results compared with the conventional scheme.

Dual Detection-Guided Newborn Target Intensity Based on Probability Hypothesis Density for Multiple Target Tracking

  • Gao, Li;Ma, Yongjie
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.10 no.10
    • /
    • pp.5095-5111
    • /
    • 2016
  • The Probability Hypothesis Density (PHD) filter is a suboptimal approximation and tractable alternative to the multi-target Bayesian filter based on random finite sets. However, the PHD filter fails to track newborn targets when the target birth intensity is unknown prior to tracking. In this paper, a dual detection-guided newborn target intensity PHD algorithm is developed to solve the problem, where two schemes, namely, a newborn target intensity estimation scheme and improved measurement-driven scheme, are proposed. First, the newborn target intensity estimation scheme, consisting of the Dirichlet distribution with the negative exponent parameter and target velocity feature, is used to recursively estimate the target birth intensity. Then, an improved measurement-driven scheme is introduced to reduce the errors of the estimated number of targets and computational load. Simulation results demonstrate that the proposed algorithm can achieve good performance in terms of target states, target number and computational load when the newborn target intensity is not predefined in multi-target tracking systems.

Highly Reliable Watermark Detection Algorithm using Statistical Decision Method in Wavelet Domain (웨이블릿 영역에서 통계적 판정법을 이용한 고신뢰 워터마크 검출 알고리즘)

  • 권성근;김병주;이석환;권기구;김영춘;권기룡;이건일
    • Journal of Korea Multimedia Society
    • /
    • v.6 no.1
    • /
    • pp.67-77
    • /
    • 2003
  • Watermark detection has a crucial role in copyright protection and authentication for multimedia Because be the correlation -based algorithm which has widely been used in the watermark detection doesn't utilize the distributional characteristics of cover image to be marked, its performance is not optimum. So a new detection algorithm is proposed which is optimum for multiplicative watermark embedding. By relying on statistical decision method, the proposed method is derived according to the Bayes decision theory. Neyman Pearson criterion, and distribution of wavelet coefficients, thus Permitting to minimize the missed detection probability subject to a given false detection probability The superiority of the proposed method has been tested from a robustness perspective. The results confirm the superiority of the proposed technique over classical correlation -based method.

  • PDF