scholarly journals Performance of Narrowband Signal Detection under Correlated Rayleigh Fading Based on Synthetic Array

2009 ◽  
Vol 2009 ◽  
pp. 1-13 ◽  
Author(s):  
Ali Broumandan ◽  
John Nielsen ◽  
Gérard Lachapelle
Keyword(s):  
Antenna Array ◽  
Rayleigh Fading ◽  
Signal To Noise Ratio ◽  
Probability Of Detection ◽  
Design Parameters ◽  
Channel Correlation ◽  
Probability Of False Alarm ◽  
Narrowband Signal ◽  
Processing Gain ◽  
Cdma 2000

The performance of a single moving antenna receiver in detecting a narrowband signal under correlated Rayleigh fading is considered. The spatial motion of the antenna during signal capture provides a realization of a synthetic antenna array. As shown, there is a net processing gain obtained by using a synthetic antenna array compared to the equivalent static antenna in Rayleigh fading environments subject to constant processing time. The performance analysis is based on average Signal-to-Noise Ratio (SNR) metrics for design parameters of probability of detection(Pd)and probability of false alarm(Pfa). An optimum detector based on Estimator-Correlator (EC) is developed, and its performance is compared with that of suboptimal Equal-Gain (EG) combiner in different channel correlation scenarios. It is shown that in moderate channel correlation scenarios the detection performance of EC and EG is identical. The sensitivity of the proposed method to knowledge of motion parameters is also investigated. An extensive set of measurements based on CDMA-2000 pilot signals using the static antenna and synthetic array are used to experimentally verify these theoretical findings.

Study on Threshold Detection of Micro-Seismic Signal Based on Constraint Judgment

2011 ◽  
Vol 255-260 ◽  
pp. 2898-2903
Author(s):  
Chang Peng Ji ◽  
Mo Gao ◽  
Jie Yang
Keyword(s):  
Signal To Noise Ratio ◽  
Seismic Signal ◽  
Probability Of Detection ◽  
Identification Accuracy ◽  
Signal To Noise ◽  
Threshold Detection ◽  
Probability Of False Alarm ◽  
Improvement Effect ◽  
The Mathematical Model ◽  
Double Threshold

Double threshold detection based on constraint judgment is proposed for micro-seismic signal detection. The improvement effect on Probability of False Alarm and influence on Probability of Detection are quantitatively analyzed with constraint judgment. The mathematical models of total PFA and PD of double threshold detection based on constraint judgment are built, and the validity of the mathematical model is verified by simulation tests and experiments. The results show that the signal-to-noise ratio under scheduled PFA and PD Call be decreased by introducing constraint judgment to double threshold detection, and improve the identification accuracy of micro-seismic signal.

scholarly journals Parameter Estimation and Target Detection of Phased-MIMO Radar Using Capon Estimator

2020 ◽  
Vol 20 (2) ◽  
pp. 60
Author(s):  
Syahfrizal Tahcfulloh ◽  
Muttaqin Hardiwansyah
Keyword(s):  
Parameter Estimation ◽  
False Alarm ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Detection Performance ◽  
Probability Of Detection ◽  
Detection Accuracy ◽  
Adaptive Estimator ◽  
Probability Of False Alarm

Phased-Multiple Input Multiple Output (PMIMO) radar is multi-antenna radar that combines the main advantages of the phased array (PA) and the MIMO radars. The advantage of the PA radar is that it has a high directional coherent gain making it suitable for detecting distant and small radar cross-section (RCS) targets. Meanwhile, the main advantage of the MIMO radar is its high waveform diversity gain which makes it suitable for detecting multiple targets. The combination of these advantages is manifested by the use of overlapping subarrays in the transmit (Tx) array to improve the performance of parameters such as angle resolution and detection accuracy at amplitude and phase proportional to the maximum number of detectable targets. This paper derives a parameter estimation formula with Capon's adaptive estimator and evaluates it for the performance of these parameters. Likewise, derivation for expressions of detection performance such as the probability of false alarm and the probability of detection is also given. The effectiveness and validation of its performance are compared to conventional estimator for other types of radars in terms of the effect of the number of target angles, the RCS of targets, and variations in the number of subarrays at Tx of this radar. Meanwhile, the detection performance is evaluated based on the effect of Signal to Noise Ratio (SNR) and the number of subarrays at Tx. The evaluation results of the estimator show that it is superior to the conventional estimator for estimating the parameters of this radar as well as the detection performance. Having no sidelobe makes this estimator strong against the influence of interference and jamming so that it is suitable and attractive for the design of radar systems. Root mean square error (RMSE) on magnitude detection from LS and Capon estimators were 0.033 and 0.062, respectively. Meanwhile, the detection performance for this radar has the probability of false alarm above 10-4 and the probability of detection of more than 99%.

scholarly journals WEAK SIGNAL DETECTION BASED ON MULTIPLE AUTO-CORRELATION TECHNIQUES

2021 ◽  
Vol 25 (Special) ◽  
pp. 1-56-1-62
Author(s):  
Sarah S. Mohammed ◽  
◽  
Maher K. Mahmood ◽  
Keyword(s):  
Signal To Noise Ratio ◽  
Probability Of Detection ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Multiple Correlation ◽  
Signal To Noise ◽  
Probability Of False Alarm ◽  
Auto Correlation ◽  
Simulation Results ◽  
Correlation Techniques

This study presents the performance of the auto-correlation methods for detecting weak signals, where the signal level is much less than the noise level. Double and triple auto-correlation techniques are used to improve the detection performance compared with the single autocorrelation. Simulation results obtained by MATLAB programs show that the multiple correlation techniques outperform the single correlation in terms of probability of detection and probability of false alarm versus signal to noise ratio SNR.

scholarly journals Improvement of the Target Sensitivity in DECIGO by Optimizing Its Parameters for Quantum Noise Including the Effect of Diffraction Loss

Galaxies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 14
Author(s):  
Tomohiro Ishikawa ◽  
Shoki Iwaguchi ◽  
Yuta Michimura ◽  
Masaki Ando ◽  
Rika Yamada ◽  
...  
Keyword(s):  
Gravitational Wave ◽  
Quantum Noise ◽  
Signal To Noise Ratio ◽  
Outer Space ◽  
Optical Diffraction ◽  
Design Parameters ◽  
Diffraction Loss ◽  
Noise Sources ◽  
Good Target ◽  
Spectrum Density

The DECi-hertz Interferometer Gravitational-wave Observatory (DECIGO) is the future Japanese, outer space gravitational wave detector. We previously set the default design parameters to provide a good target sensitivity to detect the primordial gravitational waves (GWs). However, the updated upper limit of the primordial GWs by the Planck observations motivated us toward further optimization of the target sensitivity. Previously, we had not considered optical diffraction loss due to the very long cavity length. In this paper, we optimize various DECIGO parameters by maximizing the signal-to-noise ratio (SNR) of the primordial GWs to quantum noise, including the effects of diffraction loss. We evaluated the power spectrum density for one cluster in DECIGO utilizing the quantum noise of one differential Fabry–Perot interferometer. Then we calculated the SNR by correlating two clusters in the same position. We performed the optimization for two cases: the constant mirror-thickness case and the constant mirror-mass case. As a result, we obtained the SNR dependence on the mirror radius, which also determines various DECIGO parameters. This result is the first step toward optimizing the DECIGO design by considering the practical constraints on the mirror dimensions and implementing other noise sources.

scholarly journals Optimization of spectrum sensing in cognitive radio using genetic algorithm

2012 ◽  
Vol 25 (3) ◽  
pp. 235-243 ◽  
Author(s):  
Rashmi Deka ◽  
Soma Chakraborty ◽  
Sekhar Roy
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Rapid Development ◽  
Probability Of Detection ◽  
Radio System ◽  
Probability Of False Alarm ◽  
Space Allocation ◽  
Wireless Environment ◽  
Better Than

Spectrum availability is becoming scarce due to the rise of number of users and rapid development in wireless environment. Cognitive radio (CR) is an intelligent radio system which uses its in-built technology to use the vacant spectrum holes for the use of another service provider. In this paper, genetic algorithm (GA) is used for the best possible space allocation to cognitive radio in the spectrum available. For spectrum reuse, two criteria have to be fulfilled - 1) probability of detection has to be maximized, and 2) probability of false alarm should be minimized. It is found that with the help of genetic algorithm the optimized result is better than without using genetic algorithm. It is necessary that the secondary user should vacate the spectrum in use when licensed users are demanding and detecting the primary users accurately by the cognitive radio. Here, bit error rate (BER) is minimized for better spectrum sensing purpose using GA.

scholarly journals MIMO Self-Encoded Spread Spectrum with Iterative Detection over Rayleigh Fading Channels

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Shichuan Ma ◽  
Lim Nguyen ◽  
Won Mee Jang ◽  
Yaoqing (Lamar) Yang
Keyword(s):  
Fading Channels ◽  
Spread Spectrum ◽  
Rayleigh Fading ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Spatial Diversity ◽  
Iterative Detection ◽  
Channel Fading ◽  
Input Multiple Output

Self-encoded spread spectrum (SESS) is a novel communication technique that derives its spreading code from the randomness of the source stream rather than using conventional pseudorandom noise (PN) code. In this paper, we propose to incorporate SESS in multiple-input multiple-output (MIMO) systems as a means to combat against fading effects in wireless channels. Orthogonal space-time block-coded MIMO technique is employed to achieve spatial diversity, and the inherent temporal diversity in SESS modulation is exploited with iterative detection. Simulation results demonstrate that MIMO-SESS can effectively mitigate the channel fading effect such that the system can achieve a bit error rate of with very low signal-to-noise ratio, from 3.3 dB for a antenna configuration to just less than 0 dB for a configuration under Rayleigh fading. The performance improvement for the case is as much as 6.7 dB when compared to an MIMO PN-coded spread spectrum system.

scholarly journals IMAGE RESTORATION METHOD, INVARIANT TO SIGNAL CORRELATION IN THE INFORMATION SYSTEM WITH ADAPTIVE ANTENNA ARRAY

2020 ◽  
pp. 64-76
Author(s):  
V.V. Skachkov ◽  
Keyword(s):  
Information System ◽  
Image Restoration ◽  
Antenna Array ◽  
Correlation Matrix ◽  
Signal To Noise Ratio ◽  
Weight Vector ◽  
Adaptive Antenna ◽  
Adaptive Antenna Array ◽  
Optimal Weight ◽  
Optimal Weight Vector

The problem of image signal processing in the information system with adaptive antenna array based on the inversion of sample estimates of correlation matrix of observations is considered. The example of the maximum signal-to-noise ratio criterion shows the problem, inherent in classical methods of finding the optimal weight vector under a priori uncertainty conditions when detecting correlated image signals. It has been concluded that the dependence of these methods on the inverse of estimation of the correlation matrix of observations leads to the impossibility of separating correlated image signals. As a consequence, the use of classical methods of finding the optimal weight vector in the information system with adaptive antenna array is effective only in the case of image restoration from a single signal source, with the signal received on the set of independent jamming background. A novel method, invariant to the correlation of image signals, has been developed for finding the optimal weight vector without the usage of correlation matrix of observations. An image restoration algorithm invariant to correlation of image signals in the information system with adaptive antenna array is proposed. Statistical models have been constructed for the classical method based on the criterion of maximum signal-to-noise ratio and invariant to correlation method of image restoration in following cases: a single source against the jamming background of two independent sources; two independent sources against the jamming background. Simulation results in the information system with adaptive antenna array are presented, showing to visually assess efficiency of proposed methods of image signal restoration using optimal weight vector. Detailed analysis of the results obtained is carried out.

scholarly journals A Novel Technique for Image Steganalysis Based on Separable Convolution and Adversarial Mechanism

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2742
Author(s):  
Yuwei Ge ◽  
Tao Zhang ◽  
Haihua Liang ◽  
Qingfeng Jiang ◽  
Dan Wang
Keyword(s):  
Signal To Noise Ratio ◽  
Detection Performance ◽  
Hidden Information ◽  
Adaptive Steganography ◽  
Image Steganalysis ◽  
Channel Correlation ◽  
Cyberspace Security ◽  
And Training ◽  
Training Efficiency ◽  
Good Detection

Image steganalysis is a technique for detecting the presence of hidden information in images, which has profound significance for maintaining cyberspace security. In recent years, various deep steganalysis networks have been proposed in academia, and have achieved good detection performance. Although convolutional neural networks (CNNs) can effectively extract the features describing the image content, the difficulty lies in extracting the subtle features that describe the existence of hidden information. Considering this concern, this paper introduces separable convolution and adversarial mechanism, and proposes a new network structure that effectively solves the problem. The separable convolution maximizes the residual information by utilizing its channel correlation. The adversarial mechanism makes the generator extract more content features to mislead the discriminator, thus separating more steganographic features. We conducted experiments on BOSSBase1.01 and BOWS2 to detect various adaptive steganography algorithms. The experimental results demonstrate that our method extracts the steganographic features effectively. The separable convolution increases the signal-to-noise ratio, maximizes the channel correlation of residuals, and improves efficiency. The adversarial mechanism can separate more steganographic features, effectively improving the performance. Compared with the traditional steganalysis methods based on deep learning, our method shows obvious improvements in both detection performance and training efficiency.

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