scholarly journals LEO-Based Satellite Constellation for Moving Target Detection

2022 ◽  
Vol 14 (2) ◽  
pp. 403
Author(s):  
Chongdi Duan ◽  
Yu Li ◽  
Weiwei Wang ◽  
Jianguo Li
Keyword(s):  
Detection Method ◽  
Rapid Development ◽  
Contrast Ratio ◽  
Detection Threshold ◽  
Weighted Likelihood ◽  
Cfar Detection ◽  
Satellite Constellation ◽  
Satellite Platform ◽  
Leo Satellites ◽  
Fusion Detection

With the rapid development of cooperative detection technology, target fusion detection with regard of LEO satellites can be realized by means of their diverse observation configurations. However, the existing constant false alarm ratio (CFAR) detection research rarely involves the space-based target fusion detection theory. In this paper, a novel multi-source fusion detection method based on LEO satellites is presented. Firstly, the pre-compensation function is constructed by employing the range and Doppler history of the cell where the antenna beam center is pointed. As a result, not only is the Doppler band broadening problem caused by the high-speed movement of the satellite platform, but the Doppler frequency rate (DFR) offset issue resulted from different observation configurations are alleviated synchronously. Then, the theoretical upper and lower limits of DFR are designed to achieve the effective clutter suppression and the accurate target echo fusion. Finally, the CFAR detection threshold based on the exponential weighted likelihood ratio is derived, which effectively increases the contrast ratio between the target cell and other background cells, and thus to provide an effective multi-source fusion detection method for LEO-based satellite constellation. Simulation results verify the effectiveness of the proposed algorithm.

scholarly journals A novel design of algorithm and framework for decentralized CFAR signal detection without prior information

2018 ◽  
Vol 189 ◽  
pp. 04006
Author(s):  
Nan Wang ◽  
Yunshan Xu ◽  
Haibao Xia ◽  
Jundi Wang
Keyword(s):  
Signal Detection ◽  
Prior Information ◽  
Detection Method ◽  
Detection Algorithm ◽  
Constant False Alarm Rate ◽  
Test Statistic ◽  
Fusion Algorithm ◽  
Cfar Detection ◽  
Novel Design ◽  
Fusion Detection

In this paper, a fusion detection algorithm that focuses on decentralized CFAR (Constant False Alarm Rate) signal detection problem without prior information is proposed. In the algorithm, the threshold and test statistic of the detection fusion algorithm derive from the conventional CFAR detection method. At last a framework for decentralized CFAR signal detection is designed corresponding to the fusion algorithm. Simulation results illustrate that an almost optimal detection performance is obtained by the proposed algorithm.

scholarly journals Incoherent Integration Detection Method of Airborne Phased Array Radar in a Multipath Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yili Hu ◽  
Yongbo Zhao ◽  
Sheng Chen
Keyword(s):  
Phased Array ◽  
Detection Method ◽  
Detection Threshold ◽  
Constant False Alarm Rate ◽  
Detection Model ◽  
Cfar Detection ◽  
Phased Array Radar ◽  
Multipath Signal ◽  
Multipath Environment ◽  
Airborne Phased Array Radar

Airborne phased array radar (PAR) suffers from multipath problems when flying over a calm sea surface. The existence of a multipath phenomenon will cause the electromagnetic echo of the same target to be reflected back to the airborne PAR from two paths, namely, direct path (DP) and multipath. Compared with the ground-based radar, the target echo received by airborne PAR in the multipath environment has two important characteristics: one is that the DP signal and the multipath signal exist in different range bins, and the other is that the radar cross section (RCS) in the DP direction may be smaller than that in the multipath direction. Considering these two characteristics, this paper first proposes a target pairing algorithm for matching the DP range and multipath range of the same target in signal detection, and then, combined with the cell-averaging constant false alarm rate (CA-CFAR) detection model, an incoherent integration detection method for airborne PAR in the multipath environment is proposed. In the target pairing process, the geometric structure relationship of the airborne PAR model can be fully utilized. After a successful target pairing process, the energy of the multipath signal will be incoherently accumulated into the corresponding DP range bin, so as to improve the probability of DP range bin data passing the detection threshold. In essence, the proposed method makes full use of multipath energy to improve the detection capability of airborne PAR in the multipath environment. Finally, the detection probability of the proposed method is given, and the detection performance is analyzed.

scholarly journals Analysis of the Impact of Detection Threshold Adjustments and Noise Uncertainty on Energy Detection Performance in MIMO-OFDM Cognitive Radio Systems

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 631
Author(s):  
Josip Lorincz ◽  
Ivana Ramljak ◽  
Dinko Begušić
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Detection Method ◽  
Detection Threshold ◽  
Energy Detection ◽  
Primary User ◽  
Noise Uncertainty ◽  
Cognitive Radio Systems ◽  
Radio Systems ◽  
The Impact

Due to the capability of the effective usage of the radio frequency spectrum, a concept known as cognitive radio has undergone a broad exploitation in real implementations. Spectrum sensing as a core function of the cognitive radio enables secondary users to monitor the frequency band of primary users and its exploitation in periods of availability. In this work, the efficiency of spectrum sensing performed with the energy detection method realized through the square-law combining of the received signals at secondary users has been analyzed. Performance evaluation of the energy detection method was done for the wireless system in which signal transmission is based on Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing. Although such transmission brings different advantages to wireless communication systems, the impact of noise variations known as noise uncertainty and the inability of selecting an optimal signal level threshold for deciding upon the presence of the primary user signal can compromise the sensing precision of the energy detection method. Since the energy detection may be enhanced by dynamic detection threshold adjustments, this manuscript analyses the influence of detection threshold adjustments and noise uncertainty on the performance of the energy detection spectrum sensing method in single-cell cognitive radio systems. For the evaluation of an energy detection method based on the square-law combining technique, the mathematical expressions of the main performance parameters used for the assessment of spectrum sensing efficiency have been derived. The developed expressions were further assessed by executing the algorithm that enabled the simulation of the energy detection method based on the square-law combining technique in Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing cognitive radio systems. The obtained simulation results provide insights into how different levels of detection threshold adjustments and noise uncertainty affect the probability of detection of primary user signals. It is shown that higher signal-to-noise-ratios, the transmitting powers of primary user, the number of primary user transmitting and the secondary user receiving antennas, the number of sampling points and the false alarm probabilities improve detection probability. The presented analyses establish the basis for understanding the energy detection operation through the possibility of exploiting the different combinations of operating parameters which can contribute to the improvement of spectrum sensing efficiency of the energy detection method.

scholarly journals Adjacent Infrared Multitarget Detection Using Robust Background Estimation

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Sungho Kim ◽  
Kyung-Tae Kim
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Target Detection ◽  
Detection Method ◽  
Detection Performance ◽  
Detection Methods ◽  
Constant False Alarm Rate ◽  
Cluttered Environments ◽  
Background Estimation ◽  
Cfar Detection

Small target detection is very important for infrared search and track (IRST) problems. Grouped targets are difficult to detect using the conventional constant false alarm rate (CFAR) detection method. In this study, a novel multitarget detection method was developed to identify adjacent or closely spaced small infrared targets. The neighboring targets decrease the signal-to-clutter ratio in hysteresis threshold-based constant false alarm rate (H-CFAR) detection, which leads to poor detection performance in cluttered environments. The proposed adjacent target rejection-based robust background estimation can reduce the effects of the neighboring targets and enhance the small multitarget detection performance in infrared images by increasing the signal-to-clutter ratio. The experimental results of the synthetic and real adjacent target sequences showed that the proposed method produces an upgraded detection rate with the same false alarm rate compared to the recent target detection methods (H-CFAR, Top-hat, and TDLMS).

A Simplified Detection Method for PN Sequence Acquisition and its Performance Analysis

2013 ◽  
Vol 680 ◽  
pp. 460-465
Author(s):  
Zhong Liang Deng ◽  
Xie Yuan ◽  
Yu Zhang
Keyword(s):  
Detection Method ◽  
Detection Threshold ◽  
Noise Power ◽  
Pn Sequence ◽  
Signal Systems ◽  
Ofdm Signal ◽  
Pseudo Noise ◽  
Ground Noise ◽  
Noise Sequence

Some OFDM signal systems use PN (Pseudo-noise) sequence in time domain to synchronize. During the acquisition progress, the ground noise power has to be calculated, and the determination of the detection threshold is important. This paper introduced a simplified detection method for PN sequence, and analyzed the threshold to optimize the performance.

A data fusion detection method for fish freshness based on computer vision and near-infrared spectroscopy

2016 ◽  
Vol 8 (14) ◽  
pp. 2929-2935 ◽  
Author(s):  
Xingyi Huang ◽  
Haixia Xu ◽  
Lei Wu ◽  
Huang Dai ◽  
Liya Yao ◽  
...  
Keyword(s):  
Computer Vision ◽  
Infrared Spectroscopy ◽  
Data Fusion ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Detection Method ◽  
Spectroscopic Techniques ◽  
Fusion Detection

This article proposes and describes a data fusion detection method based on computer vision and spectroscopic techniques for fish freshness classification.

Evaluation of Quality for Ink-Jet Printing Based on Capturing Measurement and Control Elements by CCD

2010 ◽  
Vol 174 ◽  
pp. 211-214 ◽  
Author(s):  
Zhen Liu ◽  
Jian Hong ◽  
Sheng Hui Li
Keyword(s):  
Detection Method ◽  
Rapid Development ◽  
Digital Printing ◽  
Ink Jet Printing ◽  
Quality Detection ◽  
Printing Quality ◽  
Ink Jet ◽  
Jet Printing ◽  
And Control ◽  
Measurement And Control

with the rapid development of digital printing, the method and standard of quality detection for digital printing become focus of research. The main work and innovations in this paper include: ①Computer image analysis method was applied to ink-jet printing quality detection for the first time; ②Compared with traditional printing quality test, ink dot, line, color patch and MTF (Modulation Transfer Function) were selected as measurement and control elements. And the test proofs for detecting printing quality were designed; ③The detection algorithm and the overall detection process were put forward in this paper. The result of the experiment demonstrates: the detection method based on capturing measurement and control elements by CCD can accurately accomplish the objective quality evaluation for ink-jet printing. Detection method of print was improved to extend the scope of detection by this research, which could be generalized as a standard method for the detection of ink-jet printing quality.

Structural damage detection via combining weighted strategy with trace Lasso

2018 ◽  
Vol 22 (3) ◽  
pp. 597-612 ◽  
Author(s):  
Chengbin Chen ◽  
Chudong Pan ◽  
Zepeng Chen ◽  
Ling Yu
Keyword(s):  
Damage Detection ◽  
Swarm Intelligence ◽  
Structural Damage ◽  
Optimization Problem ◽  
Detection Method ◽  
Rapid Development ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Structural Damage Detection ◽  
Selection Operator

With the rapid development of computation technologies, swarm intelligence–based algorithms become an innovative technique used for addressing structural damage detection issues, but traditional swarm intelligence–based structural damage detection methods often face with insufficient detection accuracy and lower robustness to noise. As an exploring attempt, a novel structural damage detection method is proposed to tackle the above deficiency via combining weighted strategy with trace least absolute shrinkage and selection operator (Lasso). First, an objective function is defined for the structural damage detection optimization problem by using structural modal parameters; a weighted strategy and the trace Lasso are also involved into the objection function. A novel antlion optimizer algorithm is then employed as a solution solver to the structural damage detection optimization problem. To assess the capability of the proposed structural damage detection method, two numerical simulations and a series of laboratory experiments are performed, and a comparative study on effects of different parameters, such as weighted coefficients, regularization parameters and damage patterns, on the proposed structural damage detection methods are also carried out. Illustrated results show that the proposed structural damage detection method via combining weighted strategy with trace Lasso is able to accurately locate structural damages and quantify damage severities of structures.

scholarly journals The Visibility of Multisensor Fusion Technology in Public Art Design

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yan Zhang ◽  
Qi Zhang
Keyword(s):  
Public Space ◽  
Public Art ◽  
Detection Method ◽  
Detection System ◽  
Rapid Development ◽  
Obstacle Detection ◽  
Multisensor Fusion ◽  
Fusion Technology ◽  
Art Design ◽  
In Transit

This exploration is aimed at improving the efficiency and safety of fully automatic line operation in public space. From the perspective of multisensor fusion technology, the definition, development status, and design principles of public art, as well as the related applications of multisensor fusion technology theory and image fusion theory, are introduced by consulting relevant literature. Then, the scheme of subway platform door gap antipinch detection system based on multisensor fusion and the obstacle detection method of tram in transit are proposed. Finally, through the method of questionnaire, the passengers’ cognition of public art in subway space and the concerned components of public art in subway space are analyzed. The results show that the subway space art content loved by passengers is mainly daily life, and the degree of love can reach 28%, followed by local customs, culture, and fashion trends, with a degree of love of 23%. Besides, the problem of obstacle detection of tram in transit is also studied, and a new obstacle detection method combining visual sensor transmission detection and lidar detection is proposed. This method can quickly and accurately identify unsafe factors. Therefore, the research on the visibility of multisensor fusion technology in public art design has great reference significance for the rapid development of transportation industry.

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