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COMPLEXITY REDUCTION OF CYCLOSTATIONARY SENSING TECHNIQUE USING IMPROVED HYBRID SENSING METHOD
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In cognitive radio system, the spectrum sensing has a major challenge in needing a sensing method, which has a high detection capability with reduced complexity. In this paper, a low-cost hybrid spectrum sensing method with an optimized detection performance based on energy and cyclostationary detectors is proposed. The method is designed such that at high signal-to-noise ratio SNR values, energy detector is used alone to perform the detection. At low SNR values, cyclostationary detector with reduced complexity may be employed to support the accurate detection. The complexity reduction is done in two ways: through reducing the number of sensing samples used in the autocorrelation process in the time domain and through using the Sliding Discrete Fourier Transform (SDFT) instead of the Fast Fourier Transform (FFT). To evaluate the performance, two versions of the proposed hybrid method are implemented, one with the FFT and the other with the SDFT. The proposed method is simulated for cooperative and non-cooperative scenarios and investigated under a multipath fading channel. Obtained results are evaluated by comparing them with other methods including: cyclostationary feature detection (CFD), energy detector and traditional hybrid. The simulation results show that the proposed method with the FFT and the SDFT successfully reduced the complexity by 20% and 40% respectively, when 60 sensing samples are used with an acceptable degradation in the detection performance. For instance, when Eb/N0 is 0 dB , the probability of the detection of Pd is decreased by 20 % and 10% by the proposed method with the FFT and the SDFT respectively, as compared with the hybrid method existing in the literature.

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Publication Date
Wed May 01 2019
Journal Name
Journal Of Engineering
Reduced Complexity SLM Method for PAPR Reduction
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In this paper, the computational complexity will be reduced using a revised version of the selected mapping (SLM) algorithm. Where a partial SLM is achieved to reduce the mathematical operations around 50%. Although the peak to average power ratio (PAPR) reduction gain has been slightly degraded, the dramatic reduction in the computational complexity is an outshining achievement. Matlab simulation is used to evaluate the results, where the PAPR result shows the capability of the proposed method.  

 

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Improved Automatic Registration Adjustment of Multi-source Remote Sensing Datasets
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Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration p

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Improved Automatic Registration Adjustment of Multi-source Remote Sensing Datasets
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Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration process by de

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Spatiotemporal Drought Monitoring Using Remote Sensing Technique in Babel-Iraq
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       Drought is one of the most natural hazards that may harm human life and property under different weather and environmental conditions. This study used remote sensing data to monitor agricultural and meteorological drought in Babel Governorate. Drought maps were drawn using Landsat 8 images based on Normalized Difference Vegetation Index (NDVI) for 2015, 2018, and 2021. The meteorological drought was assessed using a standardized precipitation index (SPI 12) for the same years. The results showed that the SPI-12 indicated near-normal drought types in 2015 and 2018, whereas SPI values showed a lower value in 2021. Two drought categories were identified which were moderate drought and severe drought. The NDVI results showed tha

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Publication Date
Mon Jul 01 2013
Journal Name
Http://www.i-csrs.org/volumes/gisars/vol.3/vol.3.1.1.july.12.pdf
Remote sensing technique to monitoring the risk of soil degradation using NDVI
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In order to take measures in controlling soil erosion it is required to estimate soil loss over area of interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss Equation (USLE). The accuracy of these models depends on parameters that are used in equations. One of the most important parameters in equations used in both of models is (C) factor that represents effects of vegetation and other land covers. Estimating land cover by interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator that shows vegetation cover. The aim of this study is estimate (C) factor values for Part of Baghdad city using NDVI derived from satellite Image of Landsat-7

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Publication Date
Tue Oct 02 2018
Journal Name
Iraqi Journal Of Physics
Informative accuracy investigation and updating map using remote sensing technique and GIS
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In this work, using GPS which has best accuracy that can be established set of GCPs, also two satellite images can be used, first with high resolution QuickBird, and second has low resolution Landsat image and topographic maps with 1:100,000 and 1:250,000 scales. The implementing of these factors (GPS, two satellite images, different scales for topographic maps, and set of GCPs) can be applying. In this study, must be divided this work into two parts geometric accuracy and informative accuracy investigation. The first part is showing geometric correction for two satellite images and maps.
The second part of the results is to demonstrate the features (how the features appearance) of topographic map or pictorial map (image map), Where i

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Publication Date
Fri Dec 01 2023
Journal Name
Ieee Antennas And Wireless Propagation Letters
Stabilized and Fast Method for Compressive-Sensing-Based Method of Moments
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Publication Date
Tue Nov 02 2021
Journal Name
Iraqi Journal Of Science
Mapping Land Cover/Land Use for Change Derivation Using Remote Sensing and GIS Technique
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    Deriving land cover information from satellite data is one of the most common applications employed to monitor, evaluate, and manage the environment. This study aims to detect the land cover/land use changes and calculate the areas of different land cover types in Baghdad, Iraq, for the period from 2015 to 2020, using Landsat 8 images. The supervised Maximum Likelihood Classification (MLC) method was applied to classify the images. Four land cover types were obtained, namely urban, vegetation, water, and barren soil.  Changes in the four land cover classes during the study period were observed. The extent of the urban, vegetation, and water areas was increased by about 7.5%, 9.5%, and 1.5%, respectively, whereas t

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Feature Extraction Using Remote Sensing Images
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Feature extraction provide a quick process for extracting object from remote sensing data (images) saving time to urban planner or GIS user from digitizing hundreds of time by hand. In the present work manual, rule based, and classification methods have been applied. And using an object- based approach to classify imagery. From the result, we obtained that each method is suitable for extraction depending on the properties of the object, for example, manual method is convenient for object, which is clear, and have sufficient area, also choosing scale and merge level have significant effect on the classification process and the accuracy of object extraction. Also from the results the rule-based method is more suitable method for extracting

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Land Surface Temperature investigation of Babylon city between (2002-2022) using Remote Sensing and GIS Technique
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      Land surface temperature (LST) is crucial for determining the region's environmental quality because a significant temperature rise causes disasters, which cause environmental imbalance, reducing biodiversity and hastening desertification. In this study, remote sensing and geographic information systems were used to estimate the change in the LST of Babylon, Iraq, using two satellite images taken 20 years apart (2002, 2022). The temperature was extracted using a specific mathematical model in ArcMap10.8 software. The findings demonstrated a significant variation in temperatures and the concentration in various regions of Babylon between 2002 and 2022 and the relationship between LST and Normalized difference

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