scispace - formally typeset
Search or ask a question

What are research gap in the utilization of xband marine radar in terms of wave detection? 


Best insight from top research papers

The research on utilizing X-band marine radar for wave detection reveals several gaps. Firstly, the detection of rainfall interference in radar images remains a challenge due to limited accuracy in statistical methods . Secondly, the need for improved methods to retrieve wave parameters from radar images, especially in non-homogeneous sea wave fields, suggests a gap in current techniques. Additionally, controlling the quality of radar images for accurate wave parameter retrieval requires more effective rainfall detection methods. Lastly, advancements in radar maritime target detection highlight the importance of sharing radar-measured data for tackling key technologies, indicating a gap in data availability and collaboration. These gaps emphasize the need for further research to enhance the effectiveness and reliability of X-band marine radar in wave detection applications.

Answers from top 5 papers

More filters
Papers (5)Insight
Not addressed in the paper.
Open accessJournal ArticleDOI
Yan Zheng, Zhen Shi, Zhizhong Lu, Wenfeng Ma 
22 Jan 2020-IEEE Access
11 Citations
Research gap in X-band marine radar lies in rainfall interference affecting wave parameter accuracy. Proposed method detects rainfall by analyzing sea clutter correlation, enhancing wave detection quality.
The research paper proposes a novel synchrosqueezed wavelet transform method to enhance wave parameter retrieval accuracy, addressing limitations in traditional methods for X-band marine radar wave detection.
Research gaps in X-band marine radar wave detection include limited accuracy of statistical methods, challenges in machine learning model selection, and the need for improved rainfall detection performance in marine environments.
Research gaps in X-band marine radar wave detection include limited accuracy due to rainfall noise interference, threshold selection challenges in rainfall detection, and the need for rainfall intensity level retrieval methods.

Related Questions

What is the research gap in microwave tumor imaging?5 answersThe research gap in microwave tumor imaging lies in the slow progress towards clinically mature systems due to challenges such as low resolution at higher frequencies and limited penetration at lower frequencies. While microwave imaging shows promise due to the high dielectric contrast between malignant tumors and normal breast tissue, the current discourse in the field lacks consensus and often overlooks core ideas, hindering advancements in the translation of research into clinical applications. Despite recent developments in radar detection, coaxial probes, and tomographic techniques for tumor detection using microwaves, there is a need to address issues like multipath signals confounding data and the complexity of dielectric property contrasts in breast tissue in vivo. Bridging these gaps could lead to more effective and widely accessible microwave imaging systems for tumor detection in breast cancer research.
What is the Research gap (Limitations) of this paper?4 answersThe research gap (limitations) of this paper include the need for filling certain gaps in corporate reporting, the low quality of business digitalization in Russia, the limited research on sustainable entrepreneurship, and the limitations and delimitations of the underlying theories, study design, and data collection in the paper.
What are the research gaps in Microwave electronics?5 answersResearch gaps in microwave electronics include limited understanding of electromagnetic interactions in small systems. Additionally, there is a lack of consideration for environmental simulation tests and their effects on electrical and mechanical properties, as well as high-frequency properties of printed structures. Furthermore, challenges persist in predicting and controlling the shape and dimension of the thermally ablated area in microwave thermal ablation (MTA) for clinical applications. Lastly, there is a need for further exploration of periodic dielectric structures exhibiting photonic band gaps and their potential applications as tunable filters.
What are the potential applications of photonic radar for underwater applications?3 answersPhotonic radar has potential applications in underwater environments. It can be used for the detection and identification of underwater threats in coastal areas, where conventional optical imaging systems have limitations. Photonic radar can enhance image contrast and resolution by discriminating against multiply scattered light. Additionally, it can be used for precise underwater distance measurements, making it suitable for applications such as autonomous underwater vehicles (AUV) and underwater construction. The use of photonic radar in underwater optical wireless communication (UOWC) is also being explored, as it offers higher data rates and lower latency compared to acoustic and RF counterparts. Furthermore, photonic radar can be used in combination with other sensors to measure the temperature of seawater, detect the depth of the sea, and monitor the state of the seabed.
What is the evidence of effectiveness of the WAVES study@?1 answersThe evidence of effectiveness of the WAVES study is supported by the research conducted by D’Angelo and Grimaldi. They applied technical analysis, specifically the Elliott waves theory, to forecast the exchange rate between the U.S. dollar and euro. Their results showed that the exchange rate could be accurately forecasted during the period from 2009-2015, and they also proposed a potential future pattern for the exchange rate starting in March 2017. This study confirmed the usefulness of Elliott’s model for predicting currency markets. Additionally, Fusco and Ringwoodfocused on wave energy converters and the need for short-term prediction of oncoming waves. They explored various forecasting techniques, including cyclical models and AR models, and found that AR models were able to effectively represent the cyclical behavior of real waves.
What are the research gaps that you want to fulfil?5 answersThere are several research gaps that need to be fulfilled based on the abstracts provided. These include: 1. Understanding the reasons for low coverage of HBV vaccination in certain regions of the world and the need for a prophylactic vaccine for HCV. 2. The lack of sound empirical analysis and evaluation of DDoS defense solutions, leading to network operators relying on basic defense techniques. 3. Gaps in knowledge regarding the etiology, prevalence, and trends of hypertension in children and adolescents, as well as the long-term impacts of hypertension and the safety and efficacy of antihypertensive therapy in youth. 4. The need for a broader characterization of African genomic diversity to better understand demographic history and improve global human health. 5. Limited research on the relationship between market mavenism and personality antecedents, as well as the consequences of mavenism such as brand loyalty and frugality.

See what other people are reading

When did electroretinogram begin?
5 answers
The electroretinogram (ERG) originated in the late 19th century when Dr. James Dewar recorded the first electrical potentials from the human eye in 1873. Subsequently, in 1865, Holmgren and Dewar independently observed light-induced electrical changes in the eye, leading to the development of the ERG as a diagnostic tool. Over the years, ERG has evolved, with researchers like Karpe in 1948 further refining methods for recording and analyzing retinal electrical activity in humans. The ERG has since become a crucial tool in ophthalmology, allowing for the assessment of retinal function and aiding in the diagnosis and prognosis of various retinal diseases.
What is 3d radiation imasing?
5 answers
Three-dimensional (3D) radiation imaging involves advanced techniques for visualizing radiation sources in three dimensions. Various methods have been proposed, such as utilizing scattered radiation information for emission location and dose distribution determination, rearranging radar echoes to achieve high-resolution 3D imaging, reconstructing radiation source distribution using multiple detector viewpoints and SLAM technology, and employing real-time gamma-ray mapping for radiological material detection and localization. These approaches enable precise mapping of radioactive sources in real-time, aiding in applications like disaster monitoring, environmental security, nuclear safety, and decommissioning activities. Additionally, the development of compact radiation imaging devices utilizing stereoscopic principles further enhances the accuracy and efficiency of 3D radiation imaging systems.
What is predictive quantitative method?
5 answers
A predictive quantitative method involves using scientific approaches to forecast trends based on historical and current data. Such methods can range from linear regression models for decision-making based on reliable data knowledgeto deep learning models for wireless network coverage indicators. These methods may also include predictive coding techniques to reduce transmission bandwidth and optimize rate distortion. By obtaining and analyzing various data types like network structure, wireless parameters, and service distribution, quantitative prediction methods enable accurate and timely forecasts, enhancing decision-making processes. Additionally, in trading markets, quantitative transaction prediction models update parameters for precise predictions, improving the speed and accuracy of transaction behavior forecasts.
How accurate is google earth mapping?
5 answers
Google Earth mapping accuracy varies based on the specific application and methodology used. Studies have shown high accuracy levels in mapping built-up areas when combining Synthetic Aperture Radar (SAR) data of Sentinel-1 and Multispectral Instrument (MSI) images of Sentinel-2 through Google Earth Engine (GEE) platform, achieving an overall accuracy of 97%. Additionally, the use of bidirectional reflectance distribution function (BRDF) signatures captured by multi-angle observation data has shown moderate improvements in land cover classification accuracy, with an overall validation accuracy increase of up to 4.9%. Furthermore, in mapping alpine grassland aboveground biomass, machine learning models like deep neural network (DNN) have demonstrated high accuracy, with DNN outperforming other models with an R2 of 0.818. These findings collectively suggest that Google Earth mapping can be highly accurate when utilizing advanced techniques and data sources.
What are the key design considerations for implementing RTL (Receive-Only) components in Doppler weather radar systems?
5 answers
Key design considerations for implementing RTL (Receive-Only) components in Doppler weather radar systems include optimizing the location of the radar system to mitigate clutter effectively, utilizing RF Front End modules operating in the S Band with specific characteristics like gain, noise figure, and dynamic range, and exploring advanced technologies like Solid State Weather Radar (SSWR) systems for minimal environmental impact and cost reduction. Additionally, in SSWR systems, accurate estimation of reflectivity for each polarization, reducing blind range, and joint design techniques for transmit waveforms and receive filters are crucial aspects that impact system performance and efficiency. By considering these factors, Doppler weather radar systems can enhance their functionality, accuracy, and sustainability in monitoring weather conditions.
What are effective strategies for reducing visual clutter in PowerPoint presentations?
5 answers
Effective strategies for reducing visual clutter in PowerPoint presentations include combining node ordering, edge sampling, and timeslicing methods to enhance layout readability and pattern identification. Additionally, utilizing a subspace-weighted mixed-norm minimization approach can improve clutter suppression performance by designing a weight vector based on the association between the dictionary matrix and the noise subspace. Moreover, keeping presentations simple by avoiding excessive information like images, text, and charts can prevent distractions and enhance clarity. Lastly, employing methods such as dimension reordering in parallel coordinate visualization can effectively lower visual clutter by minimizing clutter sums between attribute axes, resulting in a clearer and more visually understandable data analysis. By incorporating these strategies, PowerPoint presentations can maintain focus, improve comprehension, and enhance overall visual appeal.
What is parallax error?
5 answers
Parallax error refers to the mislocalization of findings in imaging techniques like scintigraphy and radar due to the displacement or uncertainty in the position of detected signals caused by oblique incidence or alignment issues. In medical imaging, parallax errors can affect the accurate determination of margins of large goiters, nodules, or ectopic tissues, emphasizing the importance of recognizing and correcting such errors. In radar systems, precise alignment of antennas is crucial to mitigate parallax errors and ensure accurate reflectivity measurements, especially in high-frequency systems with narrow beamwidths. Additionally, in PET scanners, parallax errors impact spatial resolution, with strategies like depth-of-interaction encoding showing promise in reducing axial blurring and improving resolution. Addressing parallax errors involves advanced simulation techniques and innovative solutions to enhance imaging accuracy across various fields.
How do artificial intelligence models, such as machine learning, handle complex structures in multivariate data for pattern recognition?
5 answers
Artificial intelligence models, particularly machine learning algorithms, address complex structures in multivariate data for pattern recognition by mapping input data to output through training and inference steps. These models leverage statistical approaches, neural networks, and methodologies from statistical learning theory to design recognition systems that consider various factors like pattern class definition, feature selection, and classifier design. Recent advancements, like the AlphaFold2 AI method, showcase the ability to identify rare structural motifs in protein crystal structures, indicating a grasp of subtle energetic influences beyond common patterns. Additionally, the integration of deep learning with quantum computation shows promise in efficiently processing layered interactions within data sets, overcoming classical model limitations through inherent parallelism and advanced algorithms.
What are the different methods exists in classification iin rejection? Cite paper for each kind.?
5 answers
Classification with rejection encompasses various methods to avoid misclassification in critical applications. One method involves utilizing an ensemble of cost-sensitive classifiers, which eliminates the need for estimating class-posterior probabilities, allowing for improved accuracy. This approach is detailed in a paper by Charoenphakdee et al.. Another method involves building budgeted, sequential classifiers with confidence-based reject options using a problem-specific genetic algorithm. This method considers objectives like accuracy, processing time/cost, and coverage, emphasizing Pareto efficiency. Hamilton and Fulp discuss this approach in their paper. Both methods offer innovative solutions to enhance classification systems by incorporating rejection mechanisms to mitigate risks associated with misclassification in error-critical scenarios.
What are the current advancements in UAV-borne InSAR systems and what are the future prospects for this technology?
5 answers
Current advancements in UAV-borne InSAR systems include improved baseline estimation methods to enhance accuracy and robustness. These systems face challenges due to unstable flight tracks and attitudes, making baseline estimation crucial for precise measurements. Future prospects for UAV-borne InSAR technology indicate its maturity for industrialization, with potential applications ranging from landmine detection to smart agriculture and search and rescue missions. The technology bridges the gap between space/aerial-borne and ground-based radar systems, offering the ability to conduct long scans rapidly, making it a valuable tool for various remote sensing applications. Additionally, the regulatory environment poses limitations on payload weight and operational flexibility, which may influence the technology's widespread adoption and commercialization.
How fast can an alligator run?
4 answers
Alligators can achieve impressive speeds both on land and in water. The high-speed stealth alligator, as described in Context_2, is designed to run on both water and land with the help of rotating wheels and possesses excellent stealth capabilities. In terms of natural behavior, research in Context_1 indicates that larger Crocodylia, including crocodiles, can reach significant velocities using various gaits, with trotting or bounding achieving similar speeds despite differences in gait types. Additionally, alligators have been observed to move quickly to bask in the sun for thermoregulation purposes, showcasing their agility and speed. Therefore, alligators exhibit remarkable speed capabilities both in engineered designs and natural locomotion behaviors.