A Comparative Study of LFM Reverberation Suppression Schemes

Suman, Jami Venkata; Seventline, J. Beatrice

doi:10.14257/ijfgcn.2017.10.4.10

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…Thus, the developed algorithm is feasible for tracking applications, but it does not efficiently suppress the color noise. Different LFM reverberation suppression schemes are discussed in [13]. Thus, the developed algorithms are feasible for target detection and tracking applications, but it does not efficiently suppress the color noise.…”

Section: Literature Surveymentioning

confidence: 99%

Linear frequency modulated reverberation suppression using time series models

Suman¹,

Hema

Jagadeesh³

2022

IJEECS

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When active radar and <span>sonar systems are used for target detection and tracking, boosting target detection, and tracking efficiency is the most important challenge in real-time reverberation. To eliminate reverberation when transmitting linear frequency modulated (LFM) signals, this study employs time series techniques such as autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA). The primary purpose of this research is to whiten LFM reverberation by transforming it to a fractional domain using the fractional Fourier transform (FrFT). The LFM reverberation is a highly coloured noise whose frequency fluctuates according to the stationary hitting frequency. As a reference signal, the proposed methods make use of the adjacent signal block. The effectiveness of FrFT-based AR, MA, and ARMA pre-whitening for LFM reverberation reduction was assessed, and the results were presente</span>d.

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Section: Literature Surveymentioning

confidence: 99%

Linear frequency modulated reverberation suppression using time series models

Suman¹,

Hema

Jagadeesh³

2022

IJEECS

Self Cite

View full text Add to dashboard Cite

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Investigation of Navigation Solutions for Better Accuracy in Position Estimations

Kumar

Dutt

Kumar

et al. 2021

Computational Intelligence in Pattern Recognition

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IoT Based Remote Patient Health Monitoring System

Ravi Kumar,

Chandra Sekhar Rao,

Venkata Suman

et al. 2024

E3S Web Conf.

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Regular health monitoring is essential for maintaining good health, but long hospital queues and the need for ambulatory monitoring in our fast-paced world underscore the necessity for a simple health monitoring system adaptable to various settings. This system addresses the increasing demand for monitoring primary health parameters, particularly among older individuals, where conventional healthcare infrastructure often falls short. To overcome these challenges, we propose a comprehensive health monitoring system leveraging Internet of Things (IoT) technology. By utilizing IoT, we can wirelessly capture and transmit health data, ensuring interoperability. Our system collects and transmits vital health parameters such as body temperature, blood pressure, pulse, and GPS location using an Arduino Board and Wi-Fi module for data processing and transmission, respectively. This approach allows for real-time data capture, analysis, and storage, with automatic alerts sent to healthcare professionals when critical conditions are detected. Overall, our system offers user-friendly health monitoring, timely intervention, and reduces the burden on overcrowded healthcare facilities.

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A Comparative Study of LFM Reverberation Suppression Schemes

Abstract: Abstract

Cited by 3 publications

References 4 publications

Linear frequency modulated reverberation suppression using time series models

Linear frequency modulated reverberation suppression using time series models

Investigation of Navigation Solutions for Better Accuracy in Position Estimations

IoT Based Remote Patient Health Monitoring System

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