Analysis and Mitigation of Phase Noise Effects in Linear Frequency Modulated Radar Systems

Phase noise presents a significant challenge in mod-ern radar systems, particularly those employing Linear frequency Modulation (LFM) waveforms. This paper presents a comprehensive analysis of phase noise effects on radar per-formance and evaluates various mitigation strategies. Through detailed simulation studies, we quantify the impact of phase noise levels ranging from 0 to 0.5 radians on Peak-to-Sidelobe Ra-tio (PSLR) performance. Results demonstrate significant PSLR degradation from −60.6 dB under ideal conditions to −32.7 dB under severe phase noise conditions. We implement and compare three mitigation techniques: window functions, phase compensation, and coherent integration. The coherent integration method proves most effective, achieving a 27.5 dB improvement in PSLR compared to uncompensated signals. Our analysis provides practical insights into phase noise mitigation strategies and their relative effectiveness, contributing to the development of more robust radar systems. The methodology and results presented offer valuable guidelines for radar system designers in selecting and implementing appropriate phase noise mitigation techniques based on specific performance requirements. Our analysis demonstrates a 27.5 dB improvement in PSLR compared to uncompensated signals, outperforming previous methods which achieved improvements of 15–20 dB

Authors

Institutions

Publication Details

Published
2024-12-31
DOI
https://doi.org/10.1109/ic-ftai62324.2024.10950048
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis and Mitigation of Phase Noise Effects in Linear Frequency Modulated Radar Systems

Hayman El-Sayed Hassan, Amgad A. Salama, Samy H. Darwish
Radar Systems and Signal Processing
article

Analysis and Mitigation of Phase Noise Effects in Linear Frequency Modulated Radar Systems

Hayman El-Sayed Hassan, Amgad A. Salama, Samy H. Darwish
article en

Abstract

Phase noise presents a significant challenge in mod-ern radar systems, particularly those employing Linear frequency Modulation (LFM) waveforms. This paper presents a comprehensive analysis of phase noise effects on radar per-formance and evaluates various mitigation strategies. Through detailed simulation studies, we quantify the impact of phase noise levels ranging from 0 to 0.5 radians on Peak-to-Sidelobe Ra-tio (PSLR) performance. Results demonstrate significant PSLR degradation from −60.6 dB under ideal conditions to −32.7 dB under severe phase noise conditions. We implement and compare three mitigation techniques: window functions, phase compensation, and coherent integration. The coherent integration method proves most effective, achieving a 27.5 dB improvement in PSLR compared to uncompensated signals. Our analysis provides practical insights into phase noise mitigation strategies and their relative effectiveness, contributing to the development of more robust radar systems. The methodology and results presented offer valuable guidelines for radar system designers in selecting and implementing appropriate phase noise mitigation techniques based on specific performance requirements. Our analysis demonstrates a 27.5 dB improvement in PSLR compared to uncompensated signals, outperforming previous methods which achieved improvements of 15–20 dB

Alexandria Higher Institute of Engineering and Technology (EG), Egyptian Consulting & Trading Co. Ltd (EG), Alexandria University (EG)
Climate action
Openalex Percentile: Top 52%
Radar Systems and Signal Processing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.