Distributed Phased Multiple-Input Multiple-Output Radars for Early Warning: Observation Area Generation

This paper introduces a resource management approach for distributed multiple-input multiple-output (MIMO) radar systems equipped with phased array antennas. The approach focuses and adjusts narrow beams from all transmit and receive nodes to generate a regularly shaped observation area for reliable detection. Based on this, a structured early warning framework can be built by evenly arranging sufficient observation areas to cover the surveillance region and periodically scanning these areas for continuous monitoring. Observation area generation, a core technique for this framework, involves the joint optimization of beamforming weights for both transmit and receive nodes, as well as the beam dwell time. Our optimization strategy is designed to achieve two key objectives: minimizing beam dwell time to ensure rapid alerts for defense systems, and minimizing node transmit power to extend operational time while reducing the risk of intercept. To address the problem of observation area generation, we propose a two-stage method. The first stage uses the signal-to-clutter-plus-noise ratio (SCNR) as a new criterion to determine the transmit and receive beamforming weights. The second stage employs a power factor as an additional variable to scale the transmit beamforming weights under various beam dwell times, constructing a Pareto solution set for the problem. Numerical simulations validate the effectiveness of our method, demonstrating improved detection capabilities compared to monostatic phased array radar systems.

Authors

Institutions

Publication Details

Journal
Remote Sensing
Published
2024-08-19
DOI
https://doi.org/10.3390/rs16163052
Citations
3
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
3.90
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Distributed Phased Multiple-Input Multiple-Output Radars for Early Warning: Observation Area Generation

Gongjian Wen, Dengsanlang Luo
3 citations
Remote Sensing
Radar Systems and Signal Processing
3.90
article

Distributed Phased Multiple-Input Multiple-Output Radars for Early Warning: Observation Area Generation

Gongjian Wen, Dengsanlang Luo
article en
3 citations

Abstract

This paper introduces a resource management approach for distributed multiple-input multiple-output (MIMO) radar systems equipped with phased array antennas. The approach focuses and adjusts narrow beams from all transmit and receive nodes to generate a regularly shaped observation area for reliable detection. Based on this, a structured early warning framework can be built by evenly arranging sufficient observation areas to cover the surveillance region and periodically scanning these areas for continuous monitoring. Observation area generation, a core technique for this framework, involves the joint optimization of beamforming weights for both transmit and receive nodes, as well as the beam dwell time. Our optimization strategy is designed to achieve two key objectives: minimizing beam dwell time to ensure rapid alerts for defense systems, and minimizing node transmit power to extend operational time while reducing the risk of intercept. To address the problem of observation area generation, we propose a two-stage method. The first stage uses the signal-to-clutter-plus-noise ratio (SCNR) as a new criterion to determine the transmit and receive beamforming weights. The second stage employs a power factor as an additional variable to scale the transmit beamforming weights under various beam dwell times, constructing a Pareto solution set for the problem. Numerical simulations validate the effectiveness of our method, demonstrating improved detection capabilities compared to monostatic phased array radar systems.

Remote SensingVol. 16(16)
National University of Defense Technology (CN)
Decent work and economic growth
Openalex Percentile: Top 6%
Radar Systems and Signal Processing
3.90
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.

Distributed Phased Multiple-Input Multiple-Output Radars for Early Warning: Observation Area Generation — Gongjian Wen, Dengsanlang Luo · Remote Sensing (2024) | TGRS Research Map | TGRS