Multistatic Data Fusion for GNSS-Based Air-to-Air Passive Radar

This work addresses the use of a global navigation satellite system (GNSS)-based passive multistatic radar to enable non-cooperative air traffic situational awareness. The low transmit signal power of the GNSS signals is known to largely limit the detection capabilities in the GNSS-based passive bistatic radar case, even when employing a long integration time (LIT). To this end, the possibility of simultaneously employing several GNSS satellites as illuminators of opportunity (IoOs) is explored in this work as a means of improving the signal processing gain and, in turn, the detection performance. A common domain for integrating the bistatic results is defined and the needed transformations are implemented with the help of the chirp-Z transform (CZT). Simulation results employing several satellites confirm the successful domain transformation and the multistatic data fusion.

Authors

Institutions

Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/radar58436.2024.10993652
Citations
2
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
2.60
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multistatic Data Fusion for GNSS-Based Air-to-Air Passive Radar

Alexandra Filip, Alberto Arana Ragel
2 citations
Radar Systems and Signal Processing
2.60
article

Multistatic Data Fusion for GNSS-Based Air-to-Air Passive Radar

Alexandra Filip, Alberto Arana Ragel
article en
2 citations

Abstract

This work addresses the use of a global navigation satellite system (GNSS)-based passive multistatic radar to enable non-cooperative air traffic situational awareness. The low transmit signal power of the GNSS signals is known to largely limit the detection capabilities in the GNSS-based passive bistatic radar case, even when employing a long integration time (LIT). To this end, the possibility of simultaneously employing several GNSS satellites as illuminators of opportunity (IoOs) is explored in this work as a means of improving the signal processing gain and, in turn, the detection performance. A common domain for integrating the bistatic results is defined and the needed transformations are implemented with the help of the chirp-Z transform (CZT). Simulation results employing several satellites confirm the successful domain transformation and the multistatic data fusion.

Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
Affordable and clean energy
Openalex Percentile: Top 7%
Radar Systems and Signal Processing
2.60
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.