FPGA/ARM Design of Multibeam Adaptive Array for GNSS Receiver

A multibeam Adaptive Antenna Array (AAA) for the receivers of the Global Navigation Satellite Systems' (GNSS) signals is presented. The AAA channel signals are preprocessed by correlators. This increases the Signal-to-Noise Ratio (SNR) and allows to use the adaptive algorithms that employ the desired signals. The paper describes the details of the correlator implementation in a Field Programmable Gate Array (FPGA) as well as the implementation of the Matrix Inversion Lemma (MIL) Recursive Least Squares (RLS) algorithm for the AAA weights calculation that uses a core of the Advanced RISC Machine (ARM) processor which is a part of the Xilinx XCZU5EG System-on-Chip (SoC). The ARM processor computes the AAA weights using complex-valued double-precision arithmetic. One beam of the resulting 16 channel AAA occupies less than 1 % of all possible resources of the XCZU5EG FPGA which is a part of the SoC. One iteration of the adaptive algorithm (weights calculation) per beam takes about 0.015 ms. This allows to easily implement up to 16 beams of the considered AAA, which is a maximum possible number of the Global Positioning System (GPS) satellites visible at a certain point on the Earth surface at an arbitrary time moment. The designed adaptive algorithm also requires about 8 kB of external memory per AAA beam. The rest of the SoC resources and the external memory is used for other digital elements of the AAA/GNSS receiver, such as synchronization, data processing, etc., which are not considered in this paper.

Authors

Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/ewdts63723.2024.10873650
Primary Topic
Antenna Design and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

FPGA/ARM Design of Multibeam Adaptive Array for GNSS Receiver

Vladimir I. Tsarik, Victor I. Djigan, Dmitrii A. Bitsulia
Antenna Design and Optimization
article

FPGA/ARM Design of Multibeam Adaptive Array for GNSS Receiver

Vladimir I. Tsarik, Victor I. Djigan, Dmitrii A. Bitsulia
article en

Abstract

A multibeam Adaptive Antenna Array (AAA) for the receivers of the Global Navigation Satellite Systems' (GNSS) signals is presented. The AAA channel signals are preprocessed by correlators. This increases the Signal-to-Noise Ratio (SNR) and allows to use the adaptive algorithms that employ the desired signals. The paper describes the details of the correlator implementation in a Field Programmable Gate Array (FPGA) as well as the implementation of the Matrix Inversion Lemma (MIL) Recursive Least Squares (RLS) algorithm for the AAA weights calculation that uses a core of the Advanced RISC Machine (ARM) processor which is a part of the Xilinx XCZU5EG System-on-Chip (SoC). The ARM processor computes the AAA weights using complex-valued double-precision arithmetic. One beam of the resulting 16 channel AAA occupies less than 1 % of all possible resources of the XCZU5EG FPGA which is a part of the SoC. One iteration of the adaptive algorithm (weights calculation) per beam takes about 0.015 ms. This allows to easily implement up to 16 beams of the considered AAA, which is a maximum possible number of the Global Positioning System (GPS) satellites visible at a certain point on the Earth surface at an arbitrary time moment. The designed adaptive algorithm also requires about 8 kB of external memory per AAA beam. The rest of the SoC resources and the external memory is used for other digital elements of the AAA/GNSS receiver, such as synchronization, data processing, etc., which are not considered in this paper.

Affordable and clean energy
Openalex Percentile: Top 55%
Antenna Design and Optimization
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.