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Jamming and Spoofing Resilient Deep Learning Based Software-Defined Multi-Antenna Multi-GNSS Receiver (JASMINE)

Sector: Telecommunications • Location: Finland

Source: EU Funding & Tenders Portal

Project
Ended

The Global Navigation Satellite Systems (GNSS) technology is known for precise positioning and timing capability that is of use in diverse fields of science and technology. The rapid development in this field by various nations in terms of deploying new satellite systems (GPS, GLONASS, Galileo, COMPASS, IRNSS/NAVIC), new signals in different frequency bands (L1, L2, L5, G1, G2, E1, E5a, E5b, B1, B

Status
Closed
Sector
Telecommunications, Government
Location
Finland
Updated
22 Jul 2026
Source
EU Funding & Tenders Portal

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The project “Jamming and Spoofing Resilient Deep Learning Based Software-Defined Multi-Antenna Multi-GNSS Receiver (JASMINE)” is an infrastructure initiative in the Telecommunications sector, located in Finland. Taiyo aggregates data on it from EU Funding & Tenders Portal.

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Sponsoring Agency

Status

Original status

ended

Taiyo status

Closed

Taiyo last update

2026-07-22

Contact

Not available for this record.

Description

Description

The Global Navigation Satellite Systems (GNSS) technology is known for precise positioning and timing capability that is of use in diverse fields of science and technology. The rapid development in this field by various nations in terms of deploying new satellite systems (GPS, GLONASS, Galileo, COMPASS, IRNSS/NAVIC), new signals in different frequency bands (L1, L2, L5, G1, G2, E1, E5a, E5b, B1, B2, B3, etc.) is changing the trend of GNSS receiver design. Especially, the intrinsic flexibility of software-based receiver design approach is becoming a competitor to even highly developed ASICs. The goal of this project is to develop ‘Jamming and Spoofing Resilient Deep Learning based Software-Defined multi-antenna GNSS Receiver (JASMINE)’. JASMINE is a multi-antenna multi-system dual-band GNSS receiver with autonomous integrity ability. In this project we propose to build a novel design approach for software defined GNSS receiver, combining deep learning (DL) approach with the expert knowledge to replace existing GNSS receiver algorithms. Novel techniques are proposed for multi-GNSS signal acquisition, denoising, orbit determination (Satellite position estimation), threat detection and mitigation (due to jamming, spoofing and ionosphere) by applying prominent deep neural networks (2D CNN, BiLSTM, RNN/LSTM, 1D CNN) and deep reinforcement learning (actor-critic (RNN/LSTM, 2D CNN), Sarsa, Q-learning, Policy Gradients) methods that add intelligence and give unseen capabilities to JASMINE in comprehending an increasingly complex environment. The proposed JASMINE supports all GNSS RF-frequencies (compatible with new signals), inherits the superiority of signal and navigation processing algorithms through Deep learning technology, and thus presents excellence performance. To achieve reconfigurability and optimized performance, Graphics processing unit (GPU) based Software Defined Radio (SDR) approach is preferred for JASMINE.

Location

Country

Finland

Source

Source

EU Funding & Tenders Portal

URL

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Record type

Project

Sector

Telecommunications, Government

Article published date

2026-02-01

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