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NAVISP-EL1-034: AI-ENABLED BASEBAND ALGORITHMS FOR HIGH FIDELITY MEASUREMENTS - EXPRO+

on 10 December 2019

ESA Open Invitation to Tender AO10128
Open Date: 03/12/2019
Closing Date: 24/01/2020 13:00:00

Status: ISSUED
Reference Nr.: 19.154.22
Prog. Ref.: NAVISP Element 1
Budget Ref.: E/0365-10 - NAVISP Element 1
Special Prov.: BE+DK+DE+CH+GB+AT+NL+NO+FI+CZ+RO+FR
Tender Type: C
Price Range: 200-500 KEURO
Products: Satellites & Probes / RF / Microwave Communication (Platform and Payloads) / RF Comm. Eng. SW / SW for RF Comm. design, analysis, simulation, etc.
Technology Domains: RF Systems, Payloads and Technologies / Radio Navigation Systems/Subsystems / Ground Receivers
Establishment: ESTEC
Directorate: Directorate of Navigation
Department: Strategy and Programme Department
Division: NAVISP Programme Office
Contract Officer: Papaioannou, Maria
Industrial Policy Measure: N/A - Not apply
Last Update Date: 10/12/2019
Update Reason: Loaded a new Clarification(English version)

Critical applications such as autonomous vehicles and machine control require high fidelity raw measurements and position in challenging environments. One of the main challenges lie in handling transfer functions from baseband signal samples to high quality / high fidelity raw measurements and use them adequately in highly hybridized PNT engines. AI-based capabilities has become very accessible, for instance thanks to key technologies made available in open source, and meanwhile, the GNSS community is collecting more and more raw data which could support machine-based learning processes. In this context, artificial intelligence and machine learning can catalyse the empirical design process of baseband algorithms, fed by the ever-growing availability of real data collected by more and more users. The objectives of the proposed activity are to: - establish a new paradigm in the design of innovative GNSS algorithms, leveraging on artificial intelligence and fed by collected data in field trials, to provide high-fidelity measurements as well as quality indicators; - Breadboard the innovative algorithms and demonstrate their performances with field trials.

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