NASA · NASA-198 · record R0154

SWaP-efficient, fast-wavelength-steering and time-division-multiplexing lidar technology capable of multi-beam ranging and concurrent hyper-spectral imaging

National Aeronautics and Space Administration · GSFC: Goddard Space Flight Center

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Science
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

We propose to integrate next-generation lidar, compact hyperspectral imaging and Artificial Intelligence (AI) technologies to provide a new remote sensing measurement capability for a broad range of Earth and planetary science objectives.

Expected benefits

A groundbreaking lidar module consisting of a high-pulse-rate, fast-wavelength-tuning fiber laser and time-division-multiplexing receiver will make height measurements using 60 steerable beams with drastically increased efficiency compared to the state-of-the-art. Concurrent hyperspectral imaging will greatly enhance science capabilities and real-time, AI neural network analysis of the images will enable optimized data collection and on-board processing. Incorporating these multiple emerging technologies will substantially reduce instrument size, weight and power thereby enabling lower-cost SmallSat-class missions with enhanced scientific return compared to the present day

System outputs

Predictions

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported