A mmW image-based algorithm on wire recognition for DVE applications

Darren S. Goshi; Ming-Ting Sun; John Kirk Jr.

doi:10.1117/12.2262250

5 June 2017 A mmW image-based algorithm on wire recognition for DVE applications

Darren S. Goshi, Ming-Ting Sun, John Kirk Jr.

Proceedings Volume 10197, Degraded Environments: Sensing, Processing, and Display 2017; 101970C (2017) https://doi.org/10.1117/12.2262250
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

In this work, we present the framework surrounding the development of a mmW radar image-based algorithm for wire recognition and classification for rotorcraft operation in degraded visual environments. While a mmW sensor image lacks the optical resolution and perspective of an IR or LIDAR sensor, it currently presents the only true see-through mitigation under the heaviest of degraded vision conditions. Additionally, the mmW sensor produces a high-resolution, radar map that has proven to be exceedingly interpretable, especially to a familiar operator. Seizing on these clear advantages, the mmW radar image-based algorithm is trained and evaluated against independent mmW imagery data collected from a live flight test in a relevant environment. The foundation of our approach is based on image processing and machine learning techniques utilizing radar-based signal properties and sensor and platform information for added robustness. We discuss some of the requirements and practical challenges of a standalone algorithm development, and lastly, present some preliminary examples using existing development tools and discuss the path for continued advancement and evaluation.

Citation Download Citation

Darren S. Goshi, Ming-Ting Sun, and John Kirk Jr. "A mmW image-based algorithm on wire recognition for DVE applications", Proc. SPIE 10197, Degraded Environments: Sensing, Processing, and Display 2017, 101970C (5 June 2017); https://doi.org/10.1117/12.2262250

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