Multiple target vehicles detection and classification based on low-rank decomposition

Teeradache Viangteeravat, Amir Shirkhodaie, Haroun Rababaah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

There are many advantages of using acoustic sensor arrays to perform targets of interest identification and classification in the battlefield. They are low cost and have relatively low power consumption. They require no line of sight and provide many capabilities for target detection, bearing estimation, target tracking, classification and identification. Furthermore, they can provide cueing for other sensors and multiple acoustic sensors responses can be combined and triangulated to localize an energy source target in the field. In practice, however, many environment noise, time-varying, and uncertainties factors affect their performance in detecting targets of interest reliably and accurate. In this paper, we have proposed a novel feature extraction approach for robust classification and identification of moving target vehicles to reduce those factors. The approach is based on Low Rank Decomposition based L p norm. Using Low Rank Decomposition based L 1 norm where p = 1, dominant features of vehicle acoustic signatures can be extracted appropriately with respect to vehicle operational responses and used for robust identification and classification of target vehicles. The performance of the proposed approach has been evaluated based on a set of experimental acoustic data from multiple vehicle test-runs. It is demonstrated that the approach yields significant improvement results over our earlier vehicle classification technique based on Singular Value Decomposition (SVD) and reduces uncertainties associated with classification of target vehicles based on acoustic signatures at different operation speeds in the field.

Original languageEnglish (US)
Title of host publicationAutomatic Target Recognition XVII
DOIs
StatePublished - Nov 15 2007
EventAutomatic Target Recognition XVII - Orlando, FL, United States
Duration: Apr 10 2007Apr 12 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6566
ISSN (Print)0277-786X

Other

OtherAutomatic Target Recognition XVII
CountryUnited States
CityOrlando, FL
Period4/10/074/12/07

Fingerprint

Vehicle Detection
Target Detection
vehicles
Acoustics
decomposition
Decompose
Target
acoustics
Target tracking
norms
Signature
sensors
Bearings (structural)
Uncertainty
Sensor
signatures
Sensor Array
Moving Target
test vehicles
Lp-norm

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Viangteeravat, T., Shirkhodaie, A., & Rababaah, H. (2007). Multiple target vehicles detection and classification based on low-rank decomposition. In Automatic Target Recognition XVII [65660R] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 6566). https://doi.org/10.1117/12.718770

Multiple target vehicles detection and classification based on low-rank decomposition. / Viangteeravat, Teeradache; Shirkhodaie, Amir; Rababaah, Haroun.

Automatic Target Recognition XVII. 2007. 65660R (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 6566).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Viangteeravat, T, Shirkhodaie, A & Rababaah, H 2007, Multiple target vehicles detection and classification based on low-rank decomposition. in Automatic Target Recognition XVII., 65660R, Proceedings of SPIE - The International Society for Optical Engineering, vol. 6566, Automatic Target Recognition XVII, Orlando, FL, United States, 4/10/07. https://doi.org/10.1117/12.718770
Viangteeravat T, Shirkhodaie A, Rababaah H. Multiple target vehicles detection and classification based on low-rank decomposition. In Automatic Target Recognition XVII. 2007. 65660R. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.718770
Viangteeravat, Teeradache ; Shirkhodaie, Amir ; Rababaah, Haroun. / Multiple target vehicles detection and classification based on low-rank decomposition. Automatic Target Recognition XVII. 2007. (Proceedings of SPIE - The International Society for Optical Engineering).
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