The ARL Multi-Modal Sensor: A Research Tool for Target Signature Collection, Algorithm Validation, and Emplacement Studies

Abstract

The U.S. Army Research Laboratory (ARL) has a significant program involving the development of UGS (unattended ground sensors) that addresses a variety of military and government missions. ARL's program involves practically every aspect of sensor development including devices, detection and fusion algorithms, communications, and command and control. One element of the ARL UGS program involves the development of low cost sensing techniques for the urban environment and one embodiment of this effort is the multi-modal sensor (MMS). The program objectives of this effort were to develop a networked personnel detection sensor with the following major criteria: low cost in volume production, support for MOUT (military operations in urban terrain) missions, and employ non-imaging sensor diversity techniques. The MMS sensor was an early prototype intended to demonstrate that low cost sensing techniques were suitable for the urban environment and a viable alternative to higher cost and fidelity sensors for some applications. The MMS is used today as a demonstration system and a test bed for many facets of urban sensing. This chapter describe many aspects of the MMS design including: hardware, software, and communications. The detection algorithms was described including the collection of target signatures and validation of algorithm performance. Finally, MMS usage in a force protection application was described including issues encountered when integrating into a larger system.

Cite

Text

Houser and Zong. "The ARL Multi-Modal Sensor: A Research Tool for Target Signature Collection, Algorithm Validation, and Emplacement Studies." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007. doi:10.1109/CVPR.2007.383530

Markdown

[Houser and Zong. "The ARL Multi-Modal Sensor: A Research Tool for Target Signature Collection, Algorithm Validation, and Emplacement Studies." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007.](https://mlanthology.org/cvpr/2007/houser2007cvpr-arl/) doi:10.1109/CVPR.2007.383530

BibTeX

@inproceedings{houser2007cvpr-arl,
  title     = {{The ARL Multi-Modal Sensor: A Research Tool for Target Signature Collection, Algorithm Validation, and Emplacement Studies}},
  author    = {Houser, Jeff and Zong, Lei},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2007},
  doi       = {10.1109/CVPR.2007.383530},
  url       = {https://mlanthology.org/cvpr/2007/houser2007cvpr-arl/}
}