TY - GEN
T1 - 3D Orientation Estimation With Configurable Backscatter Arrays
AU - Rammal, Mohamad Rida
AU - Diggavi, Suhas
AU - Sabharwal, Ashutosh
N1 - Funding Information:
This work is supported in part by NSF grants 1955632, 2146838, 1956297.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - We consider the problem of estimating the orientation of a 3D object with the assistance of configurable backscatter tags. We explore the idea of designing tag response codes to improve the accuracy of orientation estimation. To minimize the difference between the true and estimated orientation, we propose two code design criteria. We also derive a lower bound on the worst-case error using Le Cam's method and provide simulation results for multiple scenarios including perfect and imperfect channel knowledge, comparing the performance of various coding methods against the suggested designs.
AB - We consider the problem of estimating the orientation of a 3D object with the assistance of configurable backscatter tags. We explore the idea of designing tag response codes to improve the accuracy of orientation estimation. To minimize the difference between the true and estimated orientation, we propose two code design criteria. We also derive a lower bound on the worst-case error using Le Cam's method and provide simulation results for multiple scenarios including perfect and imperfect channel knowledge, comparing the performance of various coding methods against the suggested designs.
UR - http://www.scopus.com/inward/record.url?scp=85136278583&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85136278583&partnerID=8YFLogxK
U2 - 10.1109/ISIT50566.2022.9834736
DO - 10.1109/ISIT50566.2022.9834736
M3 - Conference contribution
AN - SCOPUS:85136278583
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 1832
EP - 1837
BT - 2022 IEEE International Symposium on Information Theory, ISIT 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Symposium on Information Theory, ISIT 2022
Y2 - 26 June 2022 through 1 July 2022
ER -