Sensor Selection using the Two-Target Cramér-Rao Bound for Angle of Arrival Estimation
conference paper
Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cramer-Rao bound has been adopted previously for sparse sensing, it did ´ not consider multiple targets and unknown source models. We propose to tackle the sensor selection problem for angle of arrival estimation using the worst-case Cramer-Rao bound of two uncorrelated sources. We cast ´ the problem as a convex semi-definite program and retrieve the binary selection by randomized rounding. Through numerical examples related to a linear array, we illustrate the proposed method and show that it leads to the selection of elements at the edges plus the center of the linear array.
TNO Identifier
991622
Publisher
IEEE
Source title
Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, June 2023
Files
To receive the publication files, please send an e-mail request to TNO Repository.