collaborators

5 papers

eess.SP2024

Sparse Spatial Smoothing: Reduced Complexity and Improved Beamforming Gain via Sparse Sub-Arrays

Yinyan Bu, Robin Rajamäki, Anand Dabak +3

This paper addresses the problem of single snapshot Direction-of-Arrival (DOA) estimation, which is of great importance in a wide-range of applications including automotive radar.…

eess.SP2024

Importance of array redundancy pattern in active sensing

Robin Rajamäki, Piya Pal

This paper further investigates the role of the array geometry and redundancy in active sensing. We are interested in the fundamental question of how many point scatterers can be i…

eess.SP2024

On array geometry and self-interference in full-duplex massive MIMO communications

Robin Rajamäki, Risto Wichman

This paper studies the role of the joint transmit-receive antenna array geometry in shaping the self-interference (SI) channel in full-duplex communications. We consider a simple s…

eess.SP2024

Harnessing Holes for Spatial Smoothing with Applications in Automotive Radar

Yinyan Bu, Robin Rajamäki, Pulak Sarangi +1

This paper studies spatial smoothing using sparse arrays in single-snapshot Direction of Arrival (DOA) estimation. We consider the application of automotive MIMO radar, which tradi…

eess.SP2024

Effect of Beampattern on Matrix Completion with Sparse Arrays

Robin Rajamäki, Mehmet Can Hücümenoğlu, Pulak Sarangi +1

We study the problem of noisy sparse array interpolation, where a large virtual array is synthetically generated by interpolating missing sensors using matrix completion techniques…